essay self driving cars

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 .

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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The Dangers of (Self-)Driving Cars

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By Melinda Sacks

Driverless vehicles are expected to greatly decrease traffic fatalities, but they will sometimes have to decide between bad options. Would your car swerve to miss a cyclist at the risk of hitting another vehicle head-on? Would it protect its own occupant at a greater risk to others?

Not surprisingly, respondents to a series of 2016 surveys reported in the journal Science  said that — in concept — they believe autonomous cars should sacrifice their passengers’ well-being for the greater good, but they personally would not ride in or buy such a vehicle.

Jason Millar, a postdoctoral research fellow in engineering and ethics, is one of a dozen scientists and researchers from across Stanford tackling some of the prickliest questions keeping automakers up at night.

“It is one thing to say that a machine is working better than the average human,” Millar says, “but that is based on what it means to be better. The set of criteria you use is negotiable. It can be contentious. That is where some of the interesting ethical questions arise.”

Millar wants to equip engineers to make some of the most important decisions about safety in the design room. He predicts that engineering ethics will become an important new field. “We need to get engineers solving these problems who are attuned to human ethics and human knowledge,” he says.

Mykel Kochenderfer, ’02, MS ’03, an assistant professor of aeronautics and astronautics, has brought his experience with aircraft automation to the autonomous driving discussion. As director of the Stanford Intelligent Systems Laboratory, he develops advanced algorithms and analytical methods for use in air traffic control, unmanned aircraft and other applications in which decisions must be made in uncertain, dynamic environments while maintaining safety and efficiency.

‘We need to get engineers solving these problems who are attuned to human ethics and human knowledge.’

Kochenderfer notes that, in the near term, bringing autonomous transportation to places outside the Bay Area — which benefits from “pristine” weather and a culture of innovation — will be a challenge. On a recent trip to Boston, he found himself at an intersection that took all his cognitive abilities to figure out how to navigate safely. In that moment, he could not imagine a driverless car being able to handle it.

“A lot of what we bring to autonomous vehicles comes from aircraft avoidance systems,” he explains. “In that context, you can be really, really safe if you maneuver when you see another aircraft.” But on the road, the proximity of other vehicles is a given. For example, on a two-lane road, an approaching truck can plow into a car in less than a second.

“You have to reason about the likelihood that they will invade your lane,” he says. “There is nothing you can really do about it other than [not] leave your driveway.”

Regulators — another key part of the safety puzzle — also have a ways to go in adapting laws and policy to autonomous driving. As of late March, 32 states had passed legislation or issued executive orders related to autonomous vehicles, according to the National Conference of State Legislators. While many of these laws have eased the deployment of self-driving vehicles, legislatures have yet to resolve how they will handle fundamental issues such as liability, insurance and safety inspections. Industry observers describe “a Wild West,” where adequate safety protections for consumers are not yet in place and where regulatory purview over the industry has yet to be determined. (A 2017 House bill seeking to consolidate power under the U.S. National Highway Traffic Safety Administration has yet to go before the full Senate, which is considering its own version of the proposed legislation.)

On the one hand, self-driving cars could democratize transportation, making independent travel possible for many who lack it, including people who are blind, disabled, young, old or poor. Prognosticators also expect reductions in pollution, traffic, collisions and the cost of getting around, and an increase in green space as the demand for parking lots declines. But skeptics worry that the adoption of driverless cars will eliminate too many jobs and give hackers a new way to attack, even possibly turning cars into lethal weapons.

As the debate about the deployment of autonomous vehicles unfolds, self-driving cars are hitting the road in droves. Ready or not, say experts, here they come.

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Home — Essay Samples — Science — Self-Driving Cars — The Rise of Self-Driving Cars: A Scholarly Perspective for Students

The Rise of Self-driving Cars: a Scholarly Perspective for Students

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A young man sitting in an autonomous car.

What Is An Autonomous Vehicle?

How do self-driving cars work, what are the pros and cons of driverless cars, advantages of self-driving cars, challenges of self-driving cars, what autonomous car companies are on the market, the future of self-driving cars.

An autonomous vehicle is broadly defined as one equipped with technology that senses the conditions around it, including traffic, pedestrians, and physical hazards and can adjust its course and speed without a human at the controls. The terms “autonomous” and “self driving cars” are often used interchangeably.

However, as defined by the SAE, formerly known as the Society of Automotive Engineers, there are six levels of automated driving ranging from full control of a vehicle by a physical driver, assisted by advanced safety technology, to a vehicle that can operate without any on-board human input. Only that top level represents a driverless, or fully autonomous vehicle.

In this feature we’ll define the six levels of what the SAE terms “automated driving,” or AD, the pros and cons of self-driving vehicles, where they’re being used, effects on traffic and the environment and what the prospects are of private citizens being able to own a car that drives itself.

An autonomous vehicle is defined by the University of Michigan Center for Sustainable Systems as one that uses “technology to partially or entirely replace the human driver in navigating a vehicle from an origin to a destination while avoiding road hazards and responding to traffic conditions.”

The SAE’s six levels of what it terms “automated” driving ranges from the first three levels (which start with zero), where a driver is behind the wheel and in control, but is aided by various automated warnings or safety features such as blind spot warning and automatic emergency braking. Levels 3 and 4 represent technology in which the vehicle is self-driving under certain circumstances but may require a human driver to take over. Finally, level 5—a fully autonomous, or self-driving, vehicle that does not require a human to operate the controls. This is the only level at which a vehicle is considered fully autonomous.

SAE chart showing six levels of automated driving.

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Self-driving cars see what’s going on around them using three main electronic “eyes”—radar, cameras and laser-based LiDar, which stands for light detection and ranging. All three feed data into on-board processors, using sophisticated software, algorithms and machine learning to send signals to the vehicle’s actuators to trigger appropriate actions such as braking, steering and acceleration.

The array of sensors can detect a wide variety of road features and obstacles such as lane markings, curbs, pedestrians, cyclists or other vehicles. This is done either visually, through cameras, or by bouncing light impulses or radar signals off of surrounding objects. While self-driving automation technologies help improve safety, they are not 100% infallible, and their effectiveness can be diminished when sensors or lane markings are covered by snow or other heavy precipitation.

Self-driving vehicles where there is either what’s known as a “safety driver” on board or no driver at all are currently in use, mainly by fleets that include warehouse yard trucks that transport goods from one contained location to another. Companies such as Kodiak Robotics and Gatik operate self-driving commercial trucks on certain routes with safety drivers on board.

Cab of Kodiak Robotics sixth-generation driverless ready autonomous semi-truck.

While Kodiak and Gatik aspire to run their trucks with no human on board, taxi services such as Waymo and Cruise are examples of when self-driving technology goes awry. Cruise, a subsidiary of General Motors GM Co., was forced to shut down its robotaxi service after one of its cars was involved in an accident that injured a pedestrian. In 2018 a driverless Uber UBER robotaxi with a safety driver aboard struck and killed a bicyclist in Tempe, Arizona. Conversely, Ann Arbor, Michigan-based May Mobility recently launched a transit service in Sun City, Arizona, using self-driving Toyota Sienna minivans with no backup driver aboard after successful testing.

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.

For those incapable of driving due to age or disabilities or without access to conventional methods of public transportation, self-driving taxis and other transit vehicles are seen as a way to provide mobility to get to errands, work or medical appointments. Commercial operators see self-driving vehicles as boosting cost-savings and efficiency because they can run for longer hours without having to stop for meals or breaks, and they require fewer employees.

Cars and trucks with self-driving safety technology called automated driver assistance systems, or ADAS, are already reducing traffic congestion and accidents. A report by the National High Traffic Safety Administration notes ADAS helps reduce traffic accidents because they “assist a driver by anticipating imminent dangers and working to avoid them.”

The combination of reducing traffic jams due to accidents and potentially decreasing the number of vehicles on the road when self-driving transit becomes more prevalent provides promising environmental benefits. A University of Michigan study concluded that when “savings from the driving efficiencies associated with self-driving vehicles are factored into the equation, the net result is a reduction in lifetime energy use and associated greenhouse gas emissions of up to 9% compared to the conventional vehicles.”

The notion of widely available fully autonomous cars relieving travelers from any of the duties and stresses of driving remains fraught with challenges that range from cost to safety concerns. No matter how well any of the technology works, none of it so far emulates human thought, logic or instincts to make split second decisions.

However, taking the human element out of the equation also eliminates distractions or emotions from affecting the vehicle’s operation. For that reason, fully self-driving cars are viewed as potentially safer since the technology is designed to operate the vehicle safely and logically by detecting and reacting to traffic conditions and the route it’s programmed to follow.

That brings up a question of ethics . Since self-driving cars are basically robots programmed to react a certain way in a given situation, they cannot make an ethical decision, for instance, to avoid a collision. Should the car take action to prevent it from striking a person or a group of people? Germany passed a law prioritizing saving human lives over animals.

Serious accidents such as those in California and Arizona have contributed to fear and concern on the part of many communities that would just as soon not have driverless vehicles plying their streets.

Other challenges to wider adoption of self-driving cars include weather, where sensors and road markings could be obscured by snow, sleet or a hard rain. Overall cost remains a major obstacle to private ownership of fully automated vehicles as well. A 2023 study by McKinsey and Company predicts “By 2030, 12% of new passenger cars are sold with L3+ autonomous technologies, and 37 percent have advanced AD technologies in 2035.”

GM's Super Cruise system can temporarily take over driving on certain roads and during certain ... [+] conditions. The service is offered on a subscription basis.

Right now the highest level of automation available to consumers are systems such as GM’s Super Cruise, Ford Motor F Co.’s BlueCruise and Tesla’s TSLA Full Self Driving—all Level 2. With those systems a driver can temporarily engage the systems to operate the car under certain conditions.

There are several companies building or operating self-driving vehicles for commercial deliveries and robo transit services.

Waymo operates robotaxi service in several U.S. markets.

One of the most successful is Waymo . It operates robotaxi service in San Francisco, Metro Phoenix, and is ramping up in Los Angeles and Austin, Texas. As noted above, GM’s Cruise unit has been less successful after a series of traffic accidents. Gatik operates autonomous trucks that deliver goods from distribution points to retail locations, while Kodiak Robotics adds its autonomous technology to semi-trucks running long-haul and local routes for such companies as Kroger KR and Ikea. Swedish tech company Einride’s autonomous electric pods deliver goods in Europe and North America. Pods are driven by remote operators and have no cabs for human drivers.

Consumer appetite for leaving the driving to technology is growing and they’re willing to pay for it, leading automakers to boost ADAS and other automation offerings, perhaps paving the way for fully self-driving cars and trucks to one day be available and affordable for individuals.

Based on consumer interest in automated driving features and commercial solutions available on the market today, in its report, McKinsey predicted ADAS and AD could generate between $300 billion and $400 billion in the passenger car market by 2035.

Indeed, the world will likely be affected in five key ways, according to artificial intelligence company Allerin: fewer traffic accidents, reduced car ownership, automated logistics including deliveries, improved livability due less noise and air pollution from fewer vehicles on the road and no parking or traffic tickets since autonomous vehicles can pick up and drop off passengers then go on their way.

It’s not certain if all cars will eventually operate without a human behind the wheel and at least partially in control. According to McKinsey, any transition will be at a snail’s pace, projecting that in 2030, only 4% of new passenger cars sold will be installed with level 3 or higher automation functions, increasing to just 17% in 2035.

Bottom Line

Don’t discard your favorite driving cap yet. While automakers are rapidly offering more sophisticated automated driver assist technologies, full, self-driving vehicles are likely to remain primarily in the realm of fleets and commercial operators for the foreseeable future.

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Mastering IELTS Writing Task 2: Sample Essays on Self-Driving Cars with Band-Specific Analysis

Self-driving cars have become a hot topic in recent years, and this subject has made its way into IELTS Writing Task 2 prompts. Based on our analysis of past IELTS exams and trends, we predict …

Written by: IELTS Mentor

Published on: October 3, 2024

Let’s examine a relevant IELTS Writing Task 2 question that has appeared in recent exams:

Some people believe that the development of self-driving cars will have more advantages than disadvantages. To what extent do you agree or disagree?

Table of Contents

Analysis of the Question

This question asks you to express your opinion on whether the advantages of self-driving cars outweigh their disadvantages. It’s crucial to:

• Clearly state your position in the introduction
• Discuss both advantages and disadvantages
• Provide relevant examples and explanations
• Conclude by restating your opinion

Now, let’s look at sample essays for different band scores, starting with a high band score (Band 8-9) response.

Sample Essay 1 (Band 8-9)

The advent of self-driving cars represents a significant leap in automotive technology, promising to revolutionize transportation. While some argue that the benefits of this innovation far outweigh any potential drawbacks, I believe that the advantages and disadvantages are more evenly balanced, requiring careful consideration.

On the positive side, autonomous vehicles have the potential to dramatically improve road safety. Human error is a leading cause of traffic accidents , and by removing the human element from driving, we could see a substantial reduction in collisions and fatalities. Additionally, self-driving cars could enhance mobility for those unable to drive, such as the elderly or disabled, providing them with newfound independence. Furthermore, these vehicles could optimize traffic flow, reducing congestion and, consequently, lowering emissions and improving air quality in urban areas.

However, the widespread adoption of self-driving cars is not without its challenges. One significant concern is the potential loss of jobs in the transportation sector. Taxi drivers, truck drivers, and other professionals whose livelihoods depend on operating vehicles could face unemployment , leading to economic disruption and social unrest. Moreover, there are complex ethical considerations, such as how autonomous vehicles should be programmed to respond in unavoidable accident scenarios. These ethical dilemmas raise questions about responsibility and liability that are not easily resolved.

Another crucial aspect to consider is the vulnerability of self-driving cars to hacking and cyber-attacks. As these vehicles rely heavily on computer systems and networks, they could become targets for malicious actors, potentially compromising passenger safety and privacy on a large scale.

In conclusion, while self-driving cars offer promising benefits in terms of safety, accessibility, and environmental impact, they also present significant challenges related to employment, ethics, and cybersecurity. As this technology continues to evolve, it is essential to address these concerns comprehensively to ensure that the advantages truly outweigh the disadvantages. Ultimately, the success of autonomous vehicles will depend on our ability to navigate these complex issues and create robust frameworks for their integration into society.

(Word count: 320)

Advantages and disadvantages of self-driving cars

Essay Analysis (Band 8-9)

This essay demonstrates excellence in several key areas:

Task Achievement : The essay fully addresses all parts of the task, presenting a clear position and discussing both advantages and disadvantages.

Coherence and Cohesion : The ideas are logically organized with clear progression throughout the essay. Paragraphs are well-linked, and cohesive devices are used effectively.

Lexical Resource : The essay uses a wide range of vocabulary with very natural and sophisticated control of lexical features. Examples include “advent,” “revolutionize,” “autonomous vehicles,” and “ethical dilemmas.”

Grammatical Range and Accuracy : The essay displays a wide range of structures with full flexibility and accuracy. Complex structures are used confidently.

Development of Ideas : Each main point is well-developed with relevant examples and explanations.

Now, let’s examine a sample essay for a Band 6-7 score.

Sample Essay 2 (Band 6-7)

In recent years, self-driving cars have become a topic of great interest. Some people think that these cars will bring more benefits than problems. I partially agree with this view because while there are significant advantages, we cannot ignore the potential drawbacks.

One of the main advantages of self-driving cars is improved safety on the roads. Many accidents are caused by human mistakes , like driving when tired or using phones while driving. Self-driving cars don’t get distracted or tired, so they could reduce the number of accidents. Another benefit is that these cars could help elderly or disabled people who can’t drive themselves. This would give them more independence and improve their quality of life.

However, there are also some disadvantages to consider. One big problem is that many people might lose their jobs. Taxi drivers and truck drivers could become unemployed if we use self-driving cars everywhere. This could cause economic problems for many families. Another issue is that these cars rely on complex technology, which could be hacked by criminals. This raises concerns about the safety and privacy of passengers.

In addition, self-driving cars might be very expensive at first, so only rich people could afford them. This could create more inequality in society. There are also questions about who is responsible if a self-driving car causes an accident. Is it the car manufacturer, the software developer, or the owner? These legal issues need to be solved before self-driving cars can be widely used.

In conclusion, while self-driving cars offer important benefits like improved safety and mobility, they also present challenges such as job losses and security concerns. I believe that the advantages slightly outweigh the disadvantages, but it’s important to address the problems carefully as this technology develops.

(Word count: 295)

Essay Analysis (Band 6-7)

This essay demonstrates good control of language and addresses the task, but with some limitations:

Task Achievement : The essay addresses the task and presents a clear position, but the discussion of advantages and disadvantages could be more balanced and in-depth.

Coherence and Cohesion : The essay is generally well-organized, but some transitions between ideas could be smoother.

Lexical Resource : There is a good range of vocabulary, but it lacks the sophistication seen in higher band scores. Some attempts at less common vocabulary are made.

Grammatical Range and Accuracy : The essay uses a mix of simple and complex sentence structures with generally good control, though there are occasional errors.

Development of Ideas : Ideas are relevant and supported, but some points could be elaborated further.

Self-driving car technology illustration

Key Vocabulary

Here are some important vocabulary items from the essays, along with their definitions and pronunciations:

• Advent (noun) /ˈædvent/ – The arrival of a notable person, thing, or event
• Autonomous (adjective) /ɔːˈtɒnəməs/ – Acting independently or having the freedom to do so
• Mobility (noun) /məʊˈbɪləti/ – The ability to move or be moved freely and easily
• Optimize (verb) /ˈɒptɪmaɪz/ – Make the best or most effective use of (a situation or resource)
• Ethical (adjective) /ˈeθɪkl/ – Relating to moral principles or the branch of knowledge dealing with these
• Dilemma (noun) /dɪˈlemə/ – A situation in which a difficult choice has to be made between two or more alternatives
• Vulnerability (noun) /ˌvʌlnərəˈbɪləti/ – The quality or state of being exposed to the possibility of being attacked or harmed
• Cybersecurity (noun) /ˌsaɪbəsɪˈkjʊərəti/ – The state of being protected against the criminal or unauthorized use of electronic data

These vocabulary items can help you express complex ideas related to technology and its societal impacts in your IELTS Writing Task 2 essays.

The topic of self-driving cars is likely to remain relevant in IELTS Writing Task 2 questions due to its global significance and the ongoing debate surrounding autonomous vehicles. To prepare for such questions, consider practicing with similar prompts, such as:

• Discuss the potential impact of self-driving cars on urban planning and infrastructure.
• Some people believe that self-driving cars should be mandatory once the technology is proven safe. Do you agree or disagree?
• How might the widespread adoption of self-driving cars affect the environment and energy consumption?

Remember to analyze the question carefully, plan your response, and use a range of vocabulary and grammatical structures in your essay. Feel free to practice writing an essay on the topic discussed in this article and share it in the comments section for feedback and discussion. This active practice is an excellent way to improve your IELTS Writing skills.

Impact of automation on job creation is another related topic that you might find interesting to explore as you prepare for your IELTS Writing Task 2. Understanding the broader implications of technological advancements can help you develop more nuanced arguments in your essays.

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Ielts writing task 2: expert guide on plant-based diets and environmental impact with sample essays for bands 6-9, ielts writing task 2: model essays on renewable energy’s role in reducing global carbon emissions (band 6-9).

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This self-driving Cruise robotaxi got stuck at a crossroads in San Francisco in 2019, inconveniencing pedestrians.

In 2016, just weeks before the Autopilot in his Tesla drove Joshua Brown to his death , I pleaded with the U.S. Senate Committee on Commerce, Science, and Transportation to regulate the use of artificial intelligence in vehicles. Neither my pleading nor Brown’s death could stir the government to action.

Since then, automotive AI in the United States has been linked to at least 25 confirmed deaths and to hundreds of injuries and instances of property damage.

The lack of technical comprehension across industry and government is appalling. People do not understand that the AI that runs vehicles—both the cars that operate in actual self-driving modes and the much larger number of cars offering advanced driving assistance systems (ADAS)—are based on the same principles as ChatGPT and other large language models (LLMs). These systems control a car’s lateral and longitudinal position—to change lanes, brake, and accelerate—without waiting for orders to come from the person sitting behind the wheel.

Both kinds of AI use statistical reasoning to guess what the next word or phrase or steering input should be, heavily weighting the calculation with recently used words or actions. Go to your Google search window and type in “now is the time” and you will get the result “now is the time for all good men.” And when your car detects an object on the road ahead, even if it’s just a shadow, watch the car’s self-driving module suddenly brake.

Neither the AI in LLMs nor the one in autonomous cars can “understand” the situation, the context, or any unobserved factors that a person would consider in a similar situation. The difference is that while a language model may give you nonsense, a self-driving car can kill you.

In late 2021, despite receiving threats to my physical safety for daring to speak truth about the dangers of AI in vehicles, I agreed to work with the U.S. National Highway Traffic Safety Administration (NHTSA) as the senior safety advisor. What qualified me for the job was a doctorate focused on the design of joint human-automated systems and 20 years of designing and testing unmanned systems, including some that are now used in the military, mining, and medicine.

My time at NHTSA gave me a ringside view of how real-world applications of transportation AI are or are not working. It also showed me the intrinsic problems of regulation, especially in our current divisive political landscape. My deep dive has helped me to formulate five practical insights. I believe they can serve as a guide to industry and to the agencies that regulate them.

1. Human errors in operation get replaced by human errors in coding

Proponents of autonomous vehicles routinely assert that the sooner we get rid of drivers, the safer we will all be on roads. They cite the NHTSA statistic that 94 percent of accidents are caused by human drivers. But this statistic is taken out of context and inaccurate. As the NHTSA itself noted in that report, the driver’s error was “the last event in the crash causal chain…. It is not intended to be interpreted as the cause of the crash.” In other words, there were many other possible causes as well, such as poor lighting and bad road design.

Moreover, the claim that autonomous cars will be safer than those driven by humans ignores what anyone who has ever worked in software development knows all too well: that software code is incredibly error-prone, and the problem only grows as the systems become more complex.

While a language model may give you nonsense, a self-driving car can kill you.

Consider these recent crashes in which faulty software was to blame. There was the October 2021 crash of a Pony.ai driverless car into a sign, the April 2022 crash of a TuSimple tractor trailer into a concrete barrier, the June 2022 crash of a Cruise robotaxi that suddenly stopped while making a left turn, and the March 2023 crash of another Cruise car that rear-ended a bus .

These and many other episodes make clear that AI has not ended the role of human error in road accidents. That role has merely shifted from the end of a chain of events to the beginning—to the coding of the AI itself. Because such errors are latent, they are far harder to mitigate. Testing, both in simulation but predominantly in the real world, is the key to reducing the chance of such errors, especially in safety-critical systems. However, without sufficient government regulation and clear industry standards, autonomous-vehicle companies will cut corners in order to get their products to market quickly.

2. AI failure modes are hard to predict

A large language model guesses which words and phrases are coming next by consulting an archive assembled during training from preexisting data. A self-driving module interprets the scene and decides how to get around obstacles by making similar guesses, based on a database of labeled images—this is a car, this is a pedestrian, this is a tree—also provided during training. But not every possibility can be modeled, and so the myriad failure modes are extremely hard to predict. All things being equal, a self-driving car can behave very differently on the same stretch of road at different times of the day, possibly due to varying sun angles. And anyone who has experimented with an LLM and changed just the order of words in a prompt will immediately see a difference in the system’s replies.

One failure mode not previously anticipated is phantom braking. For no obvious reason, a self-driving car will suddenly brake hard, perhaps causing a rear-end collision with the vehicle just behind it and other vehicles further back. Phantom braking has been seen in the self-driving cars of many different manufacturers and in ADAS-equipped cars as well.

Ross Gerber, behind the wheel, and Dan O’Dowd, riding shotgun, watch as a Tesla Model S, running Full Self-Driving software, blows past a stop sign.

THE DAWN PROJECT

The cause of such events is still a mystery. Experts initially attributed it to human drivers following the self-driving car too closely (often accompanying their assessments by citing the misleading 94 percent statistic about driver error). However, an increasing number of these crashes have been reported to NHTSA. In May 2022, for instance, the NHTSA sent a letter to Tesla noting that the agency had received 758 complaints about phantom braking in Model 3 and Y cars. This past May, the German publication Handelsblatt reported on 1,500 complaints of braking issues with Tesla vehicles, as well as 2,400 complaints of sudden acceleration. It now appears that self-driving cars experience roughly twice the rate of rear-end collisions as do cars driven by people.

Clearly, AI is not performing as it should. Moreover, this is not just one company’s problem—all car companies that are leveraging computer vision and AI are susceptible to this problem.

As other kinds of AI begin to infiltrate society, it is imperative for standards bodies and regulators to understand that AI failure modes will not follow a predictable path. They should also be wary of the car companies’ propensity to excuse away bad tech behavior and to blame humans for abuse or misuse of the AI.

3. Probabilistic estimates do not approximate judgment under uncertainty

Ten years ago, there was significant hand-wringing over the rise of IBM’s AI-based Watson, a precursor to today’s LLMs. People feared AI would very soon cause massive job losses, especially in the medical field. Meanwhile, some AI experts said we should stop training radiologists .

These fears didn’t materialize . While Watson could be good at making guesses, it had no real knowledge, especially when it came to making judgments under uncertainty and deciding on an action based on imperfect information. Today’s LLMs are no different: The underlying models simply cannot cope with a lack of information and do not have the ability to assess whether their estimates are even good enough in this context.

These problems are routinely seen in the self-driving world. The June 2022 accident involving a Cruise robotaxi happened when the car decided to make an aggressive left turn between two cars. As the car safety expert Michael Woon detailed in a report on the accident , the car correctly chose a feasible path, but then halfway through the turn, it slammed on its brakes and stopped in the middle of the intersection. It had guessed that an oncoming car in the right lane was going to turn, even though a turn was not physically possible at the speed the car was traveling. The uncertainty confused the Cruise, and it made the worst possible decision. The oncoming car, a Prius, was not turning, and it plowed into the Cruise, injuring passengers in both cars.

Cruise vehicles have also had many problematic interactions with first responders, who by default operate in areas of significant uncertainty. These encounters have included Cruise cars traveling through active firefighting and rescue scenes and driving over downed power lines . In one incident, a firefighter had to knock the window out of the Cruise car to remove it from the scene. Waymo, Cruise’s main rival in the robotaxi business, has experienced similar problems .

These incidents show that even though neural networks may classify a lot of images and propose a set of actions that work in common settings, they nonetheless struggle to perform even basic operations when the world does not match their training data. The same will be true for LLMs and other forms of generative AI . What these systems lack is judgment in the face of uncertainty, a key precursor to real knowledge.

4. Maintaining AI is just as important as creating AI

Because neural networks can only be effective if they are trained on significant amounts of relevant data, the quality of the data is paramount. But such training is not a one-and-done scenario: Models cannot be trained and then sent off to perform well forever after. In dynamic settings like driving, models must be constantly updated to reflect new types of cars, bikes, and scooters, construction zones, traffic patterns, and so on.

In the March 2023 accident, in which a Cruise car hit the back of an articulated bus, experts were surprised, as many believed such accidents were nearly impossible for a system that carries lidar, radar, and computer vision. Cruise attributed the accident to a faulty model that had guessed where the back of the bus would be based on the dimensions of a normal bus; additionally, the model rejected the lidar data that correctly detected the bus.

Software code is incredibly error-prone, and the problem only grows as the systems become more complex.

This example highlights the importance of maintaining the currency of AI models . “Model drift” is a known problem in AI, and it occurs when relationships between input and output data change over time. For example, if a self-driving car fleet operates in one city with one kind of bus, and then the fleet moves to another city with different bus types, the underlying model of bus detection will likely drift, which could lead to serious consequences.

Such drift affects AI working not only in transportation but in any field where new results continually change our understanding of the world. This means that large language models can’t learn a new phenomenon until it has lost the edge of its novelty and is appearing often enough to be incorporated into the dataset. Maintaining model currency is just one of many ways that AI requires periodic maintenance , and any discussion of AI regulation in the future must address this critical aspect.

5. AI has system-level implications that can’t be ignored

Self-driving cars have been designed to stop cold the moment they can no longer reason and no longer resolve uncertainty. This is an important safety feature. But as Cruise, Tesla, and Waymo have demonstrated, managing such stops poses an unexpected challenge.

A stopped car can block roads and intersections, sometimes for hours, throttling traffic and keeping out first-response vehicles. Companies have instituted remote-monitoring centers and rapid-action teams to mitigate such congestion and confusion, but at least in San Francisco, where hundreds of self-driving cars are on the road , city officials have questioned the quality of their responses.

Self-driving cars rely on wireless connectivity to maintain their road awareness, but what happens when that connectivity drops? One driver found out the hard way when his car became entrapped in a knot of 20 Cruise vehicles that had lost connection to the remote-operations center and caused a massive traffic jam.

Of course, any new technology may be expected to suffer from growing pains, but if these pains become serious enough, they will erode public trust and support. Sentiment towards self-driving cars used to be optimistic in tech-friendly San Francisco, but now it has taken a negative turn due to the sheer volume of problems the city is experiencing. Such sentiments may eventually lead to public rejection of the technology if a stopped autonomous vehicle causes the death of a person who was prevented from getting to the hospital in time.

So what does the experience of self-driving cars say about regulating AI more generally? Companies not only need to ensure they understand the broader systems-level implications of AI, they also need oversight—they should not be left to police themselves. Regulatory agencies must work to define reasonable operating boundaries for systems that use AI and issue permits and regulations accordingly. When the use of AI presents clear safety risks, agencies should not defer to industry for solutions and should be proactive in setting limits.

AI still has a long way to go in cars and trucks. I’m not calling for a ban on autonomous vehicles. There are clear advantages to using AI, and it is irresponsible for people to call on a ban, or even a pause, on AI. But we need more government oversight to prevent the taking of unnecessary risks.

And yet the regulation of AI in vehicles isn’t happening yet. That can be blamed in part on industry overclaims and pressure, but also on a lack of capability on the part of regulators. The European Union has been more proactive about regulating artificial intelligence in general and in self-driving cars particularly. In the United States, we simply do not have enough people in federal and state departments of transportation that understand the technology deeply enough to advocate effectively for balanced public policies and regulations. The same is true for other types of AI.

This is not any one administration’s problem. Not only does AI cut across party lines, it cuts across all agencies and at all levels of government. The Department of Defense, Department of Homeland Security, and other government bodies all suffer from a workforce that does not have the technical competence needed to effectively oversee advanced technologies, especially rapidly evolving AI.

To engage in effective discussion about the regulation of AI, everyone at the table needs to have technical competence in AI. Right now, these discussions are greatly influenced by industry (which has a clear conflict of interest) or Chicken Littles who claim machines have achieved the ability to outsmart humans. Until government agencies have people with the skills to understand the critical strengths and weaknesses of AI, conversations about regulation will see very little meaningful progress.

Recruiting such people can be easily done. Improve pay and bonus structures, embed government personnel in university labs, reward professors for serving in the government, provide advanced certificate and degree programs in AI for all levels of government personnel, and offer scholarships for undergraduates who agree to serve in the government for a few years after graduation. Moreover, to better educate the public, college classes that teach AI topics should be free.

We need less hysteria and more education so that people can understand the promises but also the realities of AI.

• Understanding the Risks Associated With AI ›
• Too Perilous For AI? EU Proposes Risk-Based Rules ›
• Deep Learning Makes Driverless Cars Better at Spotting Pedestrians ›
• Toyota's Gill Pratt on Self-Driving Cars and the Reality of Full Autonomy ›
• Fear’s Neural Hallmarks Make AI Drive More Safely - IEEE Spectrum ›
• AI Self-Recognition Creates Chances for New Security Risks - IEEE Spectrum ›
• Cruising Toward Self-Driving Cars: Standards and Testing Will Help ... ›
• The future of autonomous vehicles (AV) | McKinsey ›
• Automated Vehicle Safety | NHTSA ›

Mary (Missy) L. Cummings , a senior member of IEEE, is a professor in the Department of Electrical and Computer Engineering and the Department of Computer Science, Duke Institute for Brain Sciences (DIBS), Duke University. As a specialist in systems automation and the way that people use it, she recently served as a safety consultant for the National Highway Traffic Safety Administration.

Despite the

fact that autonomous transport largely solves the problem of a driver’s inattention on the road, we, alas, cannot talk about his complete safety. Below you can see the most common AI risks for self-driving cars and the whole automotive industry.

Secure AI Awareness

Secure AI Assessment

Secure AI Assurance

One possible early solution, is to implement diverse redundant control systems, where both/all the systems are compared for the quality of resolution, or the ‘second’ system is constantly evaluating the performance of the first - to provide a safety net of options when the primary algorithm is deadlocked or the conclusion unresolved.

Not a perfect answer, but an order of magnitude better than depending on a single actor to make every decision.

To be able to understand commercial technology the legacy is important. Thus, GUI based Operating System Microsoft Windows crashed on it's introduction video. It is nearly exactly like that.

Because the code is so huge, because the front-end seems so intuitive, we falter at the need for post-launch pruning and hurry. There were jokes in Urdu of a man losing millions because his mobile phone/handy did not get network in Pakistan around the time Nokia 6600 was introducing SEAsia to digital media on phone MMCards. In Hindi highways people are seen stalking trucks nowadays. Don'tGoogle :)

A Picture Is Worth 4.6 Terabits

Gandhi inspired a new kind of engineering, google is now watermarking its ai-generated text.

Self Driving Cars: All You Need to Know

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Research on Self-driving Cars

How it works

I am doing my research on self-driving cars. A self-driving is basically just a car that drives itself. It is a car or truck in which human drivers are never required to take control to safely operate the vehicle. Also known as autonomous or “”driverless”” cars, they combine sensors and software to control, navigate, and drive the vehicle. You might ask, well who developed or invented this car? Well, German engineers led by scientist Ernst Dickmaans developed it. Decades before Google, Tesla, and Uber got into the self-driving car business, a team of German engineers led by a scientist named Ernst Dickmaans had developed a car that could navigate French commuter traffic of its own.

You might also ask, well when did this happen? Or when was this car developed? This car was developed in the 1980s. Not that many people know this, but back in the 1980s and 1990s, there was a car company, Mercedes-Benz, was already doing experiments with driverless cars that could accelerate, brake, steer, and basically make a trip through traffic by themselves and not crash into anyone. Another question you might have might be, where did this take place at? Well, it took place in HOFOLDING, Germany. Another key that leads to it taking place in Germany is that Ernst Dickmaans was actually German.

The group of engineers he worked with were also German. “”Ernst Dickmaans is a German pioneer of dynamic computer vision and of driverless cars.”” You might ask, well why did he do this? The answer is, he wanted to create a car that was “”equipped with the necessary sensors, processors, and outputs to theoretically drive themselves through typical traffic without special external inputs.”” Also, he was approached by Daimler-Benz who wanted to collaborate on the project in celebration of the 100 year anniversary of the Benz first car which was the Benz Motorwagen in 1886. Moving into their second century of car manufacturing, Daimler-Benz proposed a large-scale research project to develop new technologies-one of which was autonomous driving. You might also ask, how was it done? Or how does the car work? Well, “”The van was able to process visual input from

Isabella Bryant 7th Period 12/18/18 cameras and provide commands to the steering wheel, throttle, and brakes, driving at speeds up to 96 km/h. This was achieved using innovative “”4D Vision”” techniques, which involved extracting edges from an image and analyzing them while taking into account the time delay.”” Ernst and his group at University Bundeswehr Munich built the world’s first real “”robot”” car using saccadic vision, probabilistic approaches such as Kalman filters and parallel computer.

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Essay Samples on Self Driving Cars

Are driverless cars a good idea: weighing the pros and cons.

In recent years, the prospect of driverless cars has captured the imagination of both technology enthusiasts and skeptics alike. The idea of vehicles navigating roads without human intervention presents a future that is both exciting and uncertain. While the concept promises increased safety and efficiency,...

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Self-Driving Cars: Pros and Cons of the Advanced Technology

Imagine that we may be the last generation to own cars, and the new generation may never have to learn to drive a car. They never have to worry about driving anymore because there is a car that can drive itself. A self-driving car is...

Pros and Cons of Self Driving Cars and Its Sufficiency

A self-driving vehicle, otherwise called a self-sufficient vehicle, associated and self-sufficient vehicle, driverless vehicle, robocar or mechanical vehicle, is a vehicle that is equipped for detecting its condition and moving securely with practically zero human info. Self-driving vehicles consolidate an assortment of sensors to see...

The Development Of Self Driving Cars

Throughout the world, there are new technology being developed. Technology is becoming more advanced before our eyes. For example, a new technology that is taking everything by a storm is the self driving cars. The concept of having self driving is mesmerizing to people. Having...

Self Driving Cars: A Gamechanger In The Industry

Nowadays, the self-driving car is a massive issue in our society that we are living in, and people get more and more interested as the self-driving car market gets bigger and bigger. So what exactly are self-driving cars? A self-driving car is a vehicle that...

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Self Driving Cars And How They Can Change Transportation

It has long been anticipated that autonomous vehicles would emerge into the transportation industry. With technology advancing as rapidly as it is today, it is difficult to ignore the reality that artificial intelligence and automation is beginning to take over. Some self driving car manufacturers...

The Invention Of Self Driving Cars

The computing innovation that is based on my computational artifact that I chose was self driving cars. The computational artifact that I chose is based on the innovation of self driving cars. Self driving cars are vehicles that can drive safely by themselves with little...

Best topics on Self Driving Cars

1. Are Driverless Cars a Good Idea: Weighing the Pros and Cons

2. Self-Driving Cars: Pros and Cons of the Advanced Technology

3. Pros and Cons of Self Driving Cars and Its Sufficiency

4. The Development Of Self Driving Cars

5. Self Driving Cars: A Gamechanger In The Industry

6. Self Driving Cars And How They Can Change Transportation

7. The Invention Of Self Driving Cars

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Self-Driving Cars Pros And Cons: Navigating The Future Of Transportation

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Self-driving cars may have seemed like a myth a decade ago. Still, a few manufacturers have already reached Level 3 autonomous driving, which is more than halfway toward the goal of building actual autonomous vehicles. Honda did it first with the Honda Legend Hybrid EX, which is the Japanese version of the Acura TLX .

If you're unfamiliar with the rating system, a globally accepted standard goes up to Level 5, where the driver is no longer required. Car technology is evolving rapidly, especially in the electric segment.

But before we get to that, we must first understand what self-driving cars are.

Why Do They Matter?

Fossil fuels are quickly becoming a thing of the past, and one day the human driver will likely follow. You might think it's a pipe dream, but a whole new generation of people have no interest in car ownership. They see autonomous cars as a huge win because they will be the most efficient transportation. These people want to sit back and be passengers. The current car-buying public can't stomach the idea of self-driving technology taking away what has become one of the ultimate ways of expressing freedom. But those opinions are rapidly dwindling, and their benefits are hard to ignore.

Automated driving systems are the next big step forward, so we need to know both the pros and cons of driverless cars.

Self-Driving Cars

Self-driving vehicles go by many names, but this one has become the most popular because of Tesla, even though the American automaker has been called out many times for using the term without having the technology to live up to the name. Other standard terms are autonomous vehicles, driverless cars, and automated cars.

We prefer automated vehicles as opposed to autonomous vehicles. We make this distinction purely because the autonomous vehicle does not exist yet. Autonomy suggests an artificial intelligence capable of learning and adapting. Automated cars respond to a situation using only man-made programming. This programming can be updated over time, but at the end of the day, a so-called autonomous vehicle (as they're mostly known) can only do what a line of code tells it to do. A prime example is the advanced driver assist feature known as automatic braking.

While it may appear as if the car is self-driving, it's just code. The vehicle goes through a series of yes or no questions within the blink of an eye. Is there a pedestrian in front of the car? Yes. Is the human behind the wheel paying attention? No. Will one or more pedestrians get hurt if the brakes aren't applied right now? Yes. And then it applies the brakes.

Cars with these advanced driving features are Level 2. These systems are responsible for a reduction in car crashes, but the driver still needs to be in charge of the vehicle at all times.

As mentioned, Level 3 is the highest we've gone so far; even so, it's just a higher level of automation. The vehicle can monitor its surroundings and accelerate, brake, steer, and change lanes. In certain areas where the highway code allows, a driver can even remove their hands.

Level 4 is where we reach actual autonomy. This is when the car starts to think for itself, and it can analyze complex situations and work around them. Even so, a Level 4 self-driving car still needs a steering wheel so the driver can take over if the vehicle is flummoxed. Computers can only handle so much. For now, at least.

Up until now, we've been dealing with human-driven cars. Level 5 removes human error entirely. The vehicle doesn't need a steering wheel because it can do everything a human can without human error. When discussing human error , think of distracted driving, road rage, straying over speed limits, and losing control.

Only when automakers reach Level 5 can we rightfully start using terms like driverless, autonomous, and self-driving cars.

Since the technology does not yet exist, and human drivers are still going to be around for a while, the self-driving car's pros and cons we'll be exploring are all theoretical.

Self Driving Cars Pros And Cons

According to the NHTSA, one of the main pros of self-driving cars is safety. It says that more than 90% of traffic accidents are caused by human error , so if you remove us from the formula, there will, theoretically, be a decrease in road accidents and an overall increase in road safety.

Autonomous vehicles will also be more environmentally friendly, and these cars could potentially reduce emissions. How, exactly?

Well, once computers are in charge of transport, connected technology will significantly leap forward. Many automakers have proposed that self-driving vehicles could tap into the systems that regulate traffic.

Basically, a car will know at exactly what speed it needs to move to reduce congestion. Traffic flow will increase, and the fuel savings will be immense, whether a car is powered by fossil fuels or electricity. So, reducing emissions is one big plus for autonomous vehicles.

We're also looking at fewer accidents, most likely in urban areas. Without being connected to information, improved safety in rural areas remains in the air. We must wonder how these cars will handle narrow lanes or roads without clearly painted lines. If you've ever driven on UK roads, you'll be forgiven for thinking autonomous driving is a pipe dream.

The cons of self-driving cars are both clear and not. While they may make the roads safer, we have to mention potential job losses , security issues, and more severe vehicle crashes.

The job losses as a result of the driverless car will be severe. Taxi drivers will lose their jobs because taxi services will buy vehicles that don't need drivers. Cars don't get sick or need a holiday. Delivery services also won't require humans, and Uber drivers can kiss their jobs goodbye. Once self-driving vehicles are upscaled, bus drivers will lose their jobs because the people in charge of public transportation will come to the same conclusion. That's a lot of lost jobs across the world. The future seems bleak for everyone who makes a living from driving.

Autonomous technology also poses a security threat from multiple angles. We're sure automakers will use advanced security to prevent a car from getting hacked. However, as mentioned earlier, these cars are expected to connect to loads of external servers, possibly even other vehicles on the road. This may make them vulnerable .

Cars will also have more computers than ever, putting them at greater risk to hackers. And they'll likely get hold of your credit card information because once you have nothing to do in a car, you'll probably subscribe to some streaming service. We're already seeing the first examples of this coming through for people who are waiting while charging their electric vehicles.

In the pros section, we mentioned a reduction in crashes, but one of the most significant theoretical negatives of self-driving cars is an increase in the severity of impacts. Fewer cars mean less traffic, likely resulting in a higher top speed. If an autonomous car does crash, it will probably lose control at a higher speed. A higher speed means more damage to passengers.

But the biggest con is that all cars would need to be driverless. We can't have a scenario with a 50:50 split or even a case where most vehicles are autonomous. Even if we had just 1% human drivers, human error is still in play.

Self-driving systems can be as evolved as possible, but even they can't accurately predict what a drunk person might do.

Should We Be Afraid Of Driverless Cars?

As an entity, the car is too ingrained in society to be obliterated within 50 years. Driving is also a freedom people won't willingly give up. And looking at the job losses mentioned earlier, self-driving vehicles are pretty scary. Conversely, automated vehicles can improve our lives if manufacturers can get them to function correctly over a long period.

Currently, we can't see a future where driving is wholly eradicated. Therefore, we don't believe Level 5 will ever happen. The experts agree with us on this topic. At best, we'll have Level 4 to handle all the mundane tasks, while a driver can take over when the journey gets more interesting.

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Are We Ready for Self-Driving Cars? The AI Revolution on Our Roads

In an era where artificial intelligence (AI) is reshaping industries at an unprecedented pace, perhaps no sector stands to be more dramatically transformed than transportation. The convergence of AI and automotive technology has given birth to the autonomous vehicle revolution, promising to redefine our relationship with cars and the very fabric of our urban landscapes. As we stand on the brink of this transformative era, it's crucial to examine the current state of self-driving technology, its potential impacts, and the challenges that lie ahead.

The State of Autonomous Vehicle Technology

At the heart of every autonomous vehicle lies a sophisticated AI system that serves as its brain. This system relies on a complex interplay of various technologies:

1. Machine Learning and Deep Neural Networks : These form the core of the vehicle's decision-making capabilities. Through extensive training on millions of scenarios, these systems learn to recognize objects, predict movements, and make split-second decisions.

2. Computer Vision : Advanced cameras and sensors, coupled with AI algorithms, allow vehicles to "see" and interpret their surroundings in real-time. This includes recognizing traffic signs, pedestrians, other vehicles, and road conditions.

3. LiDAR (Light Detection and Ranging) : This technology uses laser light to measure distances and create detailed 3D maps of the vehicle's environment, crucial for navigation and obstacle avoidance.

4. Radar and Ultrasonic Sensors : These complement LiDAR and cameras, especially in adverse weather conditions or for close-range object detection.

5. GPS and Inertial Measurement Units (IMUs) : These provide precise location and movement data, essential for navigation and stability control.

6. Natural Language Processing (NLP) : This enables human-machine interaction, allowing passengers to communicate with their vehicles effortlessly.

7. Big Data Analytics : The massive amount of data collected by autonomous vehicles is processed and analyzed to continuously improve performance and safety.

Levels of Autonomy

The Society of Automotive Engineers (SAE) has defined six levels of driving automation, from 0 (fully manual) to 5 (fully autonomous):

Level 0 : No automation. The driver performs all tasks.

Level 1 : Driver assistance. The vehicle can assist with either steering or acceleration/deceleration.

Level 2 : Partial automation. The vehicle can control both steering and acceleration/deceleration, but the driver must remain engaged.

Level 3 : Conditional automation. The vehicle can manage most aspects of driving, but the driver must be ready to take control when prompted.

Level 4 : High automation. The vehicle can handle most driving situations independently, but may have limitations (e.g., geographic areas, weather conditions).

Level 5 : Full automation. The vehicle can handle all driving tasks under all conditions.

As of 2024, most commercially available systems operate at Level 2, with some companies testing Level 3 and 4 systems in limited scenarios.

Current Market Leaders

Several key players are pushing the boundaries of autonomous vehicle technology:

1. Waymo : Alphabet's self-driving car project, now an independent company, is considered a leader in the field. Their vehicles have driven millions of miles on public roads and are operating a limited commercial robotaxi service in Phoenix, Arizona.

2. Tesla : Known for its Autopilot and Full Self-Driving (FSD) systems, Tesla has been aggressively pushing over-the-air updates to improve its vehicles' autonomous capabilities.

3. GM Cruise : General Motors' self-driving division has been testing its vehicles extensively in San Francisco and aims to launch a commercial robotaxi service.

4. Argo AI : Backed by Ford and Volkswagen, Argo AI is developing a self-driving system for ride-sharing and goods delivery services.

5. Baidu : The Chinese tech giant has been making significant strides in autonomous driving technology, with its Apollo platform being used by various automakers.

These companies, along with traditional automakers and other tech firms, are investing billions in R&D to bring fully autonomous vehicles to market.

The Potential Impact of Autonomous Vehicles

Safety improvements.

One of the most compelling arguments for autonomous vehicles is their potential to dramatically improve road safety. According to the National Highway Traffic Safety Administration (NHTSA), 94% of serious crashes are due to human error. By removing human factors such as distraction, fatigue, and impairment, AI-driven vehicles have the potential to save thousands of lives annually.

A study by the Insurance Institute for Highway Safety suggests that if all vehicles on U.S. roads were equipped with just four key autonomous vehicle technologies (lane departure warning, forward collision warning, blind spot detection, and adaptive headlights), nearly a third of crashes and fatalities could be prevented.

Economic Impact

The autonomous vehicle industry is poised to create a significant economic ripple effect:

1. Job Creation : While there are concerns about job displacement in traditional driving roles, the AV industry is expected to create numerous high-skilled jobs in areas such as AI development, data analysis, and vehicle maintenance.

2. Productivity Gains : McKinsey & Company estimates that autonomous vehicles could free up as much as 50 minutes a day for users, who will be able to work or relax during their commutes.

3. Reduced Costs : The widespread adoption of AVs could lead to a decrease in insurance premiums and potentially reduce healthcare costs related to traffic accidents.

4. New Business Models : The rise of autonomous vehicles is likely to spur new industries and services, from entertainment systems for driverless cars to specialized AV maintenance and cleaning services.

Environmental Benefits

Autonomous vehicles have the potential to significantly reduce the environmental impact of transportation:

1. Improved Fuel Efficiency : AI-optimized routing and driving patterns could lead to more efficient fuel consumption.

2. Reduced Emissions : More efficient driving and the potential for increased adoption of electric autonomous vehicles could help lower greenhouse gas emissions.

3. Traffic Reduction : Autonomous vehicles could communicate with each other to optimize traffic flow, potentially reducing congestion and the associated environmental impacts.

Social Impact

The advent of autonomous vehicles could bring about significant social changes:

1. Increased Mobility : Self-driving cars could provide independence to those unable to drive, such as the elderly or disabled, improving their quality of life and access to services.

2. Changed Urban Landscapes : As the need for parking in city centers decreases, urban planners could repurpose this space for housing, green areas, or community facilities.

3. Shift in Car Ownership Models : The rise of autonomous ride-sharing services could lead to a decrease in personal car ownership, particularly in urban areas.

Challenges and the Road Ahead

Despite the promising outlook, several significant challenges remain on the path to widespread adoption of autonomous vehicles:

Technical Hurdles

1. Edge Cases : While AI systems excel at handling common driving scenarios, they still struggle with rare, unexpected situations that human drivers can often navigate intuitively.

2. Weather and Road Conditions : Autonomous vehicles must be able to operate safely in all weather conditions and on all types of roads, including those with poor markings or unusual layouts.

3. Sensor Limitations : Current sensor technologies can be affected by extreme weather conditions, potentially compromising the vehicle's ability to perceive its environment accurately.

Regulatory Challenges

The rapid advancement of autonomous vehicle technology has outpaced the development of comprehensive regulatory frameworks:

1. Liability Issues : Determining responsibility in the event of an accident involving an autonomous vehicle remains a complex legal question.

2. Testing and Certification : Governments need to establish standards for testing and certifying the safety of autonomous vehicles before they can be widely deployed.

3. Data Privacy : The vast amount of data collected by autonomous vehicles raises concerns about privacy and data ownership.

Cybersecurity Concerns

As vehicles become more connected and software-dependent, they also become more vulnerable to cyber attacks:

1. Hacking Risks : There are concerns about the potential for malicious actors to remotely take control of vehicles or cause accidents.

2. Data Protection : The sensitive data collected by autonomous vehicles must be protected from theft or misuse.

Ethical Dilemmas

The development of autonomous vehicles raises complex ethical questions:

1. Trolley Problem : How should a vehicle be programmed to react in unavoidable accident scenarios where it must choose between multiple harmful outcomes?

2. Algorithmic Bias : Ensuring that the AI systems driving these vehicles are free from biases that could lead to unfair or discriminatory decision-making.

Public Acceptance

Despite the potential benefits, public skepticism remains a significant hurdle:

1. Trust Issues : A 2022 survey by AAA found that only 22% of Americans feel manufacturers should produce self-driving vehicles, indicating a lack of public trust in the technology.

2. Control Concerns : Many people are uncomfortable with the idea of surrendering control of their vehicle to an AI system.

The Road Ahead

As we navigate the transition to autonomous vehicles, several key areas require focus:

1. Infrastructure Development : The creation of smart cities and integration of Internet of Things (IoT) technologies will be crucial for the effective operation of self-driving cars.

2. Data Sharing and Standardization : Encouraging collaboration and data sharing among companies and researchers could accelerate progress and improve safety across the industry.

3. Workforce Transition : As autonomous vehicles become more prevalent, there will be a need to retrain and transition workers in affected industries, such as professional drivers.

4. Public Education : Increasing public awareness and understanding of autonomous vehicle technology will be crucial for building trust and acceptance.

5. Ethical and Legal Frameworks : Clear guidelines for liability and decision-making in autonomous systems must be established to address the complex ethical and legal questions raised by this technology.

The autonomous vehicle revolution, driven by rapid advancements in AI, promises to reshape our transportation systems and urban landscapes in profound ways. While the potential benefits in terms of safety, efficiency, and accessibility are immense, significant technical, regulatory, and social challenges remain.

As we stand at this crossroads of innovation, it's clear that the future of transportation will be shaped not just by technological advancements, but also by how we as a society address these challenges. The journey toward fully autonomous roads is complex, but with continued research, thoughtful regulation, and public engagement, we can work towards a future where self-driving cars enhance safety, accessibility, and efficiency for all.

The coming years will be crucial in determining how quickly and smoothly we can navigate this transition. As AI continues to evolve and our vehicles become increasingly intelligent, one thing is certain: the way we think about transportation is set to change dramatically, ushering in a new era of mobility that was once the realm of science fiction.

About the Author

Sanjaikanth E Vadakkethil Somanathan Pillai is a Senior Member of IEEE and a Fellow of IET, with over 19 years of industry experience and an extensive research background in secure artificial intelligence, network security, and misinformation detection. He is currently pursuing his PhD in Computer Science at the University of North Dakota, USA, and has published more than 50 influential works in prominent journals and conferences, including those by IEEE. Sanjaikanth has contributed to groundbreaking advancements in mobile networks, privacy-preserving techniques, and location-based services (LBS). Additionally, his research has been adopted by leading institutions worldwide. In addition to his extensive professional and academic achievements, Sanjaikanth plays an active role in the academic community, serving on the editorial boards of prominent journals, such as the International Journal of Artificial Intelligence in Scientific Disciplines and the Information Resources Management Journal. He has also co-authored significant books like 'ChatGPT: Transforming Industries Through AI-Powered Innovation,' contributing to advancements in AI, IoT, and machine learning.

Company Designation : Staff Site Reliability Engineer, Visa Inc.

Location : Austin, Texas, USA

LinkedIn : https://www.linkedin.com/in/sanjai-kanth-012a6922/

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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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