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Essay: Self-driving cars

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Self-driving cars. Ten years ago, something like this would seem completely unbelievable. Now however, it’s becoming our reality. A lot of questions come to mind with this subject: how will this affect our lives? How will this affect our future? Is this good for us? Is this bad? These questions must be strongly considered and answered while looking at this subject. I think that this is a promising new field, but that makes a person ask many serious questions, and even involves the entire concept of comparing artificial intelligence to human intelligence. I think that while this type of vehicle has promise, it’s very hard to choose artificial intelligence over human intelligence. A lot of things must be figured out before this type of car can seriously challenge the people’s preference for cars that they have to drive themselves.

What are self-driving cars? Well, as is clear due to the name itself, these are cars that don’t need a driver to be driven. These cars use an artificial intelligence system to decide everything that is typically decided by the driver themselves. A person can presumably input the destination, and the car will do the rest on its own. In other words, it’s a form of a taxi cab owned by the passenger themselves. There is however much more to this than just that, these cars also make decisions normally made by human drivers, such as choosing the best routes and even calculating how to cause the least casualties in an accident. This is a very controversial subject, as these cars may prefer the owner/passenger die instead of others if it causes the least overall casualties. It’s not yet clear as to all the things that these cars will be able to do, but the general basics are clear: you sit back and let the car do the rest. An interesting question that isn’t often asked, is whether a person will need to have a driver’s license to be in this car. If the car does all the work, then why does a person need to know how to drive? Will there be an option for the person to drive the car themselves if they choose to do that? Unfortunately, these are all currently unanswered questions, what we do know for a fact, is that these are cars that drive the person themselves.

The idea that cars should drive themselves is as old as cars themselves. Putting this idea into motion however was only possible in modern times. The earliest prototype of such a car was the 1925 car made by Arden Motors, called the “Chandler”. This idea was also promoted by General Motors in the 1930’s and shown off at the world fair of 1939. It was even predicted that these cars would be common in the US by the 1960’s. In 1953, RCA Labs built a miniature prototype of such a car, again promoting this as a serious future option for consumers. The common issue with all these designs however, was that none of these were practical vehicles that people could buy or trust to work properly. These were all ideas and predictions but not practical working concepts. General Motors went a step further and created a series of cars called “Firebirds”, that were supposed to be self-driven cars that would be on the market by 1975. This became a popular topic in the media and led to many interested journalists and reporters to be allowed to test drive these cars. The excitement was there but the cars still were not able to be put on the market.

The 1960’s saw Ohio State University and the Bureau of Public Roads to continue the pursuit of putting this type of car on the market. The attempts however were again hard to get off the ground, and simple prototypes were the only thing that was able to be completed. Great Britain’s Transport and Road Research Laboratory was next to try and fail at this idea. In this version of the idea, magnetic cables were embedded in the roads, and a system called Citroen DS interacted with them to move the cars across roads. In the 1970’s, the Bendix corporation worked with Stanford University, to work on a concept involving cables that were buried in the ground, and that helped move cars on the road. I think that it is obvious why this didn’t work out in the end either. I think that it is important to mention that funding was a major problem for many of these ideas. As can be easily assumed, none of these features could possibly be done at affordable rates, and that they required large amounts of labor and large changes to the roads to accommodate these changes.

The Germans decided to get into this field in the 1980’s. Mercedes-Benz launched their own version of such a car, but their version could not move faster than 39 miles per hour, a number that was clearly far below the speed of an average car. Multiple American universities were next. Universities of Maryland and Michigan created prototypes that were able to travel on hard terrains at different speeds, but again that were not very fast. It seemed that the ability to make these cars fast was, yet another problem faced by the developers. In 1991, the United States Congress passed the ISTEA Transportation Authorization bill that pushed for a creation of an automatic transport system by 1997. By the late 1990’s, the university of Parma in Italy, and Daimler-Benz were able to create vehicles that could reach the speed of 81 mph. The issue of funding and efficient mass production however continued to plague these new advancements. The 2000’s saw even more progress, as Germany invented a “Spirit of Berlin” taxicab, and the Netherlands invented the ParkShuttle. Neither of these options was able to fully replace human driven transportation services, but they managed to be effective means of transportation regardless. By the end of the decade, most of the major car companies were working on making self-driven cars. Mercedes-Benz, Audi, Tesla, Toyota… are some of the more notable companies that were working on prototypes. Uber and Lyft began developing self-driven taxicabs in recent years to save money on drivers, and by making their business to run more smoothly and efficiently. In 2018, a woman was killed by an automated Uber vehicle, and Audi officially announced the release of a mass-produced line of self-driven cars.

What can be predicted about the future of this technology? Logically we can assume that with the current state of technology, better cars will be released, and practical self-driven cars will be readily available to the public. Will this idea take-off with the public? That is the harder question. There is really nothing that can be seriously predicted about how the public will react to this. Personally, I think that it will decades before people will be ready to replace cars that they can drive themselves, with self-driven cars. Why do I think so? I think that many people love driving and would not want to let “somebody else” do it for them. It’s also reasonable to assume that taxicabs may be less expensive than buying a self-driven car. There is also the issue with the cost. How much will these cars cost? Will the average driver be able to afford such a car? Will it be popular among the general population? There are too many unanswered and hard to answer questions about the topic. I do have one concern that comes to mind… the Industrial Revolution threatened entire industries, as many people lost jobs to basically machines. How many taxi drivers would be needed with self-driven cars in the equation? How many bus drivers would be required?

What kind of impact will such cars have on the general population? How will this affect hardware? How will this affect future software? How will it affect data? I think that this concept becoming more popular, will lead to increased funding for the development of new hardware and software pertaining to self-driven cars. It will also likely lead to new ideas for other areas. What about self-working computers? What about self-working irons and laundry machine/robots? There are a lot of concepts that can be thought of by thinking of self-operating hardware and software. There are a lot of things that can be thought of by simply thinking of self-working hardware and software. I think that it will lead to a major development of these concepts. It will also lead to major advancements in software in general, as well as artificial intelligence. If companies can successfully build artificial intelligence systems that will drive cars by themselves, a lot of other things can be made self-controlled as well. One thing that I think could be done successfully is computers that can-do things for you, for example your taxes or other accounting related tasks. I can even imagine self-driven planes and boats. Basically, there are a lot of advancements that can be made through self-working technology. It’s possibl e that driving a car will become less of a priority for people, and getting a driver’s license might become more of a novelty than a necessity. I also think that NASCAR and the popularity of racing can be affected by the popularity of self-made cars as well as the whole culture of driving. The main question for me is the cost of these cars. The affordability or lack of it will be a major reason as to why or why not this business concept will work. I have my doubts over the topic, as I think that many people enjoy driving and would not want to give it up. There is also a wide variety of taxicab services that are cheaper alternatives to owning a self-driving car. I’m also unclear on whether sports cars will be possible to be self-driven as well. The latter is important because of the popularity of such cars.

How will this technology change the way business is conducted? The main thing that comes to mind is the lack of a driver’s license when purchasing a car? Is it possible that there would be a lack of an age limit to buy a car too? I think that businesses would also come up with new marketing strategies to sell these cars, since driving would no longer be an important part of the marketing pitch. It would also be a potential issue for Uber and Lyft, as well as other taxicab and car service companies. It might even affect limo companies, as wealthy people might prefer very expensive self-driven cars. The big thing that comes to mind is that driving would not be an important component of owning a car. I think that it’s common sense that any change in business would lead to companies adjusting their strategies and marketing campaigns, and focusing on different areas to promote their ideas. It could also affect other businesses entirely as they would focus more on self-working concepts and products. As I mentioned earlier, a laundromat can use some type of a laundry machine/robot that would be doing laundry for you. Phone companies could come up with cell phones that work automatically in some way, and come up with phone plans for self-driving cars. Why? Well, now it would no longer be illegal to talk on the phone in your car. I mean why would it be when it wouldn’t distract you from driving? What about television screens in cars? The owner/passenger now has free time, doesn’t that seem to be a new business opportunity for companies like Netflix? I think that these would be the main things affected by self-driving cars and similar technology. Every new invention that changes the way people normally do things, is bound to change the marketplace and affect the way that companies handle their business expenditures.

How would self-driving cars affect competition between companies? There would be no reason for companies to focus on driving as a major part of their selling pitches. Commercials would no longer advertise the handling and driving of cars, as the person would not actually be driving it. Companies would compete for having technology in which the person would have to do the least to make it work. Companies would try to gain a competitive advantage against one another by adding features that would make the product do as much as possible by itself. I can imagine cars that incorporate other technology, can you imagine cars that do accounting for you? What about a competing company that makes a car that can call companies and have conversations for you? What about cars that would make decisions for you? What about cars that act as your secretaries while driving you? There is almost a limitless amount of possibilities that can be accomplished by a company aiming to stand out. This type of technology can of course be applied to other technologies as well. So now we’re talking about cell phones that call for you, cell phones that make decisions for you…. Basically, companies would take this technology to the extreme to compete. The spirit of competition has driven many industries to unprecedented highs, and so this industry will likely be no exception to this rule. The question would ultimately be about which companies would stay ahead of the curve, and which ones would not.

How do self-driving cars affect society in a global way? Well if this concept takes off, then countries will try to keep up with each other by improving on the technology and by attempting to avoid being “behind” others. It will be a major driving factor in the competition between major companies, and create new forms of advancement in other technologies. The global impact of such a technology is enormous and would change a lot of things as we know them. It’s certainly not going to be an isolated idea that only affects one country and one field, it will affect the whole world and affect multiple industries, including those that have nothing to do with the automobile industry.

Is there an ethical side to self-driving cars? A major question that comes to mind is whether it is a good idea to trust so much in artificial intelligence. What would happen if someone who doesn’t know how to drive is faced with a malfunctioning vehicle? What happens if these vehicles cause a multitude of accidents? Is it a good idea for our society to become more “lazy”? Should we really try to have something else do as much of our work as possible? This is an issue that can be debated ad nauseum without a generally agreed upon answer or a solution. Personally, I think that giving so much authority to machines is dangerous, how long before we start putting machines in leadership positions and becoming completely incompetent without them? We rely on the internet, cell phones, cars, and social media daily, how would many of us survive if all these options were taken away? Why do we need a car to drive itself? Why can’t a person do it themselves? Why is this improvement even needed? There seems to be an endless supply of questions on this subject. Personally, I think that my position on the subject has been made clear. I don’t think that self-driven cars are as much a necessity as it seems to be, and that the current state of transportation is a better and more efficient way of doing things.

What are the legal repercussions of self-driving cars? What happens if the car owner gets into an accident? Is the person responsible or is the car? If it’s the car, what’s going to happen next? Obviously, nobody will arrest the car, so does this mean that no one is in trouble if their car runs someone over? How do we define right and wrong when it comes to artificial intelligence? Will any of these cars be able to both be controlled by people and artificial intelligence? In that case, could someone run another person over with a car and then blame it on artificial intelligence? How would law enforcement be able to prove what happened? Would the company itself be responsible? Once again, we enter a new reality filled with many different possibilities and new rules required to administer them. It seems pretty clear to me that self-driving cars will need a whole new set of laws to determine accidents that will almost certainly happen regardless of whether the driver is human or not.

As the advancement of self-sustaining technology arises, so does the general concern that I stated earlier. Driverless cars can either be a technology that benefits the population or that is detrimental to society. From the information that I found and my own opinion on these cars, my views are that it would be detrimental. Specifically, due to the life – death calculations that the artificial intelligence can make. An example being to avoid multiple causalities, AI may calculate that putting your life on the line is the correct way to go. I’d argue this as being something the AI should never be able to decide. More or less because it can’t use emotional intuition to make choices that involve life or death . All things considered we came a long way with our technology, and so did the concept of cars that drive themselves. Our society is bound to be affected by a step of this magnitude, but a lot of factors must be taken into consideration, to make a true judgment on the matter. Self-driving cars will either change driving as we know it, or become a failed attempt to fix something that did not need fixing.

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Argumentative Essay On Self-Driving Cars

Self-driving cars are still in the early stages of development, but they have the potential to revolutionize transportation. They could reduce accidents, relieve congestion, and provide new mobility options for seniors and people with disabilities. But there are also concerns about safety and privacy.

Expertise Final Project Over the past ten years, those that have been old enough to be aware of their surroundings know how drastic technology has changed over the years. New and greatly improved ways of communicating, entertainment, and transportation have been introduced, and they’ve been introduced at increasing and astonishing rates. Transportation is used daily by majority of people worldwide. In urban settings, commuters find it difficult to drive and get where they need to when roadways are congested and their commutes are long.

Frustration, fatigue and anger derive from this difficulty. While travelers experience this n the road, their ability to drive isn’t safe for themselves and others, and often these are the reasons for most accidents. Simple mistakes that are caused by this are often inevitable and could be changed if daily travelers didn’t have to worry about being the ones controlling the vehicle. The world today relies on technology to do most things for themselves, and a car that could drive itself would significantly assist people universally.

Recent testing done by Google with development of autonomous cars has the attention of people globally on the dramatic change that an advancement such as self-driving ediums would bring into society if it’s introduced within the upcoming years. Self-driving cars are safe, modern, and an updated way of transportation that will benefit people worldwide in the upcoming future. Bus and taxi services will become simplified and obtainable for pedestrians who need quick transportation.

Should Self-Driving Cars Be Legal

There are also concerns about legal liability. If a self-driving car gets into an accident, who is responsible? The driver? The car manufacturer? The software company? This is still a relatively new technology, and the laws have not caught up yet.

Self-driving cars also raise ethical questions . For example, what should the car do if it gets into an accident? Should it try to save the lives of the passengers, even if that means sacrificing the lives of pedestrians? These are tough questions that need to be considered before self-driving cars become more widespread.

Overall, there are many factors to consider when it comes to self-driving cars. Safety, legal liability, and ethics are just a few of the issues that need to be addressed. Self-driving cars have the potential to revolutionize transportation, but there are still many hurdles to overcome before they can be fully accepted by society.

Self-driving cars are becoming increasingly prevalent on roads across the globe. But, should they be legal? Some experts say yes, as they can help to reduce accidents and improve traffic flow. Others believe that self-driving cars are too dangerous and unpredictable to be allowed on public roads.

This travel method would be quick, safe, and reliable. Self-driving cars will be useful for society in the commute of passengers, although it should have limited usage on the roads today. Annually, there’s an estimate of more than 37,000 people that are killed in the US due to traffic related ccidents. 93-95% of these accidents are due to simple human error (Peterson, Peters). Whether it was a mistake that could’ve been prevented or if it was unavoidable, humans are unfortunately flawed in numerous ways while behind the wheel.

Most commonly today, the biggest preventable reasons behind fatal accidents are drunk driving and distraction with technology. Although both are illegal, our country is still faced yearly with frequent deaths with correctable causes. It’s nearly impossible to prevent humans with the ability to drive to refrain from being behind the wheel with no distractions, but the rogress of Google’s self-driving software makes it possible to program robots to do this. It’s clear that cars are one of the best and worst things invented.

Counter Argument For Self-Driving Cars

Self-driving cars are becoming increasingly popular, but there are still many who are skeptical of them. Some people argue that self-driving cars are not safe, and that we should not be trusting them with our lives. Here is a counter argument to that claim.

Self-driving cars have been tested extensively and have proven to be much safer than human-driven cars. In fact, studies have shown that self-driving cars are far less likely to get into accidents than human-driven cars. Self-driving cars also have the potential to reduce traffic congestion and save lives.

Critics of self-driving cars often argue that we should not be trusting them with our lives. However, it is important to remember that human drivers are responsible for the majority of accidents on our roads. In fact, studies have shown that human error is responsible for 94% of all car accidents. Self-driving cars have the potential to drastically reduce the number of accidents on our roads, and save lives in the process.

There are still many skeptics of self-driving cars, but it is important to remember that they have the potential to make our roads much safer. Self-driving cars have been tested extensively and have proven to be much safer than human-driven cars. In addition, self-driving cars have the potential to reduce traffic congestion and save lives. We should not be afraid to trust self-driving cars with our lives, as they have the potential to make our roads much safer.

More so best for a great deal of reasons, although cars have caused an unreal amount of fatalities and accidents that have caused serious injuries to people that may or may not have been at fault. The amount of people that die from car related accidents is equal to 737 jet planes crashing weekly (Peterson, Peters). The general population is aware that human drivers aren’t always substantial for operating vehicles, but self-driving technology ould make it a safer option and ability to transport commuters on a daily basis.

The driverless car is one of the most promising new technologies of our time. The potential for these vehicles to transform the way we live and work is staggering. But as with any new technology, there are also concerns about safety and security. In this essay, we will explore the pros and cons of driverless cars .

On the plus side, driverless cars have the potential to make our roads much safer. By removing human error from the equation, driverless cars could dramatically reduce the number of accidents on our roads. They could also help to ease congestion, as they can communicate with each other to optimize routes and avoid traffic jams.

On the downside, driverless cars could pose a threat to people’s privacy. If data from driverless cars is collected and shared, it could be used to track people’s movements and even spy on them. There are also concerns that driverless cars could be hacked, and used for malicious purposes.

Overall, driverless cars hold great promise. But as with any new technology, there are also some risks that need to be considered.

Since the autonomous cars had been initially introduced into testing in 2009, there’s been only 16 very minor accidents. Each of these accidents had cases of the other human drivers being at fault (Richtel, Dougherty). Therefore, the only unsafe factors in the autonomous cars are humans themselves. With statistics and testing results in mind, self-driving cars are developed to be an exceptional safe traveling method. As people age into their senior years of life, they lose the ability to attentively operate a vehicle. Their senses of being aware of the details of their surroundings that are necessary to drive are lost.

For most elders, they never wish to stop driving. The same concept goes for those with disabilities they’re born with, blindness, and even more tragically for those that have suddenly lost the ability to drive at a younger age. The freedom and capabilities to access transportation easily on our own should never have to end. Drivers will simply have the ability to type in or speak into their cars of their destination and let the car do the work (Dallegro). Introducing self-driving cars into ociety today will benefit everybody, especially for the impaired.

Google is developing self-driving vehicles to operate without the help of a human through exact accuracy of mapping software and sensors surrounding the car (Sage). The prototype uses Laser Illuminating Detection and Ranging (Lidar), used for 3D mapping for the car and four radars surrounding it to detect speeds of others. It includes high powered cameras that allows to see precisely around the car in the range of 30 meters, sonar for sound related detection, specific positioning, and other state of the art software (Clark).

As of 2014, there was already over 2,000 miles of the four million miles in the world mapped out for the self-driving cars (Madrigal). A year later, the Google self- driving cars have logged 70,000 miles during their test driving (Clark). Boris Sofman from The Atlantic quotes, “We are able to turn the physical world into a virtual world”. Rather than having the software be simple mapping for the self-driving cars, the programming scientists are creating are precise enough to know how high a traffic light is off the ground or how many inches high a curb to the side of the road is (Madrigal).

As a result, the autonomous vehicle is able to accurately detect its surroundings to perform accordingly. China, globally known for being one of the most thriving countries in production and growth, plan on having self-driving technology in transportation methods on their roads within the next two years (Walker). The Chinese will likely have fully functioning features of the self-driving software on the road before the US, but we’re expected to closely follow. Companies such as Baidu and Yutong located in China have done numerous public transportation demonstrations of the notion.

The culture and government is more open to the idea currently than it is in America. It’s most probable that China will see the features first used in public transit, taking the place of bus and taxi services (Walker). In large cities of the region, majority of individuals that own a motor vehicle only use it for the sake of the commute to work positions. With plans of self- driving technology on roadways, it’s anticipated that a large number of the population will not feel the need to own a car, making fuel and vehicles costs for individuals decrease significantly.

Furthermore, the economic conditions will be mproved drastically in terms of allowing the population to travel in a conveniently practical way of simplified traveling in a fuel efficient method. Following this, environmental conditions will also remarkably improve. Opposing opinions on self-driving vehicles are argued for appropriate and understandable rationale. Driving a vehicle as a human gives us a sense of freedom in having the ability ourselves to drive at our own speed, rate, and go the routes we choose to take.

Entertainment with driving and operating different vehicles has been popular since cars were first invented. In fact, the biggest distinguished eason why people are against autonomous cars is because it’s seen as too safe and restricts traveler’s freedom (Richtel, Dougherty). Many consider race-car driving to be a sport, and the change in demand for self-operated vehicles in the near future could change the possibility of continuing careers and hobbies with cars.

There would be no reason to make cars different when they each perform the same functions. Another reason why allowing self-driving programs to fully control cars is a controversial idea is due to the issue of who would be considered at fault if their was an accident between two self- riven automobiles. Insurance companies haven’t jumped on board of the idea of this technology yet for this justification. How would you be able to know who’s liable when the human didn’t have any contact or ability to correct the self-driving car’s actions?

Humans have the capability of using their own judgement while driving to step outside of legal boundaries in cases of emergency. A self-driving vehicle lacks this since it’s programmed to obey any and all laws that are presented on the roadways (Peterson, Peters). Lacking these human senses and abilities while utilizing a vehicle could lead to difficulty in the erformance of the self-driving car. The movement of self- driving software has been transitioning rapidly across the globe, with features already presented in major car companies such as BMW, Mercedes, and Tesla (Greenough).

Though the features to brake and park on a vehicle’s own has impressed its users, the advanced softwaring of a fully functionable self-automated car will be a major step into the economic, travel, and environment changes that are valuable in the physical world today. Society has become reliant on the technology that does things for themselves, and allowing mechanical methods of commuting to e done by itself would buy the population the time and energy that most need.

The United States started with their ways of travel to be done without help through horse and buggy a century ago, and the method will be brought back into the current society with autonomous software (Hirisch). With an estimate of over a billion dollars spent in the course of the next decade, the future for autonomous vehicles is reachable (Sage). The self-driving car is a major step forward in today’s technological abilities that’s expected to arrive sooner in our society than what the world may envision.

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February 3, 2018

Are Autonomous Cars Really Safer Than Human Drivers?

Most comparisons between human drivers and automated vehicles have been at best uneven—and at worst unfair

By Peter Hancock & The Conversation US

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The following essay is reprinted with permission from The Conversation , an online publication covering the latest research.

Much of the push toward self-driving cars has been underwritten by the hope that they will save lives by getting involved in fewer crashes with fewer injuries and deaths than human-driven cars. But so far, most comparisons between human drivers and automated vehicles have been at best uneven, and at worst, unfair.

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The statistics measuring how many crashes occur are hard to argue with: More than 90 percent of car crashes in the U.S. are thought to involve some form of driver error . Eliminating this error would, in two years , save as many people as the country lost in all of the Vietnam War .

But to me, as a human factors researcher , that’s not enough information to properly evaluate whether automation may actually be better than humans at not crashing. Their respective crash rates can only be determined by also knowing how many non-collisions happen. For human drivers is it one collision per billion chances to crash, or one in a trillion ?

Assessing the rate at which things do not happen is extremely difficult. For example, estimating how many times you didn’t bump into someone in the hall today relates to how many people there were in the hallway and how long you were walking there. Also, people forget non-events very quickly, if we even notice them happening. To determine whether automated vehicles are safer than humans, researchers will need to establish a non-collision rate for both humans and these emerging driverless vehicles.

Comparing appropriate statistics

Crash statistics for human-driven cars are compiled from all sorts of driving situations, and on all types of roads. This includes people driving through pouring rain, on dirt roads and climbing steep slopes in the snow. However, much of the data on self-driving cars’ safety comes from Western states of the U.S., often in good weather. Large amounts of the data have been recorded on unidirectional, multi-lane highways, where the most important tasks are staying in the car’s own lane and not getting too close to the vehicle ahead.

Automated cars are rather good at those kinds of tasks – but then again, so are humans. The data on fully automated systems will naturally expand to cover more roads as states allow automated vehicles to operate more widely. But it will take some time before self-driving cars can cover as many miles in a year and in as many circumstances as human drivers presently do.

It is true that self-driving cars don’t get tired, angry, frustrated or drunk . But neither can they yet react to uncertain and ambiguous situations with the same skill or anticipation of an attentive human driver, which suggests that perhaps the two still need to work together . Nor do purely automated vehicles possess the foresight to avoid potential peril: They largely drive from moment to moment, rather than thinking ahead to possible events literally down the road .

To an automated vision system, a bus shelter full of people might appear quite similar to an uninhabited corn field . Indeed, deciding what action to take in an emergency is difficult for humans, but drivers have sacrificed themselves for the greater good of others . An automated system’s limited understanding of the world means it will almost never evaluate a situation the same way a human would. And machines can’t be specifically programmed in advance to handle every imaginable set of events .

New tech brings new concerns

Some people may argue that the promise of simply reducing the number of injuries and deaths is enough to justify expanding the use of driverless cars. I do agree that it would be a great thing if tomorrow were the dawn of a new day when a completely driverless roadway killed or injured no one; although such an arrangement might suck more of the enjoyment from our everyday lives, especially for those who love driving.

But experience from aviation shows that as new automated systems are introduced, there is often an increase in the rate of adverse events . Though temporary, this potential uptick in the crash rate may cause concern for the general public and then politicians, lawmakers and even manufacturers – who might be discouraged from sticking with the new technology.

As a result, comparisons between humans and automated vehicles have to be performed carefully. This is particularly true because human-controlled vehicles are likely to remain on the roads for many years and even decades to come. How will people and driverless cars mix together, and who will be at fault for any collisions between them?

To fairly evaluate driverless cars on how well they fulfill their promise of improved safety, it’s important to ensure the data being presented actually provide a true comparison. Choosing to replace humans with automation has more effects than simply a one-for-one swap . It’s important to make those decisions mindfully.

This article was originally published on The Conversation . Read the original article .

Self Driving Cars - Free Essay Examples And Topic Ideas

Self-driving cars, a burgeoning field within automotive technology and artificial intelligence, promise to revolutionize transportation. Essays might explore the technological advancements enabling autonomous vehicles, the potential benefits regarding safety, efficiency, and environmental impact. Moreover, discussions might extend to the ethical, legal, and societal challenges posed by self-driving cars, such as data privacy, liability in case of accidents, and the potential displacement of jobs. We have collected a large number of free essay examples about Self Driving Cars you can find at PapersOwl Website. You can use our samples for inspiration to write your own essay, research paper, or just to explore a new topic for yourself.

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The automobile company is drastically changing over the years. Due to advancements in technology, driverless cars are in the near future. A self-driving car is a motor vehicle that is capable of automated driving and navigating entirely without direct human input. Autonomous cars are able to use cameras, sensory, GPS location, and computer systems to operate accurately and efficiently. Driverless cars have quickly become the most discussed new technologies that will be arriving within the next few years. Once these […]

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How To Write an Essay About Self Driving Cars

Understanding self-driving cars.

Before writing an essay about self-driving cars, it's essential to comprehend what they are and the technology behind them. Self-driving cars, also known as autonomous vehicles, are cars or trucks in which human drivers are never required to take control to safely operate the vehicle. These vehicles use a combination of sensors, cameras, radar, and artificial intelligence to navigate and drive. Begin your essay by explaining the technology that enables these cars to operate, including machine learning and sensor fusion. Discuss the different levels of vehicle automation, from partially automated to fully autonomous, and the key companies and players in the field.

Developing a Thesis Statement

A strong essay on self-driving cars should be anchored by a clear, focused thesis statement. This statement should present a specific viewpoint or argument about autonomous vehicles. For example, you might discuss the potential impact of self-driving cars on safety and traffic, analyze the ethical implications of autonomous driving decisions, or explore the challenges facing widespread adoption. Your thesis will guide the direction of your essay and provide a structured approach to your analysis.

Gathering Supporting Evidence

Support your thesis with relevant data, research, and examples. This might include studies on the safety of self-driving cars, surveys on public opinion regarding autonomous vehicles, or real-world data on traffic efficiency and environmental impact. Use this evidence to support your thesis and build a persuasive argument. Remember to consider different perspectives and address potential counterarguments to your thesis.

Analyzing the Impact of Self-Driving Cars

Dedicate a section of your essay to analyzing the potential impact of self-driving cars. Discuss various aspects, such as the implications for road safety, changes in transportation infrastructure, and effects on industries like insurance and logistics. Explore both the potential benefits and drawbacks, ensuring a balanced view. For instance, consider how autonomous vehicles could reduce accidents caused by human error but might also lead to challenges in cybersecurity and data privacy.

Concluding the Essay

Conclude your essay by summarizing your main points and restating your thesis in light of the evidence and discussion provided. Your conclusion should tie together your analysis and emphasize the significance of self-driving cars in shaping the future of transportation. You might also want to highlight areas where further research or development is needed, or the potential for societal changes driven by the adoption of autonomous vehicles.

Reviewing and Refining Your Essay

After completing your essay, review and edit it for clarity and coherence. Ensure that your arguments are well-structured and supported by evidence. Check for grammatical accuracy and ensure that your essay flows logically from one point to the next. Consider seeking feedback from peers or instructors to further improve your essay. A well-crafted essay on self-driving cars will not only demonstrate your understanding of the topic but also your ability to engage with complex technological and societal issues.

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Exploring the Ethics Behind Self-Driving Cars

How do you code ethics into autonomous automobiles? And who is responsible when things go awry?

August 13, 2015

Illustration by Abigail Goh

Imagine a runaway trolley barreling down on five people standing on the tracks up ahead. You can pull a lever to divert the trolley onto a different set of tracks where only one person is standing. Is the moral choice to do nothing and let the five people die? Or should you hit the switch and therefore actively participate in a different person’s death?

In the real world, the “trolley problem” first posed by philosopher Philippa Foot in 1967 is an abstraction most won’t ever have to actually face. And yet, as driverless cars roll into our lives, policymakers and auto manufacturers are edging into similar ethical dilemmas.

Quote One of the questions that comes up in class discussions is whether, as a driver, you should be able to program a degree of selfishness, making the car save the driver and passengers rather than people outside the car. Attribution Ken Shotts

For instance, how do you program a code of ethics into an automobile that performs split-second calculations that could harm one human over another? Who is legally responsible for the inevitable driverless-car accidents — car owners, carmakers, or programmers? Under what circumstances is a self-driving car allowed to break the law? What regulatory framework needs to be applied to what could be the first broad-scale social interaction between humans and intelligent machines?

Ken Shotts and Neil Malhotra , professors of political economy at Stanford GSB, along with Sheila Melvin , mull the philosophical and psychological issues at play in a new case study titled “ ‘The Nut Behind the Wheel’ to ‘Moral Machines’: A Brief History of Auto Safety .” Shotts discusses some of the issues here:

What are the ethical issues we need to be thinking about in light of driverless cars?

This is a great example of the “trolley problem.” You have a situation where the car might have to make a decision to sacrifice the driver to save some other people, or sacrifice one pedestrian to save some other pedestrians. And there are more subtle versions of it. Say there are two motorcyclists, one is wearing a helmet and the other isn’t. If I want to minimize deaths, I should hit the one wearing the helmet, but that just doesn’t feel right.

These are all hypothetical situations that you have to code into what the car is going to do. You have to cover all these situations, and so you are making the ethical choice up front.

It’s an interesting philosophical question to think about. It may turn out that we’ll be fairly consequentialist about these things. If we can save five lives by taking one, we generally think that’s something that should be done in the abstract. But it is something that is hard for automakers to talk about because they have to use very precise language for liability reasons when they talk about lives saved or deaths.

What are the implications of having to make those ethical choices in advance?

Right now, we make those instinctive decisions as humans based on our psychology. And we make those decisions erroneously some of the time. We make mistakes, we mishandle the wheel. But we make gut decisions that might be less selfish than what we would do if we were programming our own car. One of the questions that comes up in class discussions is whether, as a driver, you should be able to program a degree of selfishness, making the car save the driver and passengers rather than people outside the car. Frankly, my answer would be very different if I were programming it for driving alone versus having my 7-year-old daughter in the car. If I have her in the car, I would be very, very selfish in my programming.

Who needs to be taking the lead on parsing these ethical questions — policymakers, the automotive industry, philosophers?

The reality is that a lot of it will be what the industry chooses to do. But then policymakers are going to have to step in at some point. And at some point, there are going to be liability questions.

There are also questions about breaking the law. The folks at the Center for Automotive Research at Stanford have pointed out that there are times when normal drivers do all sorts of illegal things that make us safer. You’re merging onto the highway and you go the speed of traffic, which is faster than the speed limit. Someone goes into your lane and you briefly swerve into an oncoming lane. In an autonomous vehicle, is the “driver” legally culpable for those things? Is the automaker legally culpable for it? How do you handle all of that? That’s going to need to be worked out. And I don’t know how it is going to be worked out, frankly. Just that it needs to be.

Are there any lessons to be learned from the history of auto safety that could help guide us?

Sometimes eliminating people’s choices is beneficial. When seatbelts were not mandatory in cars, they were not supplied in cars, and when they were not mandatory to be used, they were not used. Looking at cost-benefit analysis, seatbelts are incredibly cost effective at saving lives, as is stability control. There are real benefits to having things like that mandated so that people don’t have the choice not to buy them.

The liability system can also induce companies to include automated safety features. But that actually raises an interesting issue, which is that in the liability system, sins of commission are punished more severely than sins of omission. If you put in airbags and the airbag hurts someone, that’s a huge liability issue. Failing to put in the airbag and someone dies? Not as big of an issue. Similarly, suppose that with a self-driving car, a company installs safety features that are automated. They save a lot of lives, but some of the time they result in some deaths. That safety feature is going to get hit in the liability system, I would think.

What sort of regulatory thickets are driverless cars headed into?

When people talk about self-driving cars, a lot of the attention falls on the Google car driving itself completely. But this really is just a progression of automation, bit by bit by bit. Stability control and anti-lock brakes are self-driving–type features, and we’re just getting more and more of them. Google gets a lot of attention in Silicon Valley, but the traditional automakers are putting this into practice.

So you could imagine different platforms and standards around all this. For example, should this be a series of incremental moves or should it be a big jump all the way to a Google-style self-driving car? Setting up different regulatory regimes would favor one of those approaches over the other. I’m not sure whether it’s the right policy, but incremental moves could be a good policy. But it also would be really good from the perspective of the auto manufacturers, and less good from the perspective of Google. And it could be potentially to a company’s advantage if they could try to influence the direction that the standards go in a way that favors their technology. This is something that companies moving into this area have to think about strategically, in addition to thinking about the ethical stuff.

What other big ethical questions do you see coming down the road?

At some point, do individuals get banned from having the right to drive? It sounds really far-fetched now. Being able to hit the road and drive freely is a very American thing to do. It feels weird to take away something that feels central to a lot of people’s identity.

But there are precedents for it. The one that Neil Malhotra, one of my coauthors on this case, pointed out is building houses. This used to be something we all did for ourselves with no government oversight 150 years ago. That’s a very immediate thing — it’s your dwelling, your castle. But if you try to build a house in most of the United States nowadays, there are all sorts of rules for how you have to do the wiring, how wide this has to be, how thick that has to be. Every little detail is very, very tightly regulated. Basically, you can’t do it yourself unless you follow all those rules. We’ve taken that out of individuals’ hands because we viewed there were beneficial consequences of taking it out of individuals’ hands. That may well happen for cars.

Graphics sources: newyorkologist.org; oldcarbrocheres.com; National Museum of American History; Academy of Achievement; iStock/hxdbzxy; Reuters/Stephen Lam.

For media inquiries, visit the Newsroom .

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‘The Nut Behind the Wheel’ to ‘Moral Machines:’ A Brief History of Auto Safety Neil Malhotra, Ken Shotts, Sheila Melvin

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Self-Driving Vehicles—an Ethical Overview

Research Article
Open access
Published: 12 August 2021
Volume 34 , pages 1383–1408, ( 2021 )

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Sven Ove Hansson ORCID: orcid.org/0000-0003-0071-3919 1 ,
Matts-Åke Belin 1 , 2 &
Björn Lundgren ORCID: orcid.org/0000-0001-5830-3432 3 , 4 , 5

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The introduction of self-driving vehicles gives rise to a large number of ethical issues that go beyond the common, extremely narrow, focus on improbable dilemma-like scenarios. This article provides a broad overview of realistic ethical issues related to self-driving vehicles. Some of the major topics covered are as follows: Strong opinions for and against driverless cars may give rise to severe social and political conflicts. A low tolerance for accidents caused by driverless vehicles may delay the introduction of driverless systems that would substantially reduce the risks. Trade-offs will arise between safety and other requirement on the road traffic system. Over-reliance on the swift collision-avoiding reactions of self-driving vehicles can induce people to take dangerous actions, such as stepping out in front of a car, relying on its fast braking. Children travelling alone can violate safety instructions such as the use of seatbelts. Digital information about routes and destinations can be used to convey commercial and political messages to car users. If fast passage can be bought, then socio-economic segregation of road traffic may result. Terrorists and other criminals can hack into a vehicle and make it crash. They can also use self-driving vehicles for instance to carry bombs to their designed places of detonation or to wreak havoc on a country’s road system.

The Future of Transportation: Ethical, Legal, Social and Economic Impacts of Self-driving Vehicles in the Year 2025

The Ethics of Privacy in Research and Design: Principles, Practices, and Potential

Exploring the implications of autonomous vehicles: a comprehensive review

Kareem Othman

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1 Introduction

Self-driving vehicles have been predicted to radically change our patterns of travelling and transportation (Gruel & Stanford, 2016 ; Pernestål & Kristoffersson, 2019 ). Their introduction will be a protracted process involving massive investments in vehicles and infrastructure, as well as changes in ingrained behaviours and attitudes. There will probably be a decades-long period of gradual introduction, in which fully automated operation of road vehicles will only be allowed in limited segments of the road system, such as specially designated highways or highway lanes, and small areas such as parking facilities where velocities will be kept low (Kyriakidis et al., 2019 ).

This will be a momentous technological transformation. It calls for major efforts to anticipate and evaluate social changes that may potentially accompany the introduction of the new technology. As part of these endeavours, ethical and public policy aspects of the technology itself and of various scenarios for its introduction need to be explored (Palm & Hansson, 2006 ). This article presents an overview of plausible challenges and opportunities that can potentially result from the introduction of self-driving (driverless, autonomous) road vehicles. Our purpose is to broaden the discussion from a focus on the crash behaviour of vehicles to the many types of social change that the new technology can be involved in. We have studied the ethical literature on the topic, and reflected on the social and ethical implications of topics brought up in the technical and policy-oriented literature. This search resulted in a fairly extensive (but of necessity not exhaustive) list of issues, many of which do not seem to have been discussed previously in the ethical literature. Footnote 1 In what follows we begin by discussing the changes in responsibility ascriptions that can be expected (“Sect. 2 ”), since such changes will determine much of the ethical framework for the new technology. After that we discuss potential positive and negative reactions to automated vehicles (“Sect. 3 ”) and the trade-offs between safety and other requirements on a new road traffic system (“Sect. 4 ”). We then turn to the important ethical issues that arise from the possibility of external control of autonomous vehicles (“Sect. 5 ”) and from the large amounts of person-related data that will be collected in vehicles and road management systems (“Sect. 6 ”). This is followed by chapters on human health and the environment (“Sect. 7 ”), social and labour market relations (“Sect. 8 ”), and criminality (“Sect. 9 ”). Our conclusions are summarized in “Sect. 10 ”.

2 Responsibility for Safety

Much of the discussion on self-driving vehicles has been concerned with issues of responsibility. In the currently on-going tests on public roads, there is always a person on the driver’s seat, called a “safety driver” or “steward”, who is required to follow the traffic and be prepared to take over control immediately if the need arises. The safety driver has essentially the same legal responsibilities as the driver of a conventional vehicle. However, this is seen as a temporary solution, and the automobile industry aims at releasing the safety driver, so that all occupants of the vehicle can be passengers. Such a step would seem implausible unless and until automatic driving has achieved a markedly higher level of safety than human driving. Possibly, this will first be attained only in certain parts of the road system (e.g. motorways), and fully automatic driving may then initially be allowed only there.

If and when this happens, a radically new situation will arise with respect to responsibility. If there is no driver who controls the vehicle, who is then responsible for the safety of its passengers and of those who travel or walk on the same roads? If a car is “driven” by a computer possessing artificial intelligence, does that intelligence constitute an entity that can be held responsible? What are the responsibilities of the vehicle’s current owner? Its manufacturer? The owner and manager of the road system? The organization running the traffic control centre that the vehicle communicates with?

Even without automatic vehicles, traditional assumptions about responsibilities in road traffic have been subject to change in the last few decades. Traditionally, drivers and others moving on the roads have been taken to carry almost the whole burden of responsibility (Melcher et al., 2015 , p. 2868). Footnote 2 Vision Zero, which was introduced in Sweden 1997 and is now adopted in numerous countries, states, and cities around the world, aims at eliminating all fatalities and serious injuries in road traffic. It puts much more emphasis than previous approaches on the responsibilities of road builders and managers, vehicle manufacturers, and others who contribute to creating and maintaining the traffic system, or use it professionally (Belin et al., 2012 ; Rosencrantz et al., 2007 ). Future changes in responsibility ascriptions will have to be seen in that perspective.

In order to analyse the responsibility issues connected with automated road traffic, we need to distinguish between two fundamentally different types of responsibility, namely, task responsibility and blame responsibility (Dworkin, 1981 ; Goodin, 1987 ; Hansson, 2022 ). Having a task responsibility means to be obliged to do something. Having a blame responsibility means that one is to be blamed if something goes wrong. Blame responsibility is often associated with punishments or with duties to compensate. Blame responsibility is also often called “backwards-looking responsibility”, and task responsibility can be called “forwards-looking responsibility”.

These two major forms of responsibility coincide in many practical situations, but in particular in complex social situations, they can be born by different agents. For instance, suppose that a motorist who drives too fast kills a child crossing a road on its way to school. In the subsequent trial, the driver will be held (blame) responsible for the act. And of course the driver is (task) responsible for not driving dangerously again. But that is not enough. We also need to prevent the same type of accident from happening again, with other drivers. This is not something that the culpable driver can do. Instead, measures are needed in the traffic system. We may have reasons to introduce traffic lights, speed bumps, or perhaps a pedestrian underpass. The task responsibility for these measures falls to decision-makers, such as public authorities. In cases like this, blame and task responsibility part company.

What will happen with our responsibility ascriptions when driverless cars are introduced? One thing should be clear: since the users of fully automated vehicles have no control over the vehicle, other than their choice of a destination, it would be difficult to hold them responsible either for safety (task responsibility) or for accidents (blame responsibility) (Gurney, 2017 ). We do not usually hold people responsible for what they cannot control (King, 2014 ). Footnote 3 There are three major alternatives for what we can do instead. First, we can hold other persons responsible instead. The most obvious candidates are the vehicle manufacturers and the people responsible for the road system (including the communication and coordination systems used to guide the vehicles). The second option is to hold the artificial intelligence built into the vehicles responsible. The third is to treat traffic accidents in the same way as natural accidents such as tsunamis and strokes of lightning, for which no one is held responsible. In Matthias’ ( 2004 ) terminology, this would mean that there is a “responsibility gap” for these accidents. Several authors have warned that self-driving vehicles may come with a responsibility gap (Coeckelbergh, 2016 ; de Jong, 2020 ).

Although the future is always difficult to predict, the first option is by far the most probable one. Previous experience shows that this is how we usually react when a person to whom we assigned responsibility is replaced by an automatic system. For instance, if an aviation accident unfolds after the pilot turned on the autopilot, we do not blame the artificial intelligence that took over the flight, and neither do we treat the failure as a natural event. Instead, we will probably put blame on those who directed the construction, testing, installation, service, and updating of the artificial intelligence. Such an approach is not unknown in road traffic. In the past few decades, proponents of the Vision Zero approach to traffic safety have had some success in achieving an analogous transfer of responsibility to vehicle and road system providers, although human drivers are still in place.

It cannot be excluded that future, perhaps more human-like, artificial agents will be assigned blame or task responsibility in the same way as human agents (Nyholm, 2018a , pp. 1209–1210). However, in the foreseeable future, the systems running our vehicles do not seem to be plausible candidates for being so treated. These will be systems taking and executing orders given to them by humans. There does not seem to be any need for them to express emotions, make self-reflective observations, or exhibit other behaviours that could make us see them as our peers. Footnote 4 It should also be noted that current approaches to automatic driving are predominantly based on pre-programmed response patterns, with little or no scope for autonomous learning. This is typical for safety-critical software. The cases in which it appears to be difficult to assign responsibility for an artificial agent to its creator(s) are those that involve extensive machine learning, which means that the programmers who constructed the software have no chance of predicting its behaviour.

We should therefore assume that for driverless vehicles, the responsibilities now assigned to drivers will for the most part be transferred to the constructors and maintainers of the vehicles and the roads and communication systems on which they depend (Bonnefon et al., 2020 , pp. 53–63; Crane et al., 2017 ; Luetge, 2017 , p. 503; Marchant & Lindor, 2012 ). Footnote 5 This also seems to be what the automobile industry expects to happen (Atiyeh, 2015 ; Nyholm, 2018c ). It will have the interesting consequence that blame responsibility and task responsibility will be more closely aligned with each other since they are carried by the same organization (Nyholm & Smids, 2016 , p. 1284n). The responsibility of manufacturers can either be based on products liability or on some new legal principle, such as Gurney’s ( 2017 ) proposal that in liability cases, the manufacturers of autonomous vehicles should be treated as drivers of those vehicles. Abraham and Rabin ( 2019 ) suggested a new legal concept, “manufacturer enterprise responsibility” that would involve a strict liability compensation system for injuries attributable to autonomous vehicles. Some authors, notably Danaher ( 2016 ) and de Jong ( 2020 ), have put focus on the “retribution gap”, i.e. the lack of mechanisms to identify individual persons that are punishable for a crash caused by an autonomous vehicle. This part of the responsibility gap cannot be so easily filled by a corporate entity as the parts concerning compensation (another part of blame responsibility) of future improvements (task responsibility). However, finding someone to punish is not necessarily as important as compensating victims and reducing the risks of future crashes.

It is much less clear how responsibilities will be assigned in near-automated driving, in which a human in the driver’s seat is constantly prepared to take over control of the vehicle in the case of an emergency (Nyholm, 2018a , p. 1214). However, although this may be adequate for test driving, it is unclear whether the same system can be introduced on a mass scale. Human interventions will tend to be slow, probably often slower than if the human is driving, and such interventions may also worsen rather than improve the outcome of a dangerous situation (Hevelke & Nida-Rümelin, 2015 ; Sparrow & Howard, 2017 , pp. 207–208). It is highly doubtful whether such arrangements satisfy the requirement of “meaningful human control” that is frequently referred to in the AI literature (Mecacci & Santoni de Sio 2020 ). Since meaningful control is a standard criterion for both blame and task responsibility, it is therefore also doubtful whether either type of responsibility can be assigned to a person sitting in the driver’s seat under such conditions (Hevelke & Nida-Rümelin, 2015 ).

3 What Can and Should Be Accepted?

Although the automotive industry and public traffic administrations are planning for automatized road traffic, its introduction will, at least in democracies, ultimately depend on how public attitudes will develop. Some studies indicate that large parts of the population in most countries have a fairly positive attitude to autonomous vehicles (Kyriakidis et al., 2015 ). However, such studies should be interpreted with caution. Not many have any experience of self-driving vehicles, and no one has experience of their large-scale introduction into a traffic system. Furthermore, other studies indicate a less positive attitude (Edmonds, 2019 ).

Public attitudes to accidents involving autonomous vehicles will be important, perhaps decisive, for the introduction of such vehicles in regular traffic. Will we accept the same frequency of serious accidents with self-driving cars as that which is now tolerated for vehicles driven by humans? There are several reasons to believe that we will not. Already today, tolerance for safety-critical vehicle malfunctions is low. Manufacturers recall car models to repair faults with a comparatively low probability of causing an accident. They would probably encounter severe public relations problems if they did not. Previous attempts to limit such recalls to cases when they have a favourable cost–benefit profile have proved disastrous to the manufacturer’s public relations (Smith, 2017 ). The public tends to expect much lower failure rates in vehicle technology than in the behaviour of drivers (Liu et al., 2019 ). This difference is by no means irrational, since technological systems can be constructed to be much more predictable, and in that sense more reliable, than humans. Footnote 6

Another reason to put high demands on the safety features of driverless vehicles is that improvements in technology are much more generalizable than improvements in human behaviour. Suppose that a motorist drives over a child at dusk because of problems with his eyesight. This may be reason enough for him to change his way of driving, or to buy new eyeglasses. If his eyesight cannot be sufficiently improved, it is a reason for authorities to withdraw his driver’s licence. However, all these measures will only affect this particular driver. In contrast, if a similar accident occurs due to some problem with the information processing in an automatized vehicle, then improvements to avoid similar accidents in the future will apply (at least) to all new vehicles of the same type. The fact that a crash with a self-driving vehicles cannot be written off as an exception due to reckless behaviour may also contribute to higher demands on the safety of these vehicles.

In addition to these rational reasons for high safety requirements on driverless vehicles, public attitudes may be influenced by factors such as fear of novelties or a particular revulsion to being killed by a machine. There have already been cases of enraged opponents slashing tyres, throwing rocks, standing in front of a car to stop it, and pointing guns at travellers sitting in a self-driving car, largely due to safety concerns (Cuthbertson, 2018 ). At least one company has left its self-driving test vehicles unmarked in order to avoid sabotage (Connor, 2016 ).

All this can combine to heighten the safety requirements on self-driving vehicles. This was confirmed in a study indicating that self-driving vehicles would have to reduce current traffic fatalities by 75–80% in order to be tolerated by the public in China (Liu et al., 2019 ). Potentially, requirements of safety improvement may turn out to be so high that they delay the introduction of driverless systems even if these systems would in fact substantially reduce the risks. Such delays can be ethically quite problematic (Brooks, 2017a ; Hicks, 2018 , p. 67).

To the extent that future driverless vehicles satisfy such augmented safety requirements, the public’s tolerance of accidents with humanly driven vehicles may be affected. If a much lower accident rate is shown to be possible in automatized road traffic, then demands for safer driving can be expected to gain momentum. This can lead to measures that reduce the risks of conventional driving, such as alcohol interlocks, speed limiters, and advanced driver assistance technologies. Insurance will become more expensive for human-driven than self-driving cars if the former are involved in more accidents. There may also be proposals to exclude human-driven vehicles from parts of the road net, or even to prohibit them altogether. According to Sparrow and Howard ( 2017 , p. 206), when self-driving cars pose a smaller risk to other road-users than what conventional cars do, “then it should be illegal to drive them: at that point human drivers will be the moral equivalent of drunk robots” (Cf. Müller & Gogoll, 2020 ; Nyholm & Smids, 2020 ).

On the other hand, strong negative reactions to driverless cars can be expected to develop in segments of the population. In road traffic as we know it, drivers communicate with each other and with unprotected persons in various informal ways. Drivers show other drivers that they are leaving them space to change lanes, and pedestrians tend to wait for drivers to signal that they have seen them before stepping into the street. Similarly, drivers react to pedestrians showing that they wait for the vehicle to pass (Brooks, 2017a ; b ; Färber, 2015 , p. 143; Färber, 2016 , p. 140). Inability of automatic vehicles to take part, as senders or receivers, in such communications, may give rise to reactions against their presence in the streets. There may also be disapprovals of patterns of movement that differ from the driving styles of most human drivers, such as strictly following speed limits and other traffic laws, and accelerating and decelerating slowly in order to save energy (Nyholm & Smids, 2020 ; Prakken, 2017 ).

Furthermore, negative reactions can have their grounds in worries about the social and psychological effects of dependence on artificial intelligence, or about the uncertainties pertaining to risks of sabotage or large accidents due to a breakdown of the system. There are signs that significant reactions of this nature may arise. According to a study conducted by the American Automobile Association, three out of four Americans are afraid of riding a fully autonomous car (Edmonds, 2019 ). Such attitudes may be connected with other misgivings about a future, more technocentric society. Such reactions should not be underestimated. The experience of genetically modified crops in Europe shows that resistance to new technologies can delay their introduction several decades, despite extensive experience of safe use (Hansson, 2016 ).

Attitudes to automatized road traffic can also be influenced by devotion to the activity of driving. For some people, driving a motor vehicle is an important source of pride and self-fulfilment. The “right to drive a car” is important in their lives (Borenstein et al., 2019 , p. 392; Edensor, 2004 ; Moor, 2016 ). Notably, this does not necessarily involve negativity to mixed traffic, as long as one is allowed to drive oneself, and the “pleasure of driving” is not too much thwarted by the self-driving vehicles and the arrangements made for them. The “Human Driving Manifesto” that was published in 2018 argued explicitly for mixed traffic, claiming that “[t]he same technology that enables self-driving cars will allow humans to retain control within the safe confines of automation” (Roy, 2018 ). However, from an ethical (but perhaps not a political) point of view, the pleasures of driving would tend to be lightweight considerations in comparison with the avoidance of fatalities on the road.

All this adds up to prospects for severe social and political conflicts on the automatization of road traffic. Judging by previous introductions of contested technology, there is a clear risk that this can develop into a trench war between parties with impassioned and uncompromising positions. If driverless cars achieve a much better safety record than conventional vehicles—otherwise their introduction seems unlikely—then proponents will be invigorated by the safety statistics and will see little reason to make concessions that would be costly in terms of human lives. On the other hand, opponents motivated by abhorrence of a more technology dependent society cannot be expected to look for compromises. Dealing with the terms of such an entrenched clash of social ideals may well be the dominant issue of ethical involvement in road traffic automatization. Needless to say, rash and badly prepared introductions of self-driving vehicles could potentially trigger an escalation of such conflicts.

4 Safety and the Trade-Offs of Constructing a Traffic System

In the construction of a new traffic system, safety will be a major concern, and possibly the most discussed aspect in public deliberations. However, there will also be other specifications of what the traffic system should achieve. Just as in the existing traffic system, this will in practice often lead to trade-offs between safety and other objectives. Since safety is an ethical requirement, all such trade-offs have a considerable ethical component. In a new traffic system, they will have to be made with a considerably higher priority for safety than in the current system with its dreadful death toll.

Many of the more specific features of self-driving vehicles, such as short reaction time and abilities to communicate with other vehicles, can be used both to enhance safety and to increase speed. For instance, driving on city roads and other roads with unprotected travellers, such as pedestrians and cyclists, will always be subject to a speed–safety trade-off (Flipse & Puylaert, 2018 , p. 55). With sufficiently low speeds, fatal car–pedestrian collisions can virtually be eradicated. Probably, passengers of driverless vehicles would not tolerate such low speeds. They can also cause annoyance and possibly risky behaviour by the drivers of conventional vehicles. On the other hand, if the tolerance for fatal accidents becomes much lower for self-driving than for humanly driven vehicles (as discussed above), then demands for such low speeds can be expected. As noted by Goodall ( 2016 , pp. 815–816), since fast transportation in city areas is beneficial to many types of businesses, the speed–safety trade-off will be accompanied by an economy–safety trade-off connected with the efficiency of logistics.

Increased separation between pedestrians and motor vehicles can efficiently reduce accident risks. The introduction of inner city zones, similar to pedestrian zones but allowing for automatized vehicles driving at very low speeds and giving way to pedestrians, could possibly solve the safety problem and the need for transportation of goods. However, such zones may not be easily accepted by people who wish to reach city destinations with conventionally driven vehicles. This can lead to an accessibility–safety trade-off.

Self-driving vehicles can drive close to each other in a caravan, where the first vehicle sends out instructions to brake or accelerate, so that these operations are performed simultaneously by the whole row of vehicles. This technology (“platooning”) can significantly reduce congestion and thereby travel time. However, an efficient use of this mechanism will inevitably tend to reduce safety margins (Hasan et al., 2019 ; Hu et al., 2021 ). This will give rise to a speed–safety trade-off, but also to an economy–safety trade-off concerning infrastructure investments.

Even if accidents due to incoordination in fast-moving vehicle caravans will be very unusual, the effects can be enormous. This may place road traffic in a situation more similar to that of civil aviation, whose safety considerations are dominated by rare but potentially very large accidents (Lin, 2015 , p. 80; Lin, 2016 , p. 80). There may then be incentives to limit the number of vehicles in a caravan, and thereby the size of a maximal accident, although such a limitation may not decrease the expected total number of fatalities in these rare accidents. Discussions on such measures will involve a small–vs.–large–accidents trade-off.

Already in today’s traffic system there are large differences in safety between different cars. Important safety features are present in some car models but not in others. Some of these safety features, such as crumple zones, safety cells, and airbags, reduce the severity of the injuries affecting drivers and passengers (crashworthiness). Others, such as driver monitoring systems and anti-lock braking systems, reduce the probability of accidents (crash avoidance). Many of the crash avoidance features that are now installed on human-driven cars can be seen as forerunners of components that will be integrated into fully autonomous driving systems. The efficiency of the total crash avoidance system of self-driving cars will be crucial for the extent to which these vehicles can be introduced into road traffic. Like all other features, those affecting crash avoidance can be expected to differ between car models. New models will expectedly have better crash avoidance systems. Expensive car models may be equipped with better systems than less expensive ones; for instance, they may have better and more costly sensors (Holstein et al., 2018 ).

Currently, our tolerance is in practice fairly high for large differences in the risks that different vehicles expose other road users to, due to variations in equipment as well as in driver skills and behaviour. In many countries, a minimal technical safety level is ensured by compulsory periodic motor vehicle inspections, which include checks of brakes and other basic requirements. However, there are still large differences between vehicle types and models for instance in driver monitoring systems and anti-lock braking systems. In general, new cars have a higher standard than old cars in these respects. Recalls to update old cars to the technical safety standards of new cars are, to our knowledge, not practised anywhere. Footnote 7 Software updates in old vehicles may become a difficult issue, in particular for vehicles that outlive their manufacturing company (Smith, 2014 ). Today, most accidents are ascribed to human failures (Rolison et al., 2018 ). When the majority of crashes are ascribed to vehicle failures, prohibition of inferior vehicle types will be a much more obvious way to improve safety. Doing so will be good for safety, but achieving the higher safety level will be costly. To the extent that the higher costs for safety will prevent people with low incomes from owning motor vehicles, it can also involve an equity–safety trade-off.

The protection of passengers against accident risks will have to be implemented in a new situation in driverless cars. There may no longer be a person present in the vehicle who is responsible for the safety of all passengers. Presumably, this also means that there will no longer be a need for one sober person in the car. We can foresee trade-offs between, on the one hand, passengers’ free choice of activities and behaviour in the vehicle, and on the other hand, the measures required for their safety, in short freedom–safety trade-offs. A car or a bus can be occupied by a company of befuddled daredevils trying to bypass whatever features the vehicle has been equipped with to prevent dangerous behaviour such as leaning out of windows or throwing out objects. The introduction of mechanisms to detect and prevent dangerous behaviour, such as non-belted travel, can be conceived as privacy intrusive, and we then have a privacy–safety trade-off. It should be noted, however, that such mechanisms have an important function for minors travelling alone. Children may easily indulge in unsafe behaviour, such as travelling without a seat belt, and standard anti-paternalist arguments are not applicable to under-age persons. Vehicle-to-vehicle and vehicle-to-infrastructure communication can give rise to another privacy–safety trade-off; see “Sect. 6 ”.

Just like human drivers, self-driving vehicles can become involved in traffic situations where an accident cannot be avoided, and a fast reaction is needed in order to reduce its consequences as far as possible. A considerable number of ethics papers have been devoted to cases in which this reaction has to deal with an ethical dilemma, for instance between driving either into two elderly persons or one child. Footnote 8 Such dilemmas are virtually unheard of in the history of human driving. The reason for this is that the dilemmatic situations are extremely rare in practice. In order for such a situation to arise, two unexpected human obstacles will have to be perceived simultaneously and with about the same degree of certainty, so that the (human or artificial) agent’s first reaction will take both into account. Furthermore, there have to be two reasonably controlled options to choose between. As excellently explained by Davnall ( 2020 ), such situations are extremely rare. In almost all situations when a crash is imminent, the most important reaction is to decrease the car’s speed as much as possible in order to reduce its momentum. The choice is therefore between braking maximally without swerving and braking maximally and at the same time swerving. The latter option has severe disadvantages: swerving reduces the efficiency of braking, so that the collision will take place with a larger momentum. Swerving leads to loss of control, so that (in sharp contrast to the unrealistic examples in this literature) the car’s trajectory becomes unpredictable. This can lead to skidding, spinning, and a sideways collision that is not alleviated by the crumple zones at the car’s front. The chances for pedestrians and others to move out of harm’s way are also smaller if the car is spinning and skidding. In summary, the self-driving car “does not face a decision between hitting an object in front of it and hitting an object off to one side. Instead, the decision is better described as being between a controlled manoeuvre—one which can be proven with generality to result in the lowest impact speed of any available option—and a wildly uncontrolled one.” (Davnall, 2020 , pp. 442–443). Due to the physics of braking and crashing, the situation is very much the same for self-driving systems as it is for human drivers. Consequently, the need for including deliberations on this type of dilemmas does not seem to be larger in the programming of automatized vehicles than in driver’s education Footnote 9 (Brooks, 2017a ). Discussions of such dilemmatic situations seem to have been driven by theoretical considerations, rather than by attempts to identify the ethical problems arising in automated road traffic. Footnote 10 The ethical problems of crash avoidance, in particular the speed–safety trade-offs and the other trade-offs described above, will in all probability be much more important and should therefore be at the centre of the ethical discussion.

5 External Control of Driverless Vehicles

We typically think of an automated car as a vehicle following the directions of the human being who instructs it, both concerning the destination and the route. However, it will not be difficult to construct systems in which the decisions by individual drivers can be overridden by the traffic guidance system. In the case of a traffic jam on a particular road section, driverless vehicles can be redirected to uncongested roads. Such automatic redirection will be much more efficient than sending messages to the passengers who will then have to choose whether or not to follow the recommended new route. However, enforced redirection of a vehicle due to congestion may be conceived as an infringement on the freedom of its occupants. It is both possible and desirable to retain a personal choice for the road users in that case.

The ability of emergency service vehicles to reach their destination as quickly as possible is often a matter of life or death. In a fully automatized road traffic system, both the velocity of the blue light vehicles and the safety of other travellers can be substantially increased if all other vehicles on the pertinent roads are kept out of way through external control by the traffic guidance system. In addition, such external control of vehicles can be used for various law enforcement purposes, such as stopping a car at the roadside in order to arrest a traveller or to search for drugs, contraband or stolen goods. It has been predicted that such remote seizure can decrease the risk of deadly violence when a car is stopped by the police (Joh, 2019 , p. 309).

Arguably, this does not differ from what the police already have the authority to do. They can redirect traffic for purposes such as avoiding congestion, and they can stop a vehicle to arrest a driver or passenger or search for objects to be confiscated. If there is continuous electronic communication between the targeted vehicle(s) and a traffic guidance system, then it will be possible to inform the travellers of the reasons for the external interference and the expected consequences for their continued journey. This is a distinct advantage as compared to traditional police action on roads. Furthermore, taking control of a suspect’s vehicle and bringing it to the roadside is a much safer method than traditional high-speed pursuits. Car chases have a yearly death toll of about 100 per year in the USA alone. Between a fourth and half of those killed are innocent bystanders or road users (Hutson et al., 2007 ; Lyneham & Hewitt-Rau, 2013 ; Rice et al., 2015 ). From an ethical point of view, a reduction in these numbers is of course most desirable.

However, as the risks involved in stopping a vehicle become smaller, there may be moves to use the method for many more purposes than what traditional car chases are used for (namely, to capture persons trying to escape law enforcement). For instance, vehicles can be stopped in order to seize foreign nationals without a valid visa, persons suspected of having committed a minor misdemeanour, or a person whose travel destination indicates an intention to violate a restraining order (Holstein et al., 2018 ). The purposes for which law enforcement agencies can take over control of a vehicle, and the procedures for decisions to do so, will therefore have to be determined, based on a balance between the interests of law enforcement and other legitimate interests.

6 Information Handling

The potential advantages of self-driving vehicles can only be realized with well-developed communication systems. Vehicle-to-vehicle (inter-vehicle) communication can be used to avoid crashes and organize platooning. Vehicle-to-road-management communication systems can provide updated local information on traffic and accessibility. Both types of communication can complement the information gathered by the vehicle itself. Information about obstacles ahead can be obtained before they are registered by the car’s own sensors. Furthermore, sensor or sensor interpretation errors can be detected by comparison with information from other cars or from the roadside. If vehicle-to-road-management systems are interconnected on a large scale, then they can also be used for optimizing the traffic flow (van Wyk et al., 2020 ).

However, like all large-scale handling of person-related information, the collection and processing of traffic information can give rise to considerable privacy intrusions (Zimmer, 2005 ). Today, it is still largely possible to travel anonymously. A person who drives a private car does not necessarily leave any electronic traces, and the same applies to someone travelling by collective transportation (unless she pays with a payment card or a personal travel card) or by taxi (unless she pays with a payment card or the taxi has video surveillance).

All this will be different in an automatized traffic system. Self-driving vehicles will depend on geopositioning transponders operating in a highly standardized fashion (Borenstein et al., 2019 , p. 384), and possibly on centralized communication systems that keep track of each vehicle’s planned route and destination (Luetge, 2017 , p. 554). For privately owned cars, this information will be linkable to the owner. It can potentially be accessed by the road manager and by authorities. The situation will be similar for cars that are rented on a short-term or long-term basis. Just as today, companies renting out vehicles for personal use will register the identity of their customers. Furthermore, there will presumably be an incentive to install video surveillance systems in driverless vehicles—in particular buses—in order to deal with potential disturbances.

Geopositioning of persons can be highly sensitive. It can reveal memberships in religious or political organizations, as well as sensitive private relationships. For a member of a cult, a criminal or extreme political organization, disclosure of visits to an organization offering exit counselling can be life-threatening. The disclosure of travel destinations can be equally dangerous for a person who has obtained a new identity, for instance in a witness protection programme or a programme protecting women from harassment by ex-husbands. More generally, freedom to travel without being surveilled—by government, companies, or private persons—is arguably one of the values universally cherished in liberal societies (Sobel, 2014 ).

Geopositioning data can also potentially be used for commercial purposes. Currently, web browsing data on a person’s movements in the virtual space of the internet is used to tailor a massive flow of advertisements (Véliz, 2019 ; Vold & Whittlestone, 2019 ). With geopositioning data, our movements in real space can be used in the same way (Gillespie, 2016 ). Sellers and rental providers of vehicles will have economic incentives to include an advertisement function over which they retain control, so that they can sell space on it. For instance, after a car has been parked outside a timber yard, the owner or renter of the car would receive commercial messages from other construction stores. A (devotional or touristic) visit to a church or a mosque could be followed by messages from proselytizing organizations etc. Political ads could be individualized, based for instance on the combination of past travel and web surfing habits. These commercial messages could be conveyed via loudspeakers or screens in the car, or through other media connected with the person who owns or rents the vehicle. It is not inconceivable that such personalized commercials may become as ineluctable for travellers as the (personalized) commercials are today for the web surfer and the (impersonal) ads for the newspaper reader (King, 2011 ; Svarcas, 2012 ). Car manufacturers are already developing recommender systems that deliver commercial information based on the recipient’s previous behaviour. Such systems can be installed in both human-driven and self-driving cars (Vrščaj et al., 2020 ). In addition, ride-sharing can be tailored, based on personal information for instance from web browsing, which is used to find a suitable travel companion (Moor, 2016 ; Soteropoulos et al., 2019 , p. 46). However, we still have a (political) choice whether we want our real-world movements to be registered and used for such purposes.

A person going by a driverless car may have a destination that is less precise than a specific address, such as “a grocery” or “a place on the way to the final destination where I can buy some flowers”. Such destinations leave open for considerable commercial opportunities of the same types that are currently used on web browsers and social media. The car-traveller can then find herself driven, not to the closest grocery or flower shop, but to a store further away that has paid for being directed to. Travellers can also be offered to stop at places, for instance restaurants, for which they have not expressed any desire. There will be strong incentives for the sellers and renters of vehicles to display such services. But in this case as well, we still have an option to decide (politically) what types of messages our future travels should impose on us.

If the coordination between automatized vehicles is efficient, then the vast majority of accidents will probably result from collisions with cars driven by humans and with unprotected travellers such as pedestrians, cyclists, motorcyclists, and horseback riders. An obvious solution to this would be for non-autonomous vehicles, pedestrians etc. to carry a transponder that communicates with motor vehicles in order to avoid collisions (Morhart & Biebl, 2011 ). Parents may wish to provide their children with transponders in order to ensure their safety. It is not inconceivable that demands may arise to make transponders mandatory for certain types of vehicles (such as motorcycles), or for persons walking, cycling or horse-riding on particularly dangerous roads. Obviously, personal transponders would give rise to much the same privacy issues as vehicle-bound geopositioning.

7 Effects on Health and the Environment

To the extent that public transportation such as fixed route buses is replaced by self-driving vehicles that are called to the user’s location, there will no longer be a need to walk to and from a bus stop or a train or subway station. Such walks are an important part of the physical exercise performed by large parts of the population. Reducing the amount of exercise from an already suboptimal level can have negative health effects (Sallis et al., 2012 ). This may call for counter-measures, such as making residential areas car-free (Nieuwenhuijsen & Khreis, 2016 ).

The distribution between road traffic and other modes of traffic, in particular aviation and rail-bound traffic, may change due to the introduction of self-driving vehicles, but it is not possible to foresee what direction such changes will take. If road traffic replaces air-trips, then this will have positive environmental and climate effects. If it replaces rail traffic, then the effect may go in the opposite direction.

It seems plausible that self-driving vehicles will have better energy efficiency than vehicles driven by humans (Urmson & Whittaker, 2008 ). It has also been proposed that electric vehicles will be more attractive if they are self-driven so that they can “recharge themselves” when they are not needed (Brown et al., 2014 ). However, it is also plausible that the total mileage will increase (ibid.). The effects of automatized road traffic on the climate and the environment will also depend on several other factors, such as the distribution between privately owned and rentable vehicles (Zhang et al., 2018 ), and the extent of car- and ride-sharing (Fagnant & Kockelman, 2018 ). The introduction of a traffic management system that coordinates travel will make it easier than in the current system to arrange ride-sharing. However, if most of the vehicles continue to be privately owned (or long-time rented), then incentives to ride-sharing may be insufficient, and car travelling may continue to be as inefficient as today in terms of the number of passengers per vehicle. If traffic is mostly organized with cars hired for each occasion, similar to the current taxi system, then large-scale ride-sharing can more easily be organized and made economically attractive. Needless to say, the choice between these alternatives is a policy decision that need not be left to the market. The climate crisis provides strong reasons to support ride-sharing for instance with incentives in the transport fare system (Greenwald & Kornhauser, 2019 ). However, it is doubtful whether improved energy efficiency and increased car- and ride-sharing can outweigh the increased mileage that is expected to follow with the introduction of self-driving vehicles. At any rate, increased use of climate-friendlier modes of transportation, such as trains and bicycles, is necessary to achieve climate objectives.

A routing system for automatized traffic can be constructed to ensure that each vehicle reaches its destination as soon as possible. Alternatively, it can be tailored to achieve energy efficiency. This will mean lower velocities and fewer accelerations and decelerations, and therefore also increased travel time. Policy-makers will have to decide whether to leave this choice to the individual vehicle user (just as the same decision is left to individual drivers in the present system), or to regulate it in some way. Such a regulation can for instance impose a minimal priority to be assigned to energy conservation in all motor vehicles, or it can involve some form of taxation incurring additional costs on energy-inefficient transportation. Probably, platooning will be so energy-efficient that there will be strong reasons for policy-makers to consider the introduction of a unified speed on major highways (Brown et al., 2014 ).

Both road lighting and exterior automotive lighting can be substantially reduced in an automatized road traffic system (Sparrow & Howard, 2017 , p. 212). This will reduce energy consumption, and it will also lead to a reduction in light pollution (Stone et al., 2020 ). No large effects on the noise pollution emitted from each vehicle can be expected, since the noise level depends primarily on the energy source and the type of motor, rather than on whether the vehicle is automatized or conventionally driven. An increase in road traffic, which is a plausible consequence of automation, will lead to increased noise pollution.

8 Social and Labour Market Consequences

The introduction of self-driving vehicles will have important social consequences. Perhaps most obviously, people who cannot travel alone on roads today will be able to do so. Parents may wish to allow children to go alone by a driverless car. This can make it possible for children to visit relatives or friends, or take part in various activities, even when there is no grown-up available who has the time to accompany them (Harb et al., 2018 ). However, traffic situations can arise in which it is not safe for children to travel alone in a self-driving vehicle. Therefore, a regulation setting a minimal age for the oldest person travelling in a driverless vehicle may be required (Gasser, 2015 , pp. 571–572; Gasser, 2016 , pp. 548–549).

The effects for people with disabilities would seem to be more unequivocally positive. Costly adaptations of vehicles can to a large part be dispensed with. A considerable number of people who cannot drive a car will be able to go on their own in a self-driving car (Mladenovic & McPherson, 2016 , p. 1137). This will increase their mobility, and it can potentially have positive effects on their well-being and social connectedness.

On the negative side, an automatized road traffic system makes it possible to introduce new social divisions among travellers. We already have divisions between more and less affordable manners of travelling on-board the same vehicle. However, although those who travel first or business class on trains and airplanes have more legroom, and (on airplanes) receive more drinks and presumably better food, they leave and arrive at the same time. If there is a traffic delay, first class passengers are not sent off in a separate vehicle, leaving the second (or “tourist”) class passengers behind. A road management system will of course ensure the swift passage of emergency vehicles when other vehicles have to travel slowly, but will it also offer swift passage to those who can afford a “first” or “business” option for their travel? There will certainly be economic incentives to provide such services for those who can pay for them (Dietrich & Weisswange, 2019 ; Mladenovic & McPherson, 2016 ). The negative effects on social cohesion and solidarity of such a system should not be underestimated. Fortunately, the choice whether to allow such shortcuts for the prosperous is a political decision yet to be made.

Sensors currently in use tend to be less reliable in detecting dark-skinned than light-skinned pedestrians (Cuthbertson, 2019 ). This will expose dark-skinned pedestrians to higher risks than others. The probable cause of this defect is that too few dark-skinned faces have been included in the training sets used when the sensor software was developed. This is a problem that will urgently have to be eliminated.

New and more comfortable travel opportunities can give rise to changes in the relative attractiveness of different residential districts, possibly with areas further from city centres gaining in attractiveness (Heinrichs, 2015 , pp. 230–231; Heinrichs, 2016 , pp. 223–224; Soteropoulos et al., 2019 , p. 42). There may also be effects on the localization choices of firms, including shops and entertainment facilities. Changes in the use of urban space may have effects on social segregation, which are difficult to foresee but should be at the focus in urban planning.

As in other branches of industry, automatization of the traffic system will lead to a decreased need of personnel. Driving professions such as those of a bus driver, lorry driver or taxi driver will gradually diminish. For instance, it has been estimated that 5 million Americans work at least part time as drivers (Eisenstein, 2017 ). That is about 3% of the workforce. Even a partial and gradual replacement of these jobs by automatized vehicles will require solutions such as training schemes and other forms of labour market policies (Hicks, 2018 , p. 67; Ryan, 2020 ). If such measures are not taken, or are not efficient enough, the result will be unemployment, with its accompanying social problems. Footnote 11 It should be noted that other branches of industry are expected to undergo a similar process at the same time. The labour market effects of automatized road traffic can therefore be seen as part of the much larger question whether and how the labour market can be readjusted at sufficient pace to deal with the effects of artificial intelligence and its attendant automatization (Pavlidou et al., 2011 ).

However, self-driving vehicles may also have a positive effect on the supply side of the labour market. To the extent that travel becomes faster and/or more convenient, workers will be willing to take jobs at larger distance from home, thus facilitating matching on the labour market. Affordable travel opportunities to workplaces can make it possible for underprivileged people to escape poverty (Epting, 2019 , p. 393).

It is highly uncertain what effects the introduction of self-driving cars will have on employment in the automotive industry. A decrease in the number of cars produced would have a negative impact on employment. However, as noted in “Sect. 2 ”, the industry is expected to have a much higher post-production involvement in self-driving than in human-driven cars. This should have positive effects on employment in the automobile industry. However, parts of this effect may be due to a transfer of employments from other branches of industry. Furthermore, the automotive industry is at the same time subject to other developments that affect the size of its labour force, in particular the automatization of its production processes and economic developments in third-world countries that increase the number of potential users and owners of motor vehicles. The total effect of all these developments is uncertain.

9 Criminality

Almost invariably, major social changes give rise to new forms of criminality that threaten human welfare. We have no reason to believe that vehicle automatization will be an exception from this. Four important potential variants of criminality are illegal transportation, unauthorized access to data, sabotage, and new forms of auto theft.

Automated vehicles can be used for illegal transportation tasks, for instance smuggling and the delivery of drugs, stolen goods, and contraband. For law enforcement, this can give rise to new challenges. Police inspection of vehicles with no traveller will be less intrusive than inspection of vehicles containing humans, but privacy concerns will nevertheless have to be taken into account.

The most obvious way to steal data from a vehicle is to hack into its computer system, either by surreptitious physical connection or using its links to other vehicles and to the traffic guidance system (Jafarnejad et al., 2015 ). If the system contains sensitive information, such as geopositioned travel logs, then this information can be used for instance for blackmailing or for arranging an “accident” at a place to which the owner returns regularly. Information about individual travel patterns obtained from hacking of the traffic guidance system can be used in the same ways.

All self-driving vehicles depend on sensor and software technology, both of which are sensitive to manipulation. Physical sensor manipulation can be performed in order to make the vehicle dysfunctional or (worse) to hurt or kill its passengers (Petit & Shladover, 2015 ). The effects of such manipulation (as well as other forms of sensor malfunction) can to a large extent be eliminated with sensor redundancy. By comparing the inputs from several sensors with overlapping functionalities, sensor malfunctioning can be detected.

Software manipulation can be performed for various criminal purposes, for instance to make the vehicle inoperable, to make it crash, or to direct the vehicle to a destination undesired by the passengers, for instance with the intent of frightening or kidnapping travellers (Crane et al., 2017 , pp. 239–251; Jafarnejad et al., 2015 ; Joh, 2019 , p. 313). Such manipulations can be connected with terrorism or organized crime. The prospect of being helplessly driven at high speed to an unknown place would seem to be scary enough to intimidate a witness. The risk of such software manipulation should be taken seriously. In addition to the usual measures to prevent, detect, contain and respond to an attack, vehicles can be provided with an overriding option for passengers to order it to stop at the nearest place where it can be safely parked (Kiss, 2019 ).

Vehicles without passengers can be used for criminal and terrorist attacks, such as driving at high speed into a crowd, or carrying a bomb to a place where it will be detonated (instead of having it carried by a suicide bomber) (Joh, 2019 , pp. 306–307; Ryan, 2020 ). Some such crimes will require software manipulation, which criminals can be expected to perform on vehicles in their own possession. Therefore, systems that detect and report attempts to alter the software will have to be an essential component of the security system (Straub et al., 2017 ).

Software manipulation performed by insiders in the automotive industry is much more difficult to prevent. In the recent diesel emission scandals, prominent motor vehicle industries were capable of illegal manipulation of software, sanctioned on top level in the business hierarchies (Bovens, 2016 ). Since car manufacturers have much to lose from a bad safety record, they do not have an incentive to manipulate software in a way that leads to serious accidents. However, they may have an incentive to manipulate vehicle-to-road-management information in ways that avoid unfavourable reporting to statistical systems based on these communications. Manufacturers working under an authoritarian regime may be ordered to provide exported vehicles with software backdoors that can be used in a potential future conflict to create havoc in another country’s traffic system.

Terrorists or enemy states can hack the traffic guidance system (rather than individual vehicles) in order to sabotage a country’s road traffic. They can for instance stop or redirect transportation of goods, or they can direct targeted vehicles to deadly collisions. This is a serious security problem that requires at least two types of responses. First, traffic guidance systems have to be made as inaccessible as possible to attacks. Secondly, vehicle-to-vehicle communication systems should include warning signals sent out from crashing vehicles, giving rise to crash-avoiding reactions in vehicles in the vicinity.

Automatized cars need to be protected against unauthorized access. Privately owned cars can be equipped with face recognition or other bioidentification systems that only allow certain persons to start a ride (similar systems can exclude unauthorized persons from driving a conventional car, Park et al., 2017 ). Companies renting out self-driving cars will have strong incentives to install identification mechanisms that ensure proper payment and make it possible to trace customers who have done damage to the vehicle. Auto theft may therefore become much more difficult to get away with. This may lead to an increased prevalence of kidnappings with the sole purpose of using the kidnapped person to direct a self-driving car to a desired destination.

In mixed traffic, some roads or lanes may be reserved for driverless vehicles. The traffic on such roads may potentially run at higher speed than the highest speed allowed on roads that are open to conventionally driven cars. Illegal human driving on such roads can give rise to considerable risks, and will therefore have to be strictly forbidden. One potential new form of criminality is driving on such roads, as a form of street racing. There may also be other ways for human drivers to exploit the fast reactions of self-driving vehicles. Safety margins can be transgressed for the thrill of it or in order to pass queues and reach a destination faster (Lin, 2015 , p. 81; Lin, 2016 , p. 81; Sparrow & Howard, 2017 , p. 211). Pedestrians may develop over-reliance on the reactions of self-driving vehicles, and step out in front of a vehicle with an insufficient safety margin, relying on its fast braking (Färber, 2015 , p. 143; Färber, 2016 , p. 138; Loh & Misselhorn, 2019 ). Such over-trust in autonomous systems may offset the safety gains that are obtainable with automated road traffic. Measures against it may run into ethical problems concerning paternalism and intrusiveness.

10 Conclusion

In this final section, we will summarize some of the major ethical issues that require further deliberations.

10.1 Responsibility

The introduction of automated road traffic will give rise to large changes in responsibility ascriptions concerning accidents and traffic safety. Probably, the responsibilities now assigned to drivers will for the most part be transferred to the constructors and maintainers of vehicles, roads, and communication systems.

10.2 Public Attitudes

We can expect a much lower tolerance for crashes caused by driverless vehicles than for crashes attributable to errors by human drivers. Such high safety requirements may postpone the introduction of driverless systems even if these systems in fact substantially reduce the risks.

Public opinion will also be influenced by other issues than safety. Apprehensions about a future society dominated by increasingly autonomous technology can lead to resistance against self-driving vehicles. Such resistance can also be fuelled by aberrant “behaviour” of self-driving cars, and by wishes to retain human driving as a source of pride and self-fulfilment. On the other hand, if human driving coexists with much safer automated traffic, it may be put under pressure to become safer. There may also be proposals to limit human driving or to prohibit it altogether. All this can add up to severe social and political conflicts on automatized road traffic. Rash and badly prepared introductions of self-driving vehicles can potentially lead to an escalation of such conflicts.

10.3 Safety

The short reaction times of self-driving vehicles can be used to enhance safety or to increase speed. A trade-off between safety and speed will have to be struck. This applies to platooning on highways, and also to vehicle movements in the vicinity of pedestrians.

A fully automatic vehicle can carry passengers that could not travel alone in a conventional car, for instance a group of inebriated daredevils, or children unaccompanied by adults. It may then be difficult to ensure safety, for instance that seatbelts are used and that no one leans out of a window.

Over-reliance on the swift collision-avoiding reactions of self-driving cars can induce people to take dangerous actions. Pedestrians may step out in front of a vehicle, relying on its fast braking. Motorists may choose to drive (illegally) on roads or lanes reserved for automatic vehicles.

10.4 Control

The police will probably be able stop a self-driving vehicle by taking control of it electronically. This is much safer than traditional high-speed pursuits. However, the purposes and procedures for decisions to halt a vehicle will have to be based on a balance between the interests of law enforcement and other legitimate interests.

More ominously, criminals can take control over a vehicle in order to make it crash or become inoperable. Terrorists or enemy states can use self-driving vehicles to redirect the transportation of important goods, drive into crowds, carry bombs to their designed places of detonation, or create a general havoc in a country’s road system.

10.5 Information

Extensive information about routes and destinations will have to be collected in order to optimize the movements of self-driving vehicles. Such information can be misused or hacked. It can for instance be used to convey commercial and political messages to car users. An authoritarian state can use it to keep track of the opposition.

The safety of pedestrians, cyclists, and people travelling in conventional motor vehicles can be improved if they carry transponders that keep self-driving vehicles in their vicinity informed of their positions and movements. Such transponders will give rise to the same issues concerning privacy as the transponders in self-driving vehicles.

10.6 Social Justice

Vehicle types and models will differ in their crash avoidance systems, expectedly with newer and more expensive models having the best systems. It will be technically possible to allow cars with better safety features to operate on different places or at higher speeds than other cars. Socio-economic segregation of road traffic can potentially have considerable negative effects on social cohesion.

The need for professional drivers will gradually decrease, and many will lose their employments. This will require solutions such as training schemes and other forms of labour market policies.

In general, the ethical implications of introducing autonomous vehicles are not inherent in the technology itself, but will depend to a large extent on social choices, not least the decisions of law-makers. Choices have to be made for instance on the required level of safety, the distribution of responsibilities between infrastructure providers and vehicle manufacturers and providers, the organization of traffic control, trade-offs between privacy and other interests, and the adjustment of the traffic sector as a whole to climate and environmental policies. It is essential that these decisions be made in the public interest and based on thorough investigations of the issues at hand. There is also an urgent need for further ethical and social research that penetrates the full range of potential issues that the introduction of autonomous vehicles can give rise to, including key ethical issues such as equity, privacy, acceptability of risk, responsibility, and the social mechanisms for dealing with trade-offs and value conflicts.

Availability of Data and Material

This research is based on publicly available texts that are listed in the bibliography.

Code Availability

Not applicable.

For a previous review focusing on crashes with self-driving cars, see Nyholm ( 2018b , c ). For a comprehensive scenario-based treatment, see Ryan ( 2020 ).

Husak ( 2004 ) highlighted the unacceptably high level of risk-taking in the current road traffic system, but laid the responsibility on individual road-users, arguing for instance that trips taken for “frivolous purposes” (p. 352), such as recreational travels by car, are morally objectionable. In contrast, Vision Zero emphasizes the responsibility of those who can transform the traffic system and make it safer.

Hevelke and Nida-Rümelin ( 2015 ) proposed a form of collective (blame) responsibility, shared by all users of fully automated vehicles. However, such shared responsibility can only be implemented through an insurance-based compensation system. It cannot include the possibility of criminal charges. This does not seem to be a plausible way to deal with offences that may potentially include the causation of deaths and serious injuries.

Tigard ( 2020 ) proposed that in cases when a technological system has failed, we can “demand answers from the system itself” and even “hold AI to account by imposing sanctions, correcting undesirable behavioral patterns acquired, and generally seeing that the target of our response works to improve for the future.” Although this may be possible as a purely intellectual venture, it is difficult to see how the emotional components of responsibility ascriptions could be established in relation to software.

Possibly, large companies that rent out cars will take on more extensive responsibilities than private car owners, whether or not these companies are owned by the car industry.

However, it does not follow that machines necessarily perform better in a complex environment where unpredictable disturbances may require reactions that cannot be pre-programmed. Arguably, road traffic is such a complex environment, in particular mixed traffic with both driverless and conventional vehicles.

In Sweden between 1975 and 2007, recycling of older vehicles was rewarded with a bonus. This was primarily for environmental reasons, but the bonus also contributed to the disposal of vehicles lacking modern safety equipment.

See Nyholm ( 2018b , c ) and Davnall ( 2020 , pp. 431–434) for references and systematic reviews of this literature.

The most plausible scenario in which an ethical dilemma could arise seems to be sudden loss of braking power. This is a rare event in human driving and it is not expected to become more common in self-driving vehicles (Davnall 2020 ). The dilemmas that it can give rise to do not seem to be a common topic in drivers’ education.

For further clarifications of the lack of realism of these deliberations, see Gasser ( 2015 , p. 556), Goodall ( 2016 ), Hansson ( 2012 , p. 44), Hern ( 2016 ), Himmelreich ( 2018 ), and Nyholm and Smids ( 2016 ). For a well-articulated contrary view, see Keeling ( 2020 ). Keeling does not take into account the problems with swerving discussed above, and seems to grossly overestimate the frequency of cases with a controlled choice between different ways to crash.

This will not be the case in areas with a large shortage of drivers. Self-driving vehicles have been referred to as a potential solution to driver shortage (Mittal et al., 2018 ).

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Hansson, S.O., Belin, MÅ. & Lundgren, B. Self-Driving Vehicles—an Ethical Overview. Philos. Technol. 34 , 1383–1408 (2021). https://doi.org/10.1007/s13347-021-00464-5

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Seven Arguments Against the Autonomous-Vehicle Utopia

All the ways the self-driving future won’t come to pass

People stand indoors near a silver self-driving car.

Self-driving cars are coming. Tech giants such as Uber and Alphabet have bet on it, as have old-school car manufacturers such as Ford and General Motors. But even as Google’s sister company Waymo prepares to launch its self-driving-car service and automakers prototype vehicles with various levels of artificial intelligence , there are some who believe that the autonomous future has been oversold—that even if driverless cars are coming, it won’t be as fast, or as smooth, as we’ve been led to think. The skeptics come from different disciplines inside and out of the technology and automotive industries, and each has a different bear case against self-driving cars. Add them up and you have a guide to all the ways our autonomous future might not materialize.

Bear Case 1: They Won’t Work Until Cars Are as Smart as Humans

Computers have nowhere near human intelligence. On individual tasks, such as playing Go or identifying some objects in a picture, they can outperform humans, but that skill does not generalize. Proponents of autonomous cars tend to see driving as more like Go: a task that can be accomplished with a far-lower-than-human understanding of the world. But in a duo of essays in 2017, Rodney Brooks, a legendary roboticist and artificial-intelligence researcher who directed the MIT Computer Science and Artificial Intelligence Laboratory for a decade, argued against the short-term viability of self-driving cars based on the sheer number of “edge cases,” i.e., unusual circumstances, they’d have to handle.

Read: The AI that has nothing to learn from humans

“Even with an appropriate set of guiding principles, there are going to be a lot of perceptual challenges … that are way beyond those that current developers have solved with deep learning networks, and perhaps a lot more automated reasoning than any AI systems have so far been expected to demonstrate,” he wrote . “I suspect that to get this right we will end up wanting our cars to be as intelligent as a human, in order to handle all the edge cases appropriately. ”

He still believes that self-driving cars will one day come to supplant human drivers. “Human driving will probably disappear in the lifetimes of many people reading this,” he wrote. “But it is not going to all happen in the blink of an eye.”

Bear Case 2: They Won’t Work, Because They’ll Get Hacked

Every other computer thing occasionally gets hacked, so it’s a near-certainty that self-driving cars will be hacked, too. The question is whether that intrusion—or the fear of it— will be sufficient to delay or even halt the introduction of autonomous vehicles.

Read: The banality of the Equifax breach

The transportation reporter and self-driving car skeptic Christian Wolmar once asked a self-driving-car security specialist named Tim Mackey to lay out the problem. Mackey “believes there will be a seminal event that will stop all the players in the industry in their tracks,” Wolmar wrote . ‘‘We have had it in other areas of computing, such as the big-data hacks and security lapses and it will happen in relation to autonomous cars.” Cars, even ones that don’t drive themselves, have already proved vulnerable to hackers .

The obvious counterargument is that data lapses, hacking, identity theft, and a whole lot of other things have done basically nothing to slow down the consumer internet. A lot of people see these problems and shrug . However, the physical danger that cars pose is far greater, and maybe the norms developed for robots will be different from those prevalent on the internet, legally and otherwise , as the University of Washington legal scholar Ryan Calo has argued.

Bear Case 3: They Won’t Work as a Transportation Service

Right now most companies working on self-driving cars are working on them as the prelude to a self-driving-car service. So you wouldn’t own your car; you’d just get rides from a fleet of robo-cars maintained by Waymo or Uber or Lyft. One reason for that is the current transportation-service companies can’t seem to find their way to profitability. In fact, they keep losing insane amounts of money . Take the driver out of the equation and maybe all of that money saved would put them in the black. At the same time, the equipment that’s mounted on self-driving cars to allow them to adequately convert physical reality into data is extremely expensive. Consumer vehicles with all those lasers and computers on board would be prohibitively expensive. On top of that, the question of calibrating and maintaining all that equipment would be entrusted to people like me, who don’t wash their car for months at a time.

Read: Will Uber and Lyft become different things?

Put these factors together and the first step in fully autonomous vehicles that most companies are betting on is to sell robo-car service, not robo-cars.

There is a simple rejoinder to why this might not work. George Hotz, who is himself attempting to build a DIY driving device, has a funny line that sums it up. “They already have this product, it’s called Uber, it works pretty good,” Hotz told The Verge . And what is a robo-car ride if not “a worse Uber”?

Bear Case 4: They Won’t Work, Because You Can’t Prove They’re Safe

Commercial airplanes rely heavily on autopilot, but the autopilot software is considered provably safe because it does not rely on machine-learning algorithms. Such algorithms are harder to test because they rely on statistical techniques that are not deterministic. Several engineers have questioned how self-driving systems based on machine learning could be rigorously screened. “Most people, when they talk about safety, it’s ‘Try not to hit something,’” Phil Koopman, who studies self-driving-car safety at Carnegie Mellon University, told Wired this year. “In the software-safety world, that’s just basic functionality. Real safety is, ‘Does it really work?’ Safety is about the one kid the software might have missed, not about the 99 it didn’t.”

Regulators will ultimately decide if the evidence that self-driving-car companies such as Waymo have compiled of safe operation on roads and in simulations meets some threshold of safety. More deaths caused by autonomous vehicles, such as an Uber’s killing of Elaine Herzberg , seem likely to drive that threshold higher.

Koopman, for one, thinks that new global standards like the ones we have for aviation are needed before self-driving cars can really get on the road, which one imagines would slow down the adoption of the cars worldwide.

Bear Case 5: They’ll Work, But Not Anytime Soon

Last year, Ford announced plans to invest $1 billion in Argo AI, a self-driving-car company. So it was somewhat surprising when Argo’s CEO, Bryan Salesky, posted a pessimistic note about autonomous vehicles on Medium shortly after. “We’re still very much in the early days of making self-driving cars a reality,” he wrote . “Those who think fully self-driving vehicles will be ubiquitous on city streets months from now or even in a few years are not well connected to the state of the art or committed to the safe deployment of the technology.”

In truth, that’s the timeline the less aggressive carmakers have put forth. Most companies expect some version of self-driving cars in the 2020s, but when within the decade is where the disagreement lies.

Bear Case 6: Self-Driving Cars Will Mostly Mean Computer-Assisted Drivers

While Waymo and a few other companies are committed to fully driverless cars or nothing, most major carmakers plan to offer increasing levels of autonomy , bit by bit. That’s GM’s play with the Cadillac Super Cruise. Daimler, Nissan, and Toyota are targeting the early 2020s for incremental autonomy.

Read: The most important self-driving car announcement yet

Waymo’s leadership and Aurora’s Chris Urmson worry that disastrous scenarios lie down this path. A car that advertises itself as self-driving “should never require the person in the driver’s seat to drive. That hand back [from machine to human] is the hard part,” Urmson told me last year . “If you want to drive and enjoy driving, God bless you, go have fun, do it. But if you don’t want to drive, it’s not okay for the car to say, ‘I really need you in this moment to do that.’”

Bear Case 7: Self-Driving Cars Will Work, But Make Traffic and Emissions Worse

And finally, what if self-driving works, technically, but the system it creates only “solve[s] the problem of ‘I live in a wealthy suburb but have a horrible car commute and don’t want to drive anymore but also hate trains and buses,’” as the climate advocate Matt Lewis put it . That’s what University of California at Davis researchers warn could happen if people don’t use (electric-powered) self-driving services and instead own (gasoline-powered) self-driving cars. “Sprawl would continue to grow as people seek more affordable housing in the suburbs or the countryside, since they’ll be able to work or sleep in the car on their commute,” the scenario unfolds . Public transportation could spiral downward as ride-hailing services take share from the common infrastructure.

And that’s not an unlikely scenario based on current technological and market trends. “Left to the market and individual choice, the likely outcome is more vehicles, more driving and a slow transition to electric cars,” wrote Dan Sperling, the director of the UC Davis Institute of Transportation Studies, in his 2018 book, Three Revolutions: Steering Automated, Shared, and Electric Vehicles to a Better Future .

It would certainly be a cruel twist if self-driving cars managed to save lives on the road while contributing to climate catastrophe. But if the past few years of internet history have taught us anything, any technology as powerful and society-shaping as autonomous vehicles will certainly have unintended consequences. And skeptics might just have a handle on what those could be.

Announcements

Self-Driving Car Ethics

Earlier this spring 49-year-old Elaine Herzberg was walking her bike across the street in Tempe, Ariz., when she was hit and killed by a car traveling at over 40 miles an hour.

There was something unusual about this tragedy: The car that hit Herzberg was driving on its own. It was an autonomous car being tested by Uber.

It’s not the only car crash connected to autonomous vehicles (AVs) as of late. In May, a Tesla on “autopilot” mode accelerated briefly before hitting the back of a fire truck, injuring two people.

The accidents unearthed debates that have long been simmering around the ethics of self-driving cars. Is this technology really safer than human drivers? How do we keep people safe while this technology is being developed and tested? In the event of a crash, who is responsible: the developers who create faulty software, the human in the driver’s seat who fails to recognize the system failure, or one of the hundreds of other hands that touched the technology along the way?

The need for driving innovation is clear: Motor vehicle deaths topped 40,000 in 2017 according to the National Safety Council. A recent study by RAND Corporation estimates that putting AVs on the road once the technology is just 10 percent better than human drivers could save thousands of lives. Industry leaders continue to push ahead with development of AVs: Over $80 billion has been invested so far in AV technology, the Brookings Institute estimated . Top automotive, rideshare and technology companies including Uber, Lyft, Tesla, and GM have self-driving car projects in the works. GM has plans to release a vehicle that does not need a human driver--and won’t even have pedals or a steering wheel--by 2019.

But as the above crashes indicate, there are questions to be answered before the potential of this technology is fully realized.

Ethics in the programming process

Accidents involving self-driving cars are usually due to sensor error or software error, explains Srikanth Saripalli, associate professor in mechanical engineering at Texas A&M University, in The Conversation . The first issue is a technical one: Light Detection and Ranging (LIDAR) sensors won’t detect obstacles in fog, cameras need the right light, and radars aren’t always accurate. Sensor technology continues to develop, but there is still significant work needed for self-driving cars to drive safely in icy, snowy and other adverse conditions. When sensors aren’t accurate, it can cause errors in the system that likely wouldn’t trip up human drivers. In the case of Uber’s accident, the sensors identified Herzberg (who was walking her bike) as a pedestrian, a vehicle and finally a bike “with varying expectations of future travel path,” according to a National Transportation Safety Board (NTSB) preliminary report on the incident. The confusion caused a deadly delay--it was only 1.3 seconds before impact that the software indicated that emergency brakes were needed.

Self-driving cars are programmed to be rule-followers, explained Saripalli, but the realities of the road are usually a bit more blurred. In a 2017 accident in Tempe, Ariz., for example, a human-driven car attempted to turn left through three lanes of traffic and collided with a self-driving Uber. While there isn’t anything inherently unsafe about proceeding through a green light, a human driver might have expected there to be left-turning vehicles and slowed down before the intersection, Saripalli pointed out. “Before autonomous vehicles can really hit the road, they need to be programmed with instructions about how to behave when other vehicles do something out of the ordinary,” he writes.

However, in both the Uber accident that killed Herzberg and the Tesla collision mentioned above, there was a person behind the wheel of the car who wasn’t monitoring the road until it was too late. Even though both companies require that drivers keep their hands on the wheel and eyes on the road in case of a system error, this is a reminder that humans are prone to mistakes, accidents and distractions--even when testing self-driving cars. Can we trust humans to be reliable backup drivers when something goes wrong?

Further, can we trust that companies will be thoughtful--and ethical--about the expectations for backup drivers in the race for miles? Backup drivers who worked for Uber told CityLab that they worked eight to ten hour shifts with a 30 minute lunch and were often pressured to forgo breaks. Staying alert and focused for that amount of time is already challenging. With the false security of self-driving technology, it can be tempting to take a quick mental break while on the road. “Uber is essentially asking this operator to do what a robot would do. A robot can run loops and not get fatigued. But humans don’t do that,” an operator told CityLab.

The limits of the trolley scenario

Despite the questions that these accidents raise about the development process, the ethics conversation up to this point has largely been focused on the moment of impact. Consider the “ trolley problem ,” a hypothetical ethical brain teaser frequently brought up in the debate over self-driving cars. If an AV is faced with an inevitable fatal crash, whose life should it save? Should it prioritize the lives of the pedestrian? The passenger? Saving the most lives? Saving the lives of the young or elderly?

Ethical questions abound in every engineering and design decision, engineering researchers Tobias Holstein, Gordana Dodig-Crnkovic and Patrizio Pelliccione argue in their recent paper, Ethical and Social Aspects of Self-Driving Cars , ranging from software security (can the car be hacked?) to privacy (what happens to the data collected by the car sensors?) to quality assurance (how often does a car like this need maintenance checks?). Furthermore, the researchers note that some ethics are directly at odds with the private industry’s financial incentives: Should a car manufacturer be allowed to sell cheaper cars outfitted with cheaper sensors? Could a customer choose to pay more for a feature that lets them influence the decision-making of the vehicle in fatal situations? How transparent should the technology be, and how will that be balanced with intellectual property that is vital to a competitive advantage?

The future impact of this technology hinges on these complex and bureaucratic “mundane ethics,” points out Johannes Himmelreich, interdisciplinary ethics fellow at Stanford University in The Conversation . We need to recognize that big moral quandaries don’t just happen five seconds before the point of impact, he writes. Programmers could choose to optimize acceleration and braking to reduce emissions or improve traffic flow. But even these decisions pose big questions for the future of society: Will we prioritize safety or mobility? Efficiency or environmental concerns?

Ethics and responsibility

Lawmakers have already begun making these decisions. State governments and municipalities have scrambled to play host to the first self-driving car tests, in hopes of attracting lucrative tech companies, jobs and an innovation-friendly reputation. Arizona governor Doug Ducey has been one of the most vocal proponents, welcoming Uber when the company was kicked out of San Francisco for testing without a permit.

Currently there is a patchwork of laws and executive orders at the state level that regulate self-driving cars. Varying laws make testing and the eventual widespread roll-out more complicated and, as it is, it is likely that self-driving cars will need a completely unique set of safety regulations. Outside of the US, there has been more concrete discussion. Last summer Germany adopted the world’s first ethical guidelines for driverless cars. The rules state that human lives must take priority over damage to property and in the case of unavoidable human accident, a decision cannot be made based on “age, gender, physical or mental constitution,” among other stipulations.

There has also been discussion as to whether consumers should have the ultimate choice over AV ethics. Last fall, researchers at the European University Institute suggested the implementation of an “ ethical knob ,” as they call it, in which the consumer would set the software’s ethical decision-making to altruistic (preference for third parties), impartial (equal importance to all parties) or egoistic (preference for all passengers in the vehicle) in the case of an unavoidable accident. While their approach certainly still poses problems (a road in which every vehicle prioritizes the safety of its own passengers could create more risk), it does reflect public opinion. In a series of surveys , researchers found that people believe in utilitarian ethics when in comes to self-driving cars--AVs should minimize casualties in the case of an unavoidable accident--but wouldn’t be keen on riding in a car that would potentially value the lives of multiple others over their own.

This dilemma sums up the ethical challenges ahead as self driving technology is tested, developed and increasingly driving next to us on the roads. The public wants safety for the most people possible, but not if it means sacrificing one’s own safety or the safety of loved ones. If people will put their lives in the hands of sensors and software, thoughtful ethical decisions will need to be made to ensure a death like Herzberg’s isn’t inevitable on the journey to safer roads.

Karis Hustad is a Denmark-based freelance journalist covering technology, business, gender, politics and Northern Europe. She previously reported for The Christian Science Monitor and Chicago Inno. Follow her on Twitter @karishustad and see more of her work at karishustad.com .

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The ethical dilemma of self-driving cars

transportation
machine learning
driverless cars

What Are Self-Driving Cars?

When we think about self-driving cars, we often imagine vehicles that take us from A to B without human intervention, but what makes a vehicle truly autonomous? Our expert explains.

Self-driving cars are vehicles that use sensors and artificial intelligence to transport people on roads autonomously without human input. Self-driving cars are also known as autonomous vehicles or driverless cars.

Do Self-Driving Cars Actually Exist?

SAE International (the Society of Automotive Engineers) established six levels of vehicular autonomy , ranging from level zero — our daily-use utility vehicles — to level five , where vehicles no longer require human input to operate effectively. Currently, we are far from a level five automation since there are many situations with which autonomous vehicles cannot yet cope.

Related Reading Artificial Intelligence in Cars: Examples of AI in the Auto Industry

How Do Self-Driving Cars Work?

The main goal of self-driving cars is to drive from point A to point B safely. To do this they operate a pre-established map. We call this map a high-definition map or HD Map. Self-driving vehicles use a combination of radar, video cameras, LiDAR and GPS to locate themselves and surrounding vehicles within their HD Map.

Radar and LiDAR

Radar is a sensor that uses radio waves to detect close objects, whereas LiDAR uses light waves to detect objects that are further away with great precision. That said, since LiDAR uses light waves, it can be susceptible to fog, whereas radar is not. In addition, self-driving cars use video cameras to detect and track traffic lights, road signs and pedestrians.

GPS provides a course and precise geographic location of the vehicle (longitude, latitude and elevation), which can be fine-tuned when combined with the input from all other sensors. GPS sensors don’t tend to work well in tunnels, nevertheless a self-driving car can compensate for this with input from other sensors.

Ultrasonic Sensors

Self-driving cars also use ultrasonic sensors for close-range object detection. Ultrasonic sensors are cost effective and aren’t negatively affected by environmental factors. On the other hand, they have low resolution and a very close range. We normally use ultrasonic sensors for emergency brake assistance and to check blind spots.

While we can place more sensors in the car wheels, doors, front and back, this is ultimately dependent upon the manufacturer.

Self-driving cars use all the input from their sensors to locate themselves within an HD map and generate a route toward a destination. A route generated in an HD map contains much more data than a regular GPS route. For example, an autonomous vehicle will know when it needs to change lanes, where traffic lights are supposed to be and even road conditions.

Since HD maps can contain so much information, they may need a lot of maintenance. Some companies such as TomTom (International), Blickfeld (Germany), Civil Maps (U.S.A.) and many others, have found commercial value in maintaining proprietary HD maps.

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Are Self-Driving Cars Safe?

Experts believe self-driving cars can achieve higher levels of safety than human driven vehicles. In fact, when we analyze and compare accident data of self-driving cars versus traditional cars and adjust it to “Crash rate per million miles driven,” self-driving cars always end up with a lower accident rate .

The figure below uses the SHRP 2 NDS data set and crash levels from one to three, where level one is the worst type of crash, which involves airbag deployment and injury. For level two crashes there is no airbag deployment or injury, however there should be at least $1,500 in damage. Level three crashes involve physical conflict with another object or vehicle, but with physical damage that does not meet level one or two.

However, public opinion falls on the other side in this matter. Users expect self-driving vehicles to be as close to perfection as possible. When self-driving cars from companies like Waymo and Tesla become involved in accidents , we get a reminder that, despite wanting autonomous vehicles to never become involved in an accident, that’s almost statistically impossible, especially when they share the road with human drivers.

Components of a Self-Driving Car

We can identify three core components that make a vehicle autonomous: a high-definition map (HD Map), a state and geolocation estimator and a motion manager.

1. HD Map (High-Definition Map)

The very first thing a self-driving car needs is the ability to detect its location in the world. To achieve this, an autonomous vehicle needs to have an HD map that includes plenty of data about the road and the surroundings.

HD maps help with the management of lateral, longitudinal and speed control; these three aspects of autonomous driving allow the car to regulate speed as well as change lanes safely. Thanks to HD maps, self-driving cars always know in which lane they are located throughout an established route, which includes all necessary lane changes they will eventually need.

There are specific companies who dedicate their efforts to create and maintain their HD maps. One good example is TomTom, which offers the TomTom HD Map . TomTom’s proprietary HD Map offers accuracy down to a few centimeters and helps sensors understand their surroundings.

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2. State and Geolocation Estimator

State estimators coordinate the input from all the sensors in the autonomous vehicle and keep the vehicle’s geolocation within the HD map up-to-date. The state estimator does this by receiving input and aggregating data from all different parts of the vehicle.

Different situations might favor different sensors. For example, if the vehicle is inside a tunnel the GPS signal might not be reliable and the state estimator might have to rely on other sensors such as LiDAR, radar and the tires’ motion to update the vehicle’s geolocation.

At the same time, on a highway or motorway, a truck might be in front of the vehicle blocking the LiDAR sensor from perceiving the road ahead. In this situation, our self-driving car will be unable to see what’s ahead. Nevertheless, with a reliable HD map and GPS signal, our vehicle can have a good idea of what lies ahead of it (whether it be the next junction or exit).

Ultimately, a state estimator will receive and combine data from multiple sensors within the autonomous vehicle. Not all sensors send data at the same rate. A LiDAR system can provide many pulsations per millisecond while GPS takes longer to update. The state estimator unifies values from various inputs.

3. Motion Manager

The motion planner is in charge of the movement. What’s more, a motion planner is where the artificial intelligence operates the vehicle based on the pre-established vehicle’s route. If we intend to move a self-driving car from point A to B, the first option might be going forward (or reversing or turning). The motion planner is in charge of determining which maneuvers are required for the vehicle to reach its destination.

Just as the state estimator helps the vehicle know when there’s an obstacle obstructing the vehicle’s route, the motion planner is in charge of calling for an emergency stop. Similarly, when it’s time for the vehicle to change lanes, the motion planner calls a maneuver for switching lanes.

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Benefits of Self-Driving Cars

Once we achieve a high level of autonomy for self-driving cars it will become a matter of changing our mentality and learning to rely on these vehicles. Here are some of the benefits we can achieve as a society that embraces self-driving cars.

Reduced Accident Rates

One major feature in autonomous vehicles is connectivity. Having connected autonomous vehicles on the road means that vehicles can communicate issues on the road or nearby accidents with each other. Even without connectivity, a road full of autonomous vehicles means a road without tired, distracted or drunk drivers.

Improved Mobility for the Older People and People With Disabilities

A world where self-driving cars are the norm would mean that seniors and those with disabilities would be less limited in terms of transportation and accessibility. Those who are unable or unqualified to drive for any number of reasons would be able to fetch their own groceries or get to their doctor appointments without worry.

Self-Driving Cars-as-a-Service

If you need a car today, you not only need to buy or lease the car, but you also need a garage or parking space, not to mention the fact that you need parking anywhere you take your car. You’ll also need insurance and gas. These expenses add up quickly.

This used to be the case with web servers. If you wanted to develop a business that required a web app or back-end service you needed to spend a lot of money on a server. Cloud computing brought to us the idea of SaaS. With SaaS products, you pay less money up front, get the primary product you want and let the company worry about all the infrastructure details. So, if you want a server only for one hour every day, you only pay for one hour every day. That is the business model behind Google Cloud Platform and Amazon Web Services .

In the future, access to autonomous vehicles might mean that we can request a car just like we request Ubers . Imagine a world in which you pay an autonomous fleet service fee to carpool to work or large entertainment events. It’s like public transit but more precise and (potentially) accessible. The price of these services could potentially become so competitive in urban areas that we lose the necessity of owning a car and instead we buy the service of a car only for as long as we need it.

Related Reading on Built In What Is Mobility as a Service?

Challenges of Self-Driving Cars

There are two technical challenges facing self-driving cars with regard to achieving the maximum level of autonomy, namely motion sickness and accident liability.

Motion Sickness

Motion sickness occurs when the movement you see is different to what your inner ear expects. This happens to some people when attempting to read a book in a moving vehicle. There are two factors that increase the chance of motion sickness in autonomous vehicles. First, if you’re unable to anticipate where and when the vehicle moves, you could develop motion sickness. Secondly, if you don’t keep your eyes in the area of motion, you might easily develop motion sickness.

Accident Liability

Within the context of self-driving cars, accident liability refers to the person liable for an accident caused by a self-driving vehicle. As we get closer to the highest level of autonomy, newer designs for autonomous vehicles will not include a dashboard, steering wheel or brake pedals. If a car doesn’t receive any human input, it becomes much more difficult for law enforcement agencies and insurance companies to determine liability. State and federal legislators will need to get involved to determine how we decide liability between the car manufacturer and the autonomous vehicle’s occupants.

History of Self-Driving Cars

The idea of self-driving cars dates back to the 1920s when The Houdina Radio Control company showcased a radio-controlled vehicle in New York City. In the 1950s, RCA Labs and General Motors demonstrated their ideas for autonomous vehicles that were to be controlled by special circuitry installed below the roads (think streetcars only the rails are underground).

Advances in AI have been particularly important to make driverless cars a reality. Machine learning techniques like convolutional neural networks (CNN), backpropagation (first practically implemented in 1989) and Max Pooling (first introduced in 1992 as the Cresceptron framework ) have become building blocks of modern computer vision .

Thanks to all the latest developments in the field of computer vision, cameras — crucial for object detection and recognition — have become important sensors in autonomous vehicles.

From 2004 to 2007 the Defense Advanced Research Projects Agency (DARPA) of the United States of America held three challenges. In these challenges they offered a one million dollar price for any team that could deliver an autonomous vehicle capable of crossing 150 miles through the Mojave desert. In the first challenge no one finished. In the second challenge five vehicles completed the course .

In 2007, Darpa held its third and final challenge in an urban environment — Victorville, California. In this challenge, vehicles needed to drive in traffic and perform a series of maneuvers such as merging, passing and parking. Carnegie Mellon University won the third competition. These challenges and their prizes were a great incentive for researchers and students to work on early-days problems for self-driving cars. In the final challenge, vehicles had to show real-time intelligent decision making based on their reaction to other vehicles on the road.

These days, most car companies offer a certain level of autonomy, such as park assist or collision detection. Furthermore, companies like Waymo and Tesla are pursuing full autonomy. In 2014, Tesla Motors announced their first Autopilot feature and in 2018 Waymo launched an autonomous taxi service called Robotaxi.

Uber also made an attempt at self-driving cars for food delivery and taxi services. However, they sold their driverless car division to a Silicon Valley startup called Aurora toward the end of 2020. Although Uber is working in partnership with Aurora to release a driverless vehicle, they also struck a deal with a joint venture between Hyundai and Aptiv known as Motional , which seems closer to delivering a driverless fleet for Uber.

Recent Expert Contributors Articles

What Riding in a Self-Driving Tesla Tells Us About the Future of Autonomy

By Cade Metz , Ben Laffin , Hang Do Thi Duc and Ian Clontz Nov. 14, 2022

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Tesla is driving

By Cade Metz, Ben Laffin, Hang Do Thi Duc and Ian Clontz. Cade and Ian spent six hours riding in a self-driving car in Jacksonville, Fla., to report this story. Nov. 14, 2022

When we decided it was time for lunch , Chuck Cook tapped the digital display on the dashboard of his Tesla Model Y and told the car to drive us to the Bearded Pig, a barbecue joint on the other side of town.

“I don’t know how it’s gonna do. But I think it’s gonna do pretty good,” he said with the folksy, infectious enthusiasm he brought to nearly every moment of our daylong tour of Jacksonville, Fla., in a car that could drive itself.

Chuck Cook and Cade Metz who reports this story sit inside Chuck’s Tesla which is in “Full Self Driving” mode

This is Chuck .

This is Chuck’s Tesla .

This is Cade .

For more than two years, Tesla has been testing a technology it calls Full Self-Driving with Mr. Cook, a 53-year-old airline pilot and amateur beekeeper, and a limited number of car owners across the country.

Tesla has long offered a driver-assistance system called Autopilot, which can steer, brake and accelerate its cars on highways . But Full Self-Driving is something different. It is an effort to extend this kind of technology beyond highways and onto city streets.

This summer, Elon Musk, the company’s chief executive, said the system would be available in more than a million cars by the end of the year. In August, we spent a day driving around with Mr. Cook and his Tesla to assess the progress of this experimental technology.

Over six hours, his car navigated highways, exit ramps, city streets, roundabouts, bridges and parking lots. While his hands were near or on the wheel and his eyes on the road, the car attempted more than 40 unprotected left-hand turns against oncoming traffic. It kept us on the edge of our seats.

All the while, video cameras recorded everything we experienced, including a GoPro mounted on the roof as well as the eight cameras installed by Tesla on the front, back and sides of the car.

The Trip to the Bearded Pig

The most telling moment came as the car drove us to lunch. After navigating heavy traffic on a four-lane road, taking an unexpected turn and quickly remapping its route to the restaurant, the car took a right turn onto a short street beside a small motel.

Cade: Did you intervene with a turn signal?

Chuck: No, no.

Chuck: I am not doing anything.

Chuck: It is going to have to remap though.

Chuck: I’m doing everything I can to have this take us to lunch.

But watch as the Tesla struggles to make sense of its environment, veering from the road into a motel parking lot. Chuck is forced to retake control.

Cade: Whoa!

Cade: What’s this?

Chuck: I don’t know.

Chuck is driving

After driving around the motel, the car almost immediately made the same mistake, jerking into the lot this time.

Chuck: I don’t know why it did that.

Chuck: So we had one disengagement and a reroute into a ...

Chuck: So let’s see what it’s doing here.

From a different angle, it was sobering to see how close we came to hitting a parked car after we rolled over a low curb separating the parking lot.

Even the car’s internal display, which uses red lines to denote boundaries that the computer vision system detects, suggests that the car struggled to distinguish the curb between the road and the lot.

Tesla is constantly modifying the technology, working to fix its shortcomings. Since the day we drove around Jacksonville, the company has twice released new versions of the technology that show signs of improvement. But the moment in the motel parking lot showed why it may be a long time before cars can safely drive anywhere on their own.

The experiences of beta testers like Mr. Cook are a window into the enormously ambitious and expensive bet that Tesla is making on self-driving technology. It and other companies are investing billions into researching and developing autonomous vehicles — taxis that can ferry us around town , trucks that will deliver our online orders and maybe even one day cars that will take our children to soccer practice.

Elon Musk and Tesla did not respond to requests to participate in this story. But Mr. Cook’s Model Y provides a glimpse of the future we are moving toward, which may prove to be safer, more reliable and less stressful — but is still years away from reality.

Tesla’s technology can work remarkably well. It changes lanes on its own, recognizes green lights, and is able to make ordinary turns against oncoming traffic.

Chuck: This is beautiful.

Chuck: I love this when it happens.

Chuck: It’s just like...

Chuck: Slows, sees, turns.

Chuck: It’s so different without traffic interaction, right?

Chuck: It’s just so confident when it knows.

But every so often, it makes a mistake, forcing testers like Chuck to intervene.

“That moment shows that the car can only know what it is trained to know,” Mr. Cook said of the sudden turn into the parking lot. “The world is a big place, and there are many corner cases that Tesla may not have trained it for.”

Experts say no system could possibly have the sophistication needed to handle every possible scenario on any road. This would require technology that mimics human reasoning — technology that we humans do not yet know how to build.

Such technology, called artificial general intelligence, “is still very, very far away,” said Andrew Clare, chief technology officer of the self-driving vehicle company Nuro. “It is not something you or I or our kids should be banking on to help them get around in cars.”

‘Chuck’s Turn’

Chuck Cook smiles as he stands next to his white Tesla

In the tight-knit community of Tesla enthusiasts, stockholders, bloggers and social media mavens, Chuck Cook is famous. This summer, Mr. Musk noticed the meticulous way he explored the boundaries of the technology in a series of YouTube videos.

Mr. Cook had been posting online clips of his Tesla trying to navigate an unprotected left turn near his home in Jacksonville. (Mr. Cook uses money from YouTube ads and donations from viewers to pay for cameras and other equipment.) To make this turn, the car must pass through three lanes of traffic approaching from the left, squeeze through a gap in the median and merge into three more lanes of traffic approaching from the right.

Sometimes, the car made the turn with aplomb, edging into the thoroughfare and waiting for a moment when it could speed into a far lane.

Other times, it got stuck beside the median in the middle of the turn — its rear bumper jutting into the oncoming traffic:

Soon, Mr. Musk noticed the videos and vowed to solve what Tesla enthusiasts began calling “Chuck’s turn.” In the weeks that followed, Tesla equipped several test cars with a new version of its self-driving technology and sent them to Mr. Cook’s neighborhood, where they spent several weeks testing the new software and gathering data that could help improve it.

Mr. Cook spent a good chunk of our day asking his car to navigate the turn named after him. Each attempt was different from the last. Sometimes, the cars approached much faster from the left. Other times, from the right. Sometimes, the gap between the two was enormous. Other times, it was tiny.

Not long after that day in Jacksonville, Tesla released a new version of its software to Mr. Cook and other beta testers.

The car’s display now showed a blue overlay that indicated what was a safe zone in the median.

Before the software update

After the software update

When facing heavy traffic, it could navigate Chuck’s turn with a precision that was not possible in the past. So if it needed to stop next to the median, it would position itself so that traffic could safely pass both in front and behind.

Chuck’s turn is just one scenario among the endless scenarios a Tesla might face on American roadways.

Some are relatively common. Companies like Tesla can test and retest their technologies in these situations until they are confident a car can handle them safely. But other scenarios are rare and unexpected — what industry experts call “edge cases.”

“It is very easy to solve the first 90 percent of the problem, very hard to solve the last 10 percent,” Mr. Clare said, referring to the decades-long effort to create self-driving cars. “You need to be able to handle those edge cases gracefully.”

Facing the unexpected

After lunch, when Mr. Cook told the car to drive us to a small neighborhood park near the river, the skies were overcast and the streets were wet from summer rain.

Guided by Tesla’s self-driving technology, the car drove along the river and over a bridge before reaching an intersection lined with trees. Then it turned left toward an unmarked road that ran between several giant oaks draped in Spanish moss.

As the car approached the shadows beneath this mossy canopy, it suddenly changed course, turned sharply right and headed the wrong way down a one-way street:

Chuck: Let’s see what it does here.

Chuck: Traffic there.

Chuck: Took the right of way.

Cade: Whoa, whoa, whoa!

Chuck: It didn’t find it.

The moment highlighted the difference between Tesla’s self-driving technology and “robotaxi” services being developed by companies like Waymo, owned by the same parent company as Google, and Cruise, backed by General Motors.

The robotaxi companies are trying to reduce these unexpected moments by tightly controlling where and how a car can drive. Using laser sensors called lidar, they build three dimensional digital maps of individual neighborhoods that give cars a fine grained understanding of their environment. Then they spend months or even years testing cars in these contained areas.

These companies are now preparing self-driving car services that will operate without backup drivers in places like San Francisco and Austin, Texas. But these services will have strict limitations that make the task easier. The cars will travel only in certain neighborhoods under certain weather conditions at relatively low speeds. And company technicians will provide remote assistance to cars that inevitably find themselves in situations they cannot navigate on their own.

Tesla is not operating in this way. Lidar sensors are too expensive for most consumer vehicles. Building three-dimensional maps and testing vehicles on every American roadway is impractical. So is remote assistance. This means that Tesla cars face the unexpected more often than Waymo or Cruise cars — and that testers like Chuck Cook must keep their hands on the wheel at all times.

Just last week, he and his car revisited a few of the scenarios we encountered in August. Sometimes, the car performed perfectly. Sometimes, it did not. It drove past the motel on the way to the Bearded Pig six times, and though it remained on the road three times, it mistakenly drove into the parking lot three times as well.

When it did veer into the parking lot, it did not swerve as egregiously as it did in August. Mr. Cook says he is impressed with the progress of the technology. But he also knows that far more progress is needed. He also knows that Tesla engineers are focused on the behavior of his car and that others may not perform as well in situations that have not been closely scrutinized.

“The technology is not ready to take the driver out of the seat,” Mr. Cook told me on a recent morning. “As they continue to iterate on the hardware and the software, it is a like a salmon going up river.”

After releasing the new beta, Mr. Musk softened his claims about the immediate future of the technology. He now says that the technology will not be widely available until next year — and that regulators are unlikely to approve it for use without hands on the wheel. Autopilot still requires this oversight .

Federal regulators have spent the past several months investigating a series of crashes involving Autopilot , and they have not yet revealed the results. Safety experts worry that the arrival of Full Self-Driving will lead to more accidents.

“It is inevitable,” said Jake Fisher, senior director of Consumer Reports’ Auto Test Center, who has used the technology. “The problem comes as this system gets better and people get complacent. It will still do the unexpected.”

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Cars are getting better at driving themselves, but you still can't sit back and nap

Camila Domonoske

A Waymo minivan moves along a city street during an autonomous vehicle ride on April 7 in Chandler, Ariz. Waymo, a unit of Google parent Alphabet Inc., is one of several companies testing driverless vehicles in the U.S. Automakers are also developing self-driving technology, but it still requires human drivers to take over when required. Ross D. Franklin/AP hide caption

If you're taking a lot of road trips this holiday season, maybe you've wished your car could just drive itself to Grandma's house.

The auto industry has been working on autonomous driving for years. And companies like Waymo and Cruise are testing fully autonomous driving — in some cities, you can already hop in a driverless taxi.

But if you want a genuinely self-driving car of your own, you're out of luck.

Yes, vehicles are getting better at controlling their own steering and acceleration in more situations.

But despite all the fancy names being used by automakers, the technology is still nowhere near the point where the car can handle all the driving while you nap — a distinction drivers must keep in mind.

"There are exactly zero self-driving cars available for purchase, anywhere in the world today, from any manufacturer," says Sam Abuelsamid, principal analyst at Guidehouse Insights.

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Hands off the wheel, but eyes on the road.

Take General Motors' Super Cruise. It's one of a slew of confusingly named "advanced driver-assistance systems" that allow cars to control their own steering and/or acceleration.

And it's one of just a few systems that allow a driver to actually — safely — remove their hands from the wheel on the road. For now, the feature is only available on some highways ; it relies on a combination of GPS, high-precision maps, cameras and radar.

When it's working, the vehicle can automatically control its speed and steering without the driver having to touch a pedal or the steering wheel. That might seem pretty close to the dream of a car that can do the driving for you.

But the technology doesn't work 100% of the time — and it doesn't pretend to.

When a vehicle with Super Cruise encounters a situation it finds confusing, like a construction zone or a stretch of highway where its map is missing data, it will hand control back to the driver.

The car signals that it needs assistance by flashing red lights on the steering wheel, and on some vehicles, through vibrations in the driver's seat.

And if something unexpected happens on the roadway, the driver is supposed to be ready to seize control in an instant.

A Domino's Pizza self-driving delivery vehicle, shown in Houston on July 22, is one example in which businesses of all stripes, from food delivery restaurants to trucking, are eyeing driverless technology. Brandon Bell/Getty Images hide caption

Because the car needs help some of the time, the driver has to pay attention all of the time.

"The human is always responsible for driving, even when you're hands-free," says Ron Arnesen, executive chief engineer for automated driving and active safety programs at GM.

GM doesn't assume people will do the responsible thing and pay attention.

There's a camera embedded in the steering column that tracks the driver's eyes — even behind sunglasses — to make sure they stay on the road. Should the driver's gaze wander, the vehicle makes progressively more alarmed buzzes, flashes and alarms, and eventually refuses to drive itself any more.

It's an essential safety feature, Arnesen says, because GM knows that Super Cruise will not be able to handle all road situations.

"If you're always paying attention," he says, "you can take over within a matter of a split second if you need to."

Even "Full Self-Driving" requires human oversight

Tesla, more than any other automaker, has heavily marketed the idea of a car that can genuinely drive itself.

Its "Autopilot" driver-assistance technology is a major selling point for the vehicles.

And a small number of drivers are now getting to test the long-promised "Full Self-Driving" software, which allows a Tesla to steer itself on ordinary city roads — handling turns, waiting at stoplights and responding appropriately to the sometimes-unpredictable behavior of other vehicles and pedestrians.

Hypothetically.

For now, Tesla's technology still requires a human to have their hands on the wheel and eyes on the road, despite being called "full self-driving."

"I like to keep my foot, like, hovering in between the gas and the brakes," says Victoria Scruggs, a Tesla owner who is part of the beta test. "You really don't know what it's going to do sometimes."

In a recent test drive with Scruggs, her Model 3 drove perfectly reasonably through some intersections. At others, it hesitated, or moved with strange jerkiness, or shut off mid-route and put Scruggs back in charge.

Scruggs says a previous version of the software swerved so aggressively into the wrong lane that it actually hurt her wrist.

In general, she says, her Tesla can drive itself very well on highways. It can do OK going straight on city streets, she adds.

"But when you throw turns into the mix, it's a little bit iffy," she says.

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As Auto Industry Goes Electric, Can It Avoid A Battery Bottleneck?

On city streets, the software makes driving more stressful, not less, she says. And as a Tesla beta tester, she uses it not to make her life easier, but to collect more data to help the company make the software better.

Tesla's marketing and rollout of this technology is controversial.

Tesla's more limited Autopilot technology, which only handles simple driving tasks and is less erratic, has been involved in deadly crashes , and multiple incidents in which it didn't seem to recognize emergency vehicles .

Safety advocates have expressed concern that Tesla drivers may be relying too heavily on Autopilot, assuming the technology will function better than it will.

They've also criticized "Autopilot" and "Full Self-Driving" as dangerously misleading names, and have raised concerns about Tesla testing experimental software on public roads.

Tesla, which has been criticized for exaggerating the capabilities of its software, did include a pretty blunt warning for drivers testing the "full self-driving" features. It cautions that it could do "the wrong thing at the worst time."

The better cars get, the harder they are to supervise

While no personal vehicles are 100% self-driving, the amount of driving these systems can handle on their own is impressive, compared to what was available on the market just a few years ago.

And it's not just pricey, cutting-edge Cadillacs and Teslas that have seen significant progress in this area.

Kelly Funkhouser, who runs automated vehicle testing for Consumer Reports , says car shoppers might be surprised to learn just how many new cars can do some driving for you.

More than 50% of new vehicle models can control speed and/or steering in highway driving situations, she says – even if they can't navigate for you from start to finish, handle highway lane changes or allow you to (hypothetically) paint your nails on the freeway.

High-tech driver assistance features do make driving — especially long highway hauls — much easier. They certainly make it more pleasant. And in some cases, like when cars automatically hit the brakes to avoid an accident, they can have clear safety benefits.

Baidu Apollo Robotaxis move on a street in Beijing on May 2. Chinese tech giant Baidu rolled out its paid driverless taxi service, making it the first company that commercialized autonomous driving operations in China. Andy Wong/AP hide caption

Still, these vehicles all require close human oversight to work safely.

And the smarter our cars get, the more challenging that becomes. Funkhouser says these driver assistance functions make driving "even more boring," and that worries her.

"It's human nature, really, to just kind of want to zone out and find something exciting to do other than watch the car drive," Funkhouser says. "It's just like watching paint dry, right?"

"That's what worries us most about these systems," she says. "As they become more competent, then it's easier for drivers to kind of want to check out and find something else to do."

In other words, you still need to keep your eyes on the road for that long drive to Grandma's house — no matter how boring it gets.

Correction Dec. 27, 2021

A previous version of this story misspelled Ron Arnesen's last name as Arneson.

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Self-driving Cars: Building The World’s Most Experienced Driver

Categories: Google Invention Self-Driving Cars

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Published: Apr 17, 2023

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The 5 strongest arguments for a self-driving future

Self-driving cars often get bashed online and by the media, but an autonomous future is almost certainly on the cards. It could happen sooner rather than later. With concerns constantly being raised (and I am one of those who has written such articles ), now it’s time to put a positive spin on things.

Six electric cars that won’t cost you a fortune
Range test: How far can these six electric cars go?

So here are the five strongest arguments that car manufacturers, tech enthusiasts and inventors have put forward for self-driving vehicles becoming the future of how we get around in our futuristic urban landscapes.

Safety - the number one argument

Safety is, above all, the strongest argument that proponents of self-driving vehicles have over anything else. As most road accidents are caused by human error, autonomous driving has the potential to reduce road traffic accidents and, more importantly, fatalities occurring on our roads, to zero.

Imagine a world with no tailgating, no reckless or aggressive driving, no road rage, no distracted drivers texting or on the phone, no drunk drivers ! Think about a freeway with no long-haul truck drivers that haven’t slept in 20 hours.

Studies in America have found that autonomous vehicles could eliminate 90% of all auto accidents. The savings would be huge - around $190 billion in damages and health costs - as well as the saving of thousands of lives per year.

The counter-argument: the safety argument relies on the software and the artificial intelligence behind autonomous vehicles being 100% reliable and 100% accurate. These studies often do not factor in the potential for malware, hacks or bugs.

Less traffic - the easiest to sell to the general public

Survey any group of drivers in any developed country in the world and traffic would be top of their list of gripes. As the argument goes, with all of our autonomous cars following the same rules in an obedient manner, traffic in built-up areas could be managed much better.

With an increase in safety, speed limits could also be much higher. Cars could drive much closer together, because reaction times and braking distances become less of an issue. Increased highway capacities, fewer traffic police officers and little need for electronic road signs - there are savings and efficiency gains all over the place.

The counter-argument: The only real argument against reduced traffic congestion is the one that says it is not possible due to the reliability of the technology.

Productivity gains - the one capitalism cares about

Another strong argument in favor of autonomous vehicles is increased productivity and reduced labor costs. Why have your workforce behind the wheel on their way to work when they could be working on their way to work? Think about those that are either too old or too young to drive, and the possibilities that autonomous vehicles would open up to those people. The same applies to those that are unable to drive due to disabilities.

What about those who drive for a living? Truck drivers, taxi drivers and bus drivers could all be out of a job, which is good news for the companies and governments that pay them.

At TechCrunch Disrupt in Berlin last month, I spoke with Tim von Toerne, Co-Founder and COO of Kopernikus Automative , a company that can retrofit today’s cars to make them self-driving. He put it quite bluntly when talking about the potential for using his equipment to move cars around Volkswagen's production facilities: “VW currently has about 4,000 drivers, on German salaries… that’s a big saving.”

The counter-argument: machines taking over human jobs is not going to win over voters, and would increase the likelihood of public resistance to disruptive innovation. This is where dystopia starts.

Lower costs - for the everyday consumer

When you calculate the costs for the everyday driver, autonomous driving provides long-term saving opportunities in more than one area. If the improvements in safety can be realized, we can expect a dramatic decrease in motor insurance premiums. There is also a strong argument for autonomous driving leading to much greater fuel efficiency, either in terms of traditional fuel or a reduction in electricity required through renewable energy sources.

Then there are the costs associated with owning a personal vehicle. If an autonomous driving future is successful, the need for having your own car could be removed entirely, leading to a reduction in the purchase and maintenance costs that come with car ownership. This leads us nicely onto our fifth and final argument.

The counter-argument: there are greener alternatives that already provide the same (or even better) cost benefits to car ownership today. The cost of autonomous public transport remains a contentious point. If Elon Musk ever gets his LA tunnel network up and running, can we really expect it to be cheaper than the bus?

Parking space and environmental benefits - for the long-term dreamer

Car ownership could hardly be less efficient than it is today. It is estimated that collectively, of all the cars we own, only about 5% of them are being used at any given time. That means that 95% of the time, our vehicles are stationary, or being wasted, as proponents of this argument would say. The effect of all this wasted metal and rubber is that more space is required to park our static cars. In Los Angeles, a particularly car-loving city, 14% (or about 17 million square meters) of all land is used for parking facilities.

Those that believe that self-driving vehicles can alleviate this problem argue that by having fewer cars collectively, but using the ones we do have on the roads for longer, saves space. For this to work, of course, better sharing schemes and public transport systems would be needed to make it a reality. Still, turning all of those parking lots into parks and public spaces sounds like a nice idea.

The biggest problem with autonomous driving has nothing to do with AI

The counter-argument: people like owning their own cars and the freedom and convenience that comes with it. Cars are status symbols, as well as practical means of transport. Convincing a materialistic society to give that up in the name of a collective greater good remains a huge challenge.

What do you think about the arguments presented in this article? Something you don’t agree with or think we missed? Have your say below the line.

David McCourt Editor

David enjoys staying abreast of the latest technology and newest Android apps. Outside of the office, he can be found playing snooker and writing bad 00s indie songs.

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Let's see how they perform on dirt roads with ruts, rocks and such. For most just a hiking trailhead parking lot or ski area parking lot with hand signals from some one in hat, glasses parka and mittens. Too much talk of urban conditions. Rural and recreational use are important too. Lots of skibride in the winter from Uber and Lyft. Difficult to automate the snowy conditions, obscured road markings too.

Self Driving Cars: All You Need to Know

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About self-driving cars

Updated 30 March 2022

Subject Experience , Learning

Downloads 48

Category Education , Life

Topic Car Accident , Driving , Research

The arrival of self-driving cars, also known as self-driving or non-driving machines, appears to be upon us, and yes, engineers have been playing with self-driving cars for the last few decades (Zakharenko, 2016). Self-driving vehicles are built to feel their sorroundings and navigate safely without human interference. Research reveals that 90% of car crashes are caused by mistakes committed by drivers, such as using cell phones while driving or driving under the influence of drugs or alcohol (Robertson et al., 2017). Over the past two decades, vehicle manufacturers have designed new and increasingly sophisticated features that provide more assistance to drivers to help mitigate such errors (Robertson et al., 2017). Features such as driver lane assists, blind spot monitors, speed monitors, and lane watch are all early forms of the autonomous vehicle innovation. Such features are essential precursors of semi- or fully-automated vehicles and will dramatically reduce road crashes. The idea of autonomous cars goes back to General Motor’s vision for the future of transportation at the 1939 New York World’s fair (Gogoll & Muller, 2016). In, recent year’s autonomous car research has experienced an unprecedented uptake. Due to advancements in technology, autonomous cars are now within our reach (Gogoll & Muller, 2016). Big automobile manufacturing companies such as BMW, Mercedes, Ford, GM, and Toyota, as well as leading tech companies such as Google and Apple, back the idea of the autonomous driving (Zakharenko, 2016). The first autonomous pods were introduced to public roads in the Netherlands, while the Japanese government launched an experiment with an unmanned taxi service in 2016 (Gogoll & Muller, 2016). Of course, not all autonomous vehicles operate the same way, and there continues to be a continuum of different types of vehicle automation. According to The US National Highway Traffic Safety Administration, automated vehicles can be distinguished at five levels. Level 0 indicates that they do not have any of their control systems, computerized, while levels 1 and 2 are cars in which the human driver is still mainly in control, though some features may be automated. Levels 3 and 4 are cars that are fully automated such that a human driver can cede full control of the vehicle (Gogoll & Muller, 2016). An example is the Tesla Vehicle Autopilot feature which has the capability of both being fully automated while still being able to be driven.Avoiding obstacles, such as other automobiles, pedestrians, curbs, and bicycles, is an essential component of autonomous driving. Autonomous cars use a variety of techniques to detect their surroundings, such as lidar, radar, laser light, GPS, odometer, and computer vision (Surden & Williams, 2016). The lidar system, which is mounted on the roof of the vehicle and rapidly rotates 360-degrees, enables autonomous cars to detect obstacles around them (Surden & Williams, 2016). The placement of the lidar on the roof and its rapid rotation allows it to identify objects on all sides of the vehicle. These include those behind the car, at a rate of up to one million readings per second (Surden & Williams, 2016), using lasers which allow them to be precise in their location determinations of objects. In addition to lidar, radar is used to detect the position and speed of surrounding objects. Radar detectors have a few advantages over lidar in specific positioning tasks as radar has a more extended range of up to several hundred meters or more (Surden & William, 2016). More importantly, radar is used in assessing the speed of multiple moving objects, such as nearby vehicles, in real time (Bajpayee & Mathur, 2015). A significant disadvantage of radar compared to lidar is its precision, which can be off by several inches to feet in detecting the location of stationary obstacles. To compensate for the advantages and disadvantages of both, autonomous vehicles often use information from radar and lidar in parallel to gain different sources of information about the location of obstacles (Surden & William, 2016). An array of sensors, powered and controlled by sophisticated algorithms and powerful software, is also used to aid the vehicle during navigation. In simple terms, the sensors fall into three broad categories: navigation and guidance; driving and safety; performance and control. Furthermore, many autonomous vehicles also use video cameras to detect the location and speed of nearby obstacles. Video cameras are spaced around the vehicle at known distances, which allow the vehicle’s computer to receive parallel images of the same objects from slightly different angles (Surden & Williams, 2016). The video cameras are used to read words on traffic signs or determine whether a traffic signal is green. Visual cues play an essential role in driving, and video cameras can capture information, such as color or language, that the other sensors such as lidar or radar may not be well suited to retrieve (Surden & Williams, 2016).A prime example of a fully functioning self-driving / fully autonomous vehicle is the Tesla Model S/X. Manufactured by an American multinational corporation with the same name; Tesla is the most consumer-friendly car manufacturer of autonomous cars. In a recent marketing video posted by Tesla CEO Elon Musk on the social media platform Twitter, the ‘eyes’ of the machine (Tesla Model X) are depicted, and viewers are shown a visual representation of what the vehicle sees and how the vehicle can sense its environment and navigate the foreign terrain. The system can detect lane lines, successfully and safely perform a lane change, identify pedestrians and also identify city speed signs and adjust speeds accordingly. At the end of the video, viewers are shown a new technology based on artificial intelligence whereby the vehicle can predict and avoid a potential collision. In the video, it is explained that the vehicle was able to achieve this by observing variables such as the speed of the car ahead of it, pattern changes of the driver in front of it and the reactions of other vehicles around it. It was able to combine all of these variables and make a precise decision of how to safely steer away from a collision with the least possible outcome for error. Since autonomous cars are relatively new technology, and their development is fostered mainly by automotive companies and engineers, much of the current debate revolves around the question of liability (Gogoll & Muller, 2016). Favorable ethical arguments for the introduction of the autonomous car have been made on environmental grounds. The optimization of acceleration profiles enabled by automation will allow energy usage to be optimized leading to reduced pollution and emissions (Diels & Jelte, 2016). With the increase in the aging population, automated vehicles could also improve mobility for those unable or unwilling to take the wheel. Also, self-driving vehicles may make traveling by car more productive and comfortable. The driver now becomes the passenger and can engage in non-driving activities, sit back and relax, read a newspaper, check emails or have conversations face to face with rear passengers (Diels & Jelte, 2016). As the vast majority of accidents can be attributed to human error, self-driving cars may reduce or eliminate driver error which could lead to safer roads (Diels & Jelte, 2016). It will also allow for more efficient road use with vehicles able to safely drive closer together, thereby using fewer roads, and reducing congestion and journey times (Diels & Jelte, 2016). Though it may come across as an oxymoron, as with any incipient technological advancement, we must also understand the ethical issues regarding self-driving cars. Our focus will be on the sequence of steps that the system undergoes in the process of acting. Autonomous vehicles have not achieved complex singularity or consciousness; therefore, their actions are based on pre-programmed algorithms written by humans. Thus, following this algorithm, self-driving cars should follow ethical rules. Self-driving cars are already able to make decisions that have ethical consequences. As such machines make increasingly complex and important decisions, we will need to know that their choices are trustworthy and ethically justified. Hence, we will need them to be able to explain the reasons for these decisions. Despite the various benefits associated with self-driving cars, there is a horde of the drawbacks related to their use. One of these is the ability of the vehicle to be hacked. Self-driven cars are purely dependent on latest technology. According to Eddie Schwartz, the vice president of the global solutions in the Verizon Enterprise subsidiary, the issue of cybersecurity is still half a century from maturity. He notes that the first half of the 21st century would see a large number of targets increase exponentially (Bansal & Kockelman, 2016). On August 2017, researchers demonstrated attacks of a Toyota Prius and Ford SUV allowing them to jerk the steering wheel, slam on brakes, or accelerate the car using a computer (laptop) which had been plugged into the diagnostic port.In 2011, a team of researchers was able to penetrate the vehicles’ system using Bluetooth, mobile phone and moreover a malicious audio file which had been burned onto a CD and played within the vehicles media player. Hacking is one of the leading challenges that modern techno-savvy individuals encounter (Moon Lee, 2016). A vehicle that has been hacked is hazardous as the person responsible might decide to ram it into other cars, a group of pedestrians or even into a shopping mall. Assume a situation where a vehicle has been hacked, and it passes through a police checkpoint. What will the traffic police do? Even if they shoot at it will continue moving as directed by the hacker. This is more dangerous than when the robbers have hijacked it.The second disadvantage of self-driven cars is that they entirely depend on the effectiveness of the sensor attached to car’s roof. If the sensors get damaged, it can be devastating to the operation of the car (Moon Lee, 2016). For instance, heavy rain may cause a malfunction of the sensor disabling it from assessing the conditions on the roads. This will prevent the car from proper navigation through the traffic, and the probability of the car having an accident is increased. Moreover, a change in the location of the road signs may hinder the sensors from detecting them and hence cause misdirection of the vehicle.The cost of the driverless technology on these vehicles is a challenge both to the manufacturers and the possible buyers. It has been established that the engineering, the power and the computer requirements, sensors and the software could add to more than $100,000. This is absurd to most people. They cannot afford such vehicles. This will make the production of such vehicles to be affected negatively. According to the data from the National Automobile Dealers Association, an average American can only afford to spend $ 20, 806 on a car. Thus, it would be tough for such a person to buy a Toyota Prius, which is estimated to cost around $ 320, 000 (more than a Ferrari 599).Self-driving cars create a legal issue since there is no legal precedent on how a case would be handled. The big question remains on who holds the responsibility when the car is involved in an accident. The software developer? The car manufacturer? The driver? This results in a blame game which is somehow tricky. Mostly, self-driven cars operate on the assumption that everyone else on the road is a law-abiding citizen and will follow the set guidelines. The vehicle is not equipped with instructions on how it can maneuver through hazardous situations. If example an oncoming vehicle skids off to the wrong lane, the self-driven car may not efficiently react to that situation. This is because they lack the moral ability to make the right decisions on the roads.Self-driven cars rely purely on accurate mapping systems through the GPS. If a wrong mapping has been done, it leads to a security concern to the owner and the state at large. GPS devices are not always accurate, and hence wrong directions can be fed onto the vehicles. Agil Juliussen, Director of research for infotainment and advanced driver assistance at HIS Automotive says that the electronic systems in the modern cars contain insufficient security measures. Adoption of the self-driven vehicles has led to a debate on the effects on the economy of the nation. If such technology is used in the transportation sector, it could have an adverse impact on the job creation sector (Bansal & Kockelman, 2016). Data released in 2014 indicated that more than thirteen million Americans work in the transportation sector, accounting for about 4.6 percent of the total labor force. Adoption of such technology means that more than half of these individuals will be rendered jobless. This is disastrous to the employment sector within American alone.A failure in other technologies will typically affect the functioning of self-driven cars. Failure of traffic signs may result in accidents since these cars do not account for human traffic signals. For example, in a situation where a traffic officer is directing vehicles in a crowded street, the self-driven cars will be unable to interpret the human signals. Privacy is another issue that can prevent people from buying the self-driven cars (Moon Lee, 2016). This is because for the computer to operate the vehicle, a lot of information would have to be stored on the software of the vehicle. People who love their privacy will not acquire such a vehicle for fear of the machine collecting personal data.Most vehicle owning individuals enjoy the act of being in control of the movement of their cars. Research done by the National Automobile Dealers Association showed that people enjoy driving their vehicles, even if they can afford a personal driver (Moon Lee, 2016). They would not hence acquire self-driven cars as it is a distraction from their enjoyment of being in control of the movement of their vehicles. They would prefer a standard car as opposed to the self-driven cars.Self-driven cars may also make people become ignorant of learning the driving ways. They would not see the benefit of a knowing how to drive as the vehicles will be self-driven. Instead of investing in driving education, they would spend the money in other ways (Bansal & Kockelman, 2016). One of the significant questions that continue to linger in people’s minds is; what would happen if such technology fails in the future and people are illiterate in the driving sectors? This would be devastating effects in the transport industry.Although the issue of self-driving vehicles has received mixed reactions, the driverless car is coming. The companies that are developing these vehicles consider such challenges as being, ’normal and expected’ (Moon Lee, 2016). As John Krafcik, CEO of Waymo, notes, these are some of the challenges that manufacturers encountered during the introduction of the electric trains. Kraficik, however, notes that several issues need to be addressed to ensure that the self-driving vehicles meet the buyers’ requirements.The recently launched Google self-driving car confirmed many people’s thoughts; self-driving cars are real. Since the introduction of Waymo vehicle, the company has been able to establish its position as the leading entity in the self-driving technology (Wieczorek, 2017). In fact, Fiat Chrysler Automobiles have confirmed that they will provide 500 Pacific plug-in hybrid cars that are to be used in the Arizona project. Waymo has also invited Phoenix resident to join the trial for testing the self-driven vehicles (Wieczorek, 2017). The individuals who have been chosen are from diverse backgrounds and have different transportation needs. They have to give feedback on their experience, which will enable Waymo to modify the vehicles with their requirements.Adoption of self-driving technology in vehicles will require the combined efforts among the many sectors in the transport industry. The manufacturers will have to make a car that incorporates the modern technology within it (Wieczorek, 2017). A vehicle that will enable users to install the latest technology and not cause any malfunction within it. The software developers will have to develop software that will be convenient to the users (Wieczorek, 2017). Moreover, the technology should not interfere with the functioning of the vehicle but should make it more advanced. They should also consider the privacy-conscious individuals.The security factor should also be a significant consideration by the developers. If all the security features are enhanced, many people will embrace the idea, and hence it will be successful. For instance, if a system which is difficult to hack is used, I believe the project will be a very successful one (Wieczorek, 2017). The government should, on the other hand, ensure that road components have been developed and ensure that they are up-to-date. For instance, the roads should be in excellent condition. The road signals should be effective so that they will not mislead the vehicles (Moon Lee, 2016). A damaged road sign should be repaired quickly and any changes within the transport industry to be communicated to the road users. When all these aspects are adhered to, the future of the self-driving cars will be guaranteed to be smooth and successful. No new technology lacks its share of challenges; hence manufacturers should not be cowered by hindrances to this technology (Wieczorek, 2017). Self-driving technology is not a futuristic idea; it is here with us. ReferencesBajpayee, D., Mathur, J. (2015). A comparative study of the autonomous vehicle. Retrieved from http://ieeexplore.iee.org.proxy.bib.uottawa.ca Bansal, P., & Kockelman, K. (2016). Are we ready to embrace connected and self-driving vehicles? A case study of Texans. Transportation.Retrieved from http://dx.doi.org/10.1007/s11116-016-9745-zDiels, C., Jelte, E. B. (2016). Self-driving carsickness. Applied Ergonomics, 53. Retrieved from http://doi.org/10.1016/j.apergo.2015.09.009Gogoll, J., Muller, J. F. (2016). Autonomous cars: in favor of a mandatory ethics setting. Science and Engineering Ethics, 23(3), 681-700. Retrieved from http://doi-org.proxy.bib.uottawa.ca/10.1007/511948-016-9806-xMoon Lee, J. (2016). A Design of Road Database for Self-Driving Vehicles. Indian Journal of Science and Technology, 9 (20). http://dx.doi.org/10.17485/ijst/2016/v9i20/94704Robertson, D. R., Meister, S. R., Vanlaar, W. G. M., Hing, M. M. (2017). Automated vehicles and behavioral adaptation in Canada. Transportation Research Part A: Policy and Practice, 104, 50-57. Retrieved from http://doi.org/10.1016/j.tra.2017.08.005Surden, H., William, M. A. (2016). Technological opacity, predictability, and self-driving cars. Cardozo Law Reviews, 38(1), 121. Retrieved from http://fc3yq3bj4d.search.serialssolutions.comWieczorek, A. (2017). The influence of self-driving transport vehicles on the field of logistics. Zeszyty Naukowe Uniwersytetu Gdańskiego. Ekonomika Transport I Logistyka, 66 (0), 107-114. Retrieved from http://dx.doi.org/10.5604/01.3001.0010.5602Zakharenko, R. (2016). Self-driving cars will change cities. Regional Science and Urban Economics, 61, 26-37. Retrieved from http://doi.org/10.1016/j.regsciurbeco.2016.09.003

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Australians are open to self-driving vehicles, but want humans to retain ultimate control

Professor of Future Urban Mobility, Swinburne University of Technology

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A mob set fire to a Waymo self-driving taxi in San Francisco last month as residents’ anger about the cars boiled over.

Self-driving “robotaxis” run by Waymo and other operators such as Cruise have been causing major concerns in the United States by failing to react properly to certain traffic situations.

So how do Australians feel about automated vehicles? To find out, we surveyed 562 people about their views on self-driving vehicles.

Overall, our findings showed good public support. Nearly half of our respondents saw autonomous vehicles as a desirable trend and travel option for Australians.

However, three-quarters wanted these vehicles to retain the option of being driven by a person. It’s notable, too, how many respondents were undecided – consistently around a third or more – about the issues put to them.

Read more: We were told we'd be riding in self-driving cars by now. What happened to the promised revolution?

So why the anger in the US?

Last October, a robotaxi operated in San Francisco by Cruise struck a pedestrian who had been knocked into its path by another vehicle. Instead of making an emergency stop, it dragged her about six metres along the road. Days later, the company said it would suspend all operations to examine its process and earn back public trust.

Waymo has also had some safety slips . Two Waymo cars crashed into the same pickup truck while it was being towed in Phoenix, Arizona, last December.

Read more: Driverless cars: what we've learned from experiments in San Francisco and Phoenix

Tesla Autopilot has not been immune to repeated errors either. Last December, Tesla recalled more than 2 million vehicles to fix an Autopilot flaw. The recall followed an investigation by US regulators.

In a further blow to the industry, Apple is reported to have cancelled its secretive “ Titan ” project to build a self-driving electric car. Billions of dollars were reportedly sunk into the decade-long project.

Read more: Tesla's recall of 2 million vehicles reminds us how far driverless car AI still has to go

Public acceptance of vehicles depends on trust

The industry now recognises that creating self-driving vehicles is a much harder technical challenge than previously thought. As recent incidents show, public acceptance and trust are also going to be crucial for their success.

In our representative survey of 562 respondents from Melbourne, the overall results showed good public support.

Around 47% of respondents had a positive view of these vehicles as a desirable trend and travel option for Australians. Only 18% disagreed, though 35% were undecided. Another 47% said vehicle automation would reduce their driving workload.

Sentiment about the benefits of these vehicles was also positive. A majority (51%) believed automated vehicles will provide them with more time to complete other tasks while travelling.

There was also good support for the potential of these vehicles to improve safety and reduce vehicle emissions if they are electrified.

People do not want to surrender all control

Highly automated vehicles do not require any human intervention. Overall, however, respondents did not favour this level of vehicle autonomy.

A large majority (74%) felt these vehicles must have the option of being driven by a person. Giving complete driving responsibility to a computer would make 62% of respondents feel stressed. Around 70% said they would like to control where and when to use the automated functions, and which functions to use.

Around 72% believed automated vehicles must be made identifiable by, for example, a specific label, licence plate or sign.

More than half (55%) thought it was unsafe for children to travel without an adult in a self-driving car.

These findings suggest most people are hesitant about entrusting all driving tasks to automation.

What other concerns do people have?

Around 80% of respondents were concerned about legal and financial liability in the event of a malfunction or crash. They had similar concerns about technology and system failures.

Respondents also raised concerns about how automated vehicles perform in bad weather conditions. Other issues included cyber security and data privacy.

Respondents emphasised concerns about the safety of automated vehicles in mixed traffic. Almost a third were strongly concerned about riding in a self-driving vehicle next to other automated vehicles.

Respondents also had concerns about how these vehicles will interact with other road users. Around 47% were strongly concerned about the safety of self-driving trucks in mixed traffic.

Respondents were more confident about the safety of automated public transport buses.

Read more: Driverless cars: stopping dead seems to be a default setting when they encounter a problem — it can cause chaos on roads

Ranking the barriers to public acceptance

We asked respondents to rank the barriers to public acceptance on a scale of 1 to 7 (1 is most significant and 7 least significant).

The most prominent concern (46% of respondents ranked it first) was technical reliability or trust in the technology. It ranked as the number-one barrier to public acceptance.

The high price tag of automated vehicles ranked second (31% of respondents). Legal issues (25%) ranked third. Then, in order, came concerns about cyber security, potential erosion of privacy, and technology maturity. Respondents ranked lack of regulations as their least concern – 38% put it in seventh position.

Around 40% of respondents showed a strong willingness to buy an automated vehicle. Their main reasons were to reduce their carbon footprint and for safety.

Almost 47% said competitive purchase costs and lower insurance premiums would increase incentives to buy an automated vehicle. Premiums could fall because some studies expect these vehicles to be safer than human drivers.

What’s next?

These findings enrich the debate on automated vehicle adoption in Australia by offering an understanding of public sentiment. The factors that sway public willingness to embrace these vehicles must be acknowledged. Policymakers, manufacturers and other stakeholders can then focus on resolving the concerns and responding to public desires.

Strategies such as live demonstrations and dedicated travel lanes and routes can help build trust. Financial incentives and policy to resolve legal liabilities are also likely to help foster the uptake of automated vehicles.

While fully autonomous vehicles remain elusive , many automated vehicle technologies available today can still be built into our cars to help improve safety, reduce driving load and emissions, and improve air quality.

Read more: 'Self-driving' cars are still a long way off. Here are three reasons why

Automated vehicles can play an important role in a sustainable transport future. But unless public concerns and barriers are addressed, travellers will remain sceptical of vehicle automation, and adoption of these vehicles will stall.

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Autonomous Cars /

People are afraid of self-driving cars — can the industry change that?

The av industry’s main lobbying group says driverless cars need to earn the public’s trust. but what if it’s too late.

By Andrew J. Hawkins , transportation editor with 10+ years of experience who covers EVs, public transportation, and aviation. His work has appeared in The New York Daily News and City & State.

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Driverless car surrounded by regular cars

Self-driving cars have an image problem. They stumble into construction zones , block ambulances , run red lights , and even injure the occasional bicyclist or pedestrian .

Forget the fact that most autonomous vehicles operate each day safely, anonymously, and without fanfare. There are hundreds in operation today in California, Arizona, Texas, and elsewhere, and the numbers are only going to increase. But when they do make mistakes, people tend to notice. Numerous public opinion polls have shown declining support for autonomous vehicles (AV) over the years and a rise in outright hostility toward the technology.

The autonomous vehicle industry’s main lobbying group — yes, of course it has one — is intent on reversing this trend before it gets much worse. The Autonomous Vehicle Industry Association (AVIA) represents Cruise, Waymo, Zoox, Motional, and others. Today, it released something it’s calling its “TRUST Principles,” which is basically an action plan for dealing with these negative headlines and spiraling poll numbers.

Robotaxi companies have a serious trust issue
Robotaxis are driving on thin ice
The AV industry sends an SOS to Pete Buttigieg

“With today’s announcement, the AV industry is sending a message: we believe that public trust in autonomous vehicles is essential to their acceptance and that the AV industry must earn and maintain that trust,” Jeff Farrah, the group’s CEO, said in a statement.

The group is calling for a number of changes to the way AV operators interact with the public, including more community engagement and public education efforts as well as the creation of working groups to address some of the main concerns. For example, AVIA says it will create a “national council of law enforcement officials, first responders, and industry representatives” to improve communication between AV operators and emergency responders.

People have grown increasingly unnerved by the prospect of self-driving cars taking over the streets thanks to a lack of urgency in the industry toward building public trust. A lot of operators assumed that people would be thrilled by the futuristic concept of human-free driving and the promise of earning back lost time to driving, and that trust could come later. But several recent incidents have thrown that assumption into stark relief.

“We believe that public trust in autonomous vehicles is essential to their acceptance”

Last October, a driverless Cruise vehicle struck a pedestrian in San Francisco who was first hit by a human driver, and then caused further injury by attempting to pull over to the curb with her still trapped underneath. California regulators accused Cruise, which is backed by GM, of withholding video footage showing the incident and suspended its operating license. The company has recently said it will redeploy vehicles in Arizona — but only those that are manually driven with safety workers.

There have also been numerous incidents of driverless Waymo and Cruise vehicles blocking intersections, obstructing emergency vehicles, or generally causing chaos in the streets. In February, a driverless Waymo vehicle was vandalized and ultimately set on fire by a crowd of revelers in San Francisco’s Chinatown.

Waymo’s Self Driving Taxis Launch In Los Angeles

Running parallel to all of this is Tesla and the company’s ongoing efforts to deploy its Full Self-Driving (FSD) driver-assist system. Tesla vehicles with FSD are not autonomous in the way that Waymo and Cruise vehicles are; they still require a human driver to pay attention to the road at all times during operation.

But to most people, it’s a distinction without a difference. When a Tesla vehicle is captured behaving erratically or when there’s a crash causing injuries or fatalities , many people tend to blame all autonomous vehicles — despite the absence of any real autonomous Teslas on the road.

Tesla is not a member of AVIA, and the group often goes out of its way to draw a distinction between its members and driver-assist systems like Tesla’s FSD. But Elon Musk has said he plans to unveil a robotaxi later this year , which is sure to further muddy the waters of the public’s perceptions of autonomous vehicles.

Which is to say, AVIA is likely going to have a lot of work still to come if it wants to reverse the trend of declining public trust. Moreover, any effort to build and sustain public trust in autonomous vehicles needs to reckon with the way they are currently perceived — not with how the AV operators and its lobbyists may want them to be perceived.

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Orange cones are robot kryptonite., uber eats is now delivering burritos via waymo in phoenix., the zoox come out at night., waymo opens up in la..

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Here's Why Consumers Are Scared of Self-Driving Cars

Today is Friday, so it must be podcast day!

In our newest episode, I speak with Greg Brannon from AAA about consumer fears that surround autonomous vehicles -- and how the industry can address them.

I also chat with our resident auto-parts and accessories expert Matthew Guy to learn about headlight restoration kits, and then Matthew and I dissect NASCAR's race at Texas last weekend.

As always, you can find our podcast at the following places: Spotify , Apple , Google , Amazon , and iHeart Radio . As well as here .

Thanks for listening!

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Become a TTAC insider. Get the latest news, features, TTAC takes, and everything else that gets to the truth about cars first by subscribing to our newsletter .

Tim Healey grew up around the auto-parts business and has always had a love for cars — his parents joke his first word was “‘Vette”. Despite this, he wanted to pursue a career in sports writing but he ended up falling semi-accidentally into the automotive-journalism industry, first at Consumer Guide Automotive and later at Web2Carz.com. He also worked as an industry analyst at Mintel Group and freelanced for About.com, CarFax, Vehix.com, High Gear Media, Torque News, FutureCar.com, Cars.com, among others, and of course Vertical Scope sites such as AutoGuide.com, Off-Road.com, and HybridCars.com. He’s an urbanite and as such, doesn’t need a daily driver, but if he had one, it would be compact, sporty, and have a manual transmission.

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Title about self driving cars, linked podcast about headlight restoration. Some relationship?

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Tesla, waymo, nuro, zoox and many others embrace new ai to drive.

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A Tesla equipped with the (now Supervised) FSD system, which is more machine learning based

Machine learning based AI, particularly the Transformer and Large Language Model AI found in ChatGPT, has captured most of the tech headlines in recent years for good reason. Self-Driving cars, which will use AI to upend the world’s 3rd largest industry are also embracing these new AI technologies as fast as they can. At the recent GTC conference of Nvidia—the two-trillion dollar value chip company making the most popular AI hardware, several companies outlined their strategy, but in truth every company in the space has shifted their strategy firmly into this area.

A classic self-driving system is divided into modules, which are roughly layered. The core modules are perception (what’s out there), prediction (where is everything going), planning (where will I go) and execution (pedals and wheel) with additional support for localization (where am I?), as well as mapping, user interface, HQ interface, remote operation and more. The lines between perception, prediction and planning have become blurred, and most of all in what’s known as an “end to end” neural network design.

Tesla made waves by rewriting their driver assist system (now called Supervised Full Self Driving) to heavily use end to end networks. In an E2E system, there’s very little traditional programming logic. Instead, data from sensors (particularly cameras in Tesla’s case) go in and driving decisions come out. It is frightening to some that the programmers have only a limited idea of how the system makes decisions, they just know it does better. Most reviewers believe that Tesla’s new SFSD outperforms the older one—though many reviewers don’t realize just how greatly far behind the other self-driving systems it remains, in spite of improvements.

There are other believers in E2E, however, to various degrees, including UK startup Wayve and Toronto startup Waabi, which both presented at Nvidia GTC. Open source ADAS tool “comma” has also long used it, and HYPR, the new startup from Zoox co-founder Tim Kenley-Klay also is reported to use this approach. Writing the software is “easy” because you don’t write much, what matters is getting the right training data, and lots of it, combined with lots of compute. Tesla has been planning a giant compute center called Dojo for this, but construction of it has been delayed, reportedly angering Elon Musk and resulting in some of the recent executive departures.

Your initial training data comes from recordings of humans (and robots) doing successful drives. You must remove or label any recordings of bad driving behavior or the system will learn it. (Tesla had to remove all recordings of people doing rolling stops, since NHTSA ordered them to not have their cars do this very common activity.) Most teams also add simulated drives to the training data, and this is the specialty at Waabi, which does most training in simulator. This includes adversarial training, where one AI tries to be as clever as possible in creating simulated scenarios which will make the car crash, so it can learn what not to do. This can allow the car to have experienced far more bad situations than any human could.

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Even the companies not going E2E are making use of the same technology found in tools like ChatGPT. The “transformer large language model” has wowed the world with what it can do with written documents, but to the AI, text is just a series of words, and it learns what the best word to put out next is based on what it has seen so far. The transformer technology helps it know which words in longer texts are most worth paying attention to.

Driving may not seem like writing, but once perception has been done, what the sensors see can be turned into a string of tokens not too different from sentences. And so, an LLM that has been trained on tons of driving can get very good, and very human, at deciding what should come next in any situation. You can try this with your favorite AI, and you may see that even though all it did was read books about driving, it’s able to figure things out from very basic perception information.

Google Gemini describes how to drive at an intersection

Gemini’s answer isn’t perfect, but realize it was never trained on any actual driving, it just read the manuals. That it can do the above is astounding, but a tool trained on actual driving and quality tested can do even better. And that’s what most of the self-driving companies are now experimenting with. Some fully, others with more caution.

Nuro, for example, which makes delivery vehicles, has both an AI planner and a traditional one, and they both make proposals for what the machine should do at any given moment. Another tool then picks which of the plans it thinks is best. Usually it’s the AI planner that makes the best and most human-like choice.

Zoox has been slower to fully absorb LLMs but is working on it as well, and while Waymo has made limited comment they are also believed to be doing so—after all, the transformer model that lies at the base of all LLMs was developed at Waymo’s sibling Google.

It’s not always good. There is suspicion that when a Cruise car made a left turn from the middle lane of a San Francisco street, crossing in front of a backhoe which hit it, this might have been decided by a machine learning planner which had seen too many humans pull stunts like this. And the “hallucination” problem, where LLMs output plausible but wrong answers, requires attention.

People are afraid of “black box” approaches which may make decisions for reasons unknown to their developers. If you encounter problems, you can “fix” them by adding more training designed to discourage the bad choices, but without the same certainty of traditional programming. I often ask people, “Would you prefer a car that crashes once in a million miles but you can’t explain why, though you can fix it, or a car which crashes twice in a million miles but you know just why it did?” I get both answers.

UK developer Wayve has merged an actual text LLM with their E2E driving system. You can ask it at any time why it’s doing what it’s doing. They hope that will make people feel better, as well as help debug it. When it was stopped at a red light with some cars ahead of it, I asked it why it wasn’t going. It mentioned the red light, but not the more important forward traffic, which I felt was a serious error, since it would not drive into them just because the light went green. This approach thus needs more work but may help deal with the fear.

It’s good news that so many different approaches are being worked with, from LLMs to classic imitation and reinforcement learning, to traditional robotics constraints that are better at rigidly following rules of the road. Tesla and MobilEye have the largest pools of data of human drivers and hope those will give them an edge in a world where the party with the most training data and compute wins. But there’s a lot of data out there, and a lot of compute, when you consider that companies like Google, Amazon and Nvidia are still fighting in this game. While a number of companies have shut down in this race, including projects at major automakers, there are still many in the race, hoping to be the first to deploy this at scale.

The author has investments in NVDA, TSLA, GOOG, Deepen.AI (AI training) and Permion (explainable AI) and some others.

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It's easy to bash tech, but I've started taking robotaxis — and they're awesome

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Unlike other hyped-up tech, self-driving taxis look like they could be the real thing.
You can take Waymo's software-powered taxis in San Francisco and Phoenix. They work just like an Uber.
Waymo's robot taxis aren't perfect, and there are very reasonable concerns about them. But also: They're self-driving taxis that really work!

It's easy to crap on tech. We — I — do it all the time.

Sometimes it's because tech doesn't work the way I want it to . Sometimes it's schadenfreude about a big hyped thing that falls flat . Sometimes it's just a sense that the tech we all depend on may be harming us in ways we don't understand and can't control.

But also: Sometimes tech reminds you that tech can be awesome, in the golly-gee-can-you-believe-it sense some of us used to have about this stuff.

Which is exactly how I felt after my last trip to San Francisco, when I took several rides in Waymo's robotaxis .

That's partly because the tech is … amazing. You really are in a car, driving around the city, with no one in the driver's seat. Software and sensors take care of everything.

And partly because the tech already seems so … normal. You order a Waymo via an app, just like an Uber or Lyft. It shows up, you get in, it takes you where you want to go, and you get out.

Yes, my 13-year-old son and I spent the first few minutes in our first Waymo texting our friends and family: OMG IM IN A SELF DRIVING TAXI. We also documented it on social, of course.

View this post on Instagram A post shared by Peter Kafka (@pkafka)

We also felt a bit of the trepidatious rush you get when you sit down in a roller coaster and have that internal debate: Is this safe? It must be safe, because otherwise they wouldn't let you do it, right? But seriously, is this safe?

But after those first few minutes of novelty, we went back to doing what we always do in an Uber or a Lyft: zoning out on our phones, staring out the window, and spending next to no time thinking about who, or what, was driving us.

Which, to me, is really the most amazing part: This stuff is here, now, and you can … just use it.

At least some people can. Waymo, which is owned by Google's parent company, Alphabet, has a couple hundred self-driving cars roaming around San Francisco, and access is still limited there via a waiting list, as well as by geography . You can't get a Waymo to pick you up at San Francisco International Airport, for instance, or take you across the Bay Bridge to Oakland.

In Phoenix, where Waymo first launched consumer access , it has about the same number of cars but no waiting list. And now it's starting to roll out in Los Angeles and Austin.

We've heard about self-driving taxis forever, but they're just starting to become a reality

While Waymo says it drives tens of thousands of trips a week, even the most tech-savvy people I talk to have yet to ride in one.

And it's reasonable to have concerns about this tech as it rolls out. Waymo's rival Cruise halted its service last fall after a slew of incidents, including a grisly one where a self-driving Cruise dragged a pedestrian who had been hit by a human-driven car.

Waymo's self-driving cars aren't perfect

Yes, there are still some issues with Waymo, at least in the rides I took recently. One is simply figuring out how to get in the thing: When your Waymo arrives, you unlock its doors with your phone — but only once it has driven to a very precise location that Waymo knows and you don't.

Which led, a couple times, to some awkward slow dancing between myself and the robot car. It would stop when I got near but wouldn't let me in because it wasn't exactly where it was supposed to be. Then I'd step away, and then it would lurch forward toward its still-unknown-to-me target spot. Then I'd step forward and it would stop — but it still wouldn't let me in.

On one of my trips, this happened on a particularly tight, winding San Francisco street. As my Waymo and I negotiated with each other, we ended up blocking multiple cars, including a minivan whose driver started honking at us in frustration.

"You can't honk at a robot," I told her, not very helpfully. "It doesn't care."

Meanwhile, a guy walking by stopped and took out his phone to record the scene. "You can put a cone on it to disable it," he told me, unprompted. Apparently he's right?

More worrisome to me was that on one of my trips — to a Warriors game at the Chase Center arena — at a busy intersection, a Waymo in front of us wouldn't respond to a traffic cop trying to wave it through a red light. Then another Waymo pulled up beside it and also didn't respond to the cop. So now three Waymos were sitting there, blocking traffic and waiting for the light. The traffic cop stopped trying to move us and just held his hands over his head in disgust.

I figured this was a well-known and understandable problem for Waymos — of course their software and sensors wouldn't respond to humans telling them to override traffic signals! Think of the problems that could cause!

But Margines told me that Waymos are, in fact, supposed to understand human signals like a traffic cop. A Waymo PR person sent me this clip from Waymo CEO Dmitri Dolgov showing a Waymo doing just that:

Leveraging AI for semantic understanding of complex driving scenes is a key capability of the #WaymoDriver . Check out this example of it autonomously interpreting and adhering to a police officer directing traffic in Los Angeles. pic.twitter.com/PyPqVaOc6B — Dmitri Dolgov (@dmitri_dolgov) January 19, 2024

But unlike with other Big New Tech innovations I've seen in the past — anyone still have a 3D TV in their living room? — I don't think self-driving tech is going away. I think the people behind the tech will figure out its possibilities, its limitations, and the places it does and doesn't make sense.

Meanwhile, Cruise is starting up again , but this time with humans in the driver's seat. Elon Musk has promised to unveil his robotaxi this summer, and while your doubt about anything Musk says is well warranted, you never know. So I think that one way or another, we are going to make some version of this standard for many of us in the not-far-off future.

Is that great? I don't know. But it really is amazing.

Watch: Driverless taxi torched by mob in San Francisco

Main content

Tesla to unveil robotaxi self-driving car in August, Elon Musk says

Elon Musk announced that Tesla will unveil its robotaxi this summer.

The X owner and Tesla CEO unveiled the Aug. 8 release date on a post Friday.

The entrepreneur has previously discussed efforts to create Tesla cars without human controls and for existing vehicles to gradually improve its Full Self-Driving Capability, which are not fully autonomous.

The technological feat has been a longtime goal for Musk, who has said autonomous taxis could revolutionize modern transportation by becoming more popular than human-driven cars and that automaker would be "worth basically zero."

Musk wanted to release robotaxis in 2020

In April 2019, Musk revealed that he expected Tesla robotaxis to be fully operating by 2020 .

The company predicted that driverless vehicles would withstand 11 years and 1 million miles, earning the company $30,000 in annual profit. He also shared that the cars would would be accompanied by a ride-share app similar to both Uber and Airbnb.

U.S. and Chinese regulators have currently only approved self-driving cars in limited and experimental instances on public roads.

The automotive company faces lawsuits and investigations related to crashes with its existing autopilot and Full Self-Driving driver-assistance systems, which the company has Tesla has explained were the result of inattentive drivers.

Tesla shares down after low-cost EV plans are scrapped

Musk's announcement comes after a Reuters report revealed that Tesla has scrapped plans for its l ong-promised inexpensive car , according to three sources familiar with the matter and company messages.

Investors have been relying on the project to drive its growth into a mass-market automaker, according to Reuters.

Musk has often described affordable electric cars for the masses as a primary mission. In 2006, he said his "master plan" had to prioritize manufacturing luxury models before financing a "low cost family car."

Tesla shares closed down $6.21, or 3.63%, at $164.90 on Friday.

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Tesla's Full Self-Driving keeps driving cars into curbs, drivers say

It’s difficult to tell if this curb hopping problem is new due to a change in the vehicle software, or if it’s just being talked about more often.

Tesla owners are understandably peeved about the newest update (version 12.3.4) to the so-called Full Self-Driving suite of driver assist features. It would seem that Tesla’s camera-only driving system is having a hard time figuring out curbs . As InsideEVs pointed out , some owners are taking to social media to voice their displeasure that their cars are driving into curbs and costing them thousands of dollars in repairs to the wheels and new tires. Curbing a wheel is embarrassing and annoying, but doing it at speed is potentially quite dangerous.

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Future Of Autonomous Vehicles: Self-Driving Cars Explained
Self-driving cars offer a number of advantages over vehicles requiring hands-on drivers including convenience, access to mobility, efficiency, cost-savings and traffic congestion.
Seven Arguments Against the Autonomous-Vehicle Utopia
But in a duo of essays in 2017, ... The transportation reporter and self-driving car skeptic Christian Wolmar once asked a self-driving-car security specialist named Tim Mackey to lay out the problem.
Self-Driving Car Ethics
Self-driving cars are programmed to be rule-followers, explained Saripalli, but the realities of the road are usually a bit more blurred. In a 2017 accident in Tempe, Ariz., for example, a human-driven car attempted to turn left through three lanes of traffic and collided with a self-driving Uber. While there isn't anything inherently unsafe ...
The ethical dilemma of self-driving cars
Self-driving cars are already cruising the streets today. And while these cars will ultimately be safer and cleaner than their manual counterparts, they can't completely avoid accidents altogether. How should the car be programmed if it encounters an unavoidable accident? Patrick Lin navigates the murky ethics of self-driving cars.
What Are Self-Driving Cars? How Do They Work?
History of Self-Driving Cars. The idea of self-driving cars dates back to the 1920s when The Houdina Radio Control company showcased a radio-controlled vehicle in New York City. In the 1950s, RCA Labs and General Motors demonstrated their ideas for autonomous vehicles that were to be controlled by special circuitry installed below the roads (think streetcars only the rails are underground).
What Tesla 'Full-Self Driving' Tells Us About the Future of Autonomy
799. By Cade Metz, Ben Laffin, Hang Do Thi Duc and Ian Clontz. Cade and Ian spent six hours riding in a self-driving car in Jacksonville, Fla., to report this story. Nov. 14, 2022. When we decided ...
Why self-driving cars still require a lot of human supervision : NPR
For now, Tesla's technology still requires a human to have their hands on the wheel and eyes on the road, despite being called "full self-driving." "I like to keep my foot, like, hovering in ...
Self-driving Cars: Building the World's Most Experienced Driver: [Essay
Competitors like Ford and Volkswagen, BMW and Daimler expand their alliance in developing self-driving cars, as self-driving car business is extremely expensive. Tesla prefers to work alone and has a different approach to autonomous cars. It has already put over 300,000 semi-autonomous cars on the road and has been collecting real-world driving ...
The 5 strongest arguments for a self-driving future
Safety - the number one argument. Safety is, above all, the strongest argument that proponents of self-driving vehicles have over anything else. As most road accidents are caused by human error, autonomous driving has the potential to reduce road traffic accidents and, more importantly, fatalities occurring on our roads, to zero.
Self Driving Cars: All You Need to Know
Self-driving cars are coming closer and closer to being fact not fiction, but are we ready for them? In this research we analyze the current status in place for self-driving cars. We address the gaps that need to be filled, and we identify the questions that need to be answered before having self-driving cars on the road becomes a reality. Towards this, we discuss four issues with self-driving ...
Self-Driving Cars: Pros and Cons (Free Essay Sample)
This is a free essay sample available for all students. If you are looking where to buy pre written essays on the topic "Self-Driving Cars: Pros and Cons", browse our private essay samples.. The future is ripe for advances in car technology. Today, discussions abound on the potential of self-driving cars to revolutionize road safety and efficiency.
About self-driving cars
About self-driving cars. This sample was provided by a student, not a professional writer. Anyone has access to our essays, so likely it was already used by other students. Do not take a risk and order a custom paper from an expert. The arrival of self-driving cars, also known as self-driving or non-driving machines, appears to be upon us, and ...
Australians are open to self-driving vehicles, but want humans to
A mob set fire to a Waymo self-driving taxi in San Francisco last month as residents' anger about the cars boiled over.. Self-driving "robotaxis" run by Waymo and other operators such as ...
People are afraid of self-driving cars
Illustration by Alex Castro / The Verge. Self-driving cars have an image problem. They stumble into construction zones, block ambulances, run red lights, and even injure the occasional bicyclist ...
Here's Why Consumers Are Scared of Self-Driving Cars
Subscribe. Description. In This Playlist. 10 of 26 Episodes. Here's Why Consumers Are Scared of Self-Driving Cars. 1 hr 11 min. There's a New Problem With Electric Cars That No One Saw Coming. 50 min. These Are the Best Family Cars for 2024.
Tesla, Waymo, Nuro, Zoox And Many Others Embrace New AI To Drive
Self-Driving cars, which will use AI to upend the world's 3rd largest industry are also embracing these new AI technologies as fast as they can. At the recent GTC conference of Nvidia—the two ...
Waymo's Self-Driving Robotaxis Are Awesome. Here's How.
Apr 15, 2024, 9:07 AM PDT. Unlike other hyped-up tech, self-driving taxis look like they could be the real thing. You can take Waymo's software-powered taxis in San Francisco and Phoenix. They ...
Tesla to unveil robotaxi self-driving car in August, Elon Musk says
0:35. Elon Musk announced that Tesla will unveil its robotaxi this summer. The X owner and Tesla CEO unveiled the Aug. 8 release date on a post Friday. The entrepreneur has previously discussed ...
Tesla Full Self-Driving keeps driving cars into curbs, drivers say
Tesla's Full Self-Driving keeps driving cars into curbs, drivers say It's difficult to tell if this curb hopping problem is new due to a change in the vehicle software, or if it's just being ...