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MIT Autonomous Vehicle Technology Study: Large-Scale Deep Learning Based Analysis of. Driver Behavior and Interaction with Automation. Munich Re Autonomous Vehicles. 3. AUTONOMOUS VEHICLES. Executive Summary. Since the early 's the insurance industry has been a major force. How will Autonomous Vehicles Affect the Nature of Vehicle Ownership? files/PolicyBrief_Autonomous_Vehicles_LQ_pdf.

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PDF | The field of autonomous automation is of interest to researchers, and much has This paper can help one understand the trends in autonomous vehicle. iv Autonomous Vehicle Technology: A Guide for Policymakers. This program is part of RAND Justice, Infrastructure, and Envi- ronment, a division of the RAND. This report explores autonomous (also called self-driving, driverless or robotic) reductions, will only be significant when autonomous vehicles.

Our mission is to help leaders in multiple sectors develop a deeper understanding of the global economy. Our flagship business publication has been defining and informing the senior-management agenda since Our learning programs help organizations accelerate growth by unlocking their people's potential. From driverless taxis to automated cargo trucks, autonomous vehicles AVs will change the nature of on-road driving and, in the process, revolutionize the automotive and mobility industries. Within this mix of opportunity and uncertainty, we believe AV players from components vendors to mobility service providers could earn trillions in revenues in China. McKinsey research suggests autonomous vehicles could, at some point, take over most of the automotive market in China.

Can You Trust Autonomous Vehicles : Contactless Attacks against Sensors of Self-driving Vehicle

Can self-driving cars still function as prostheses of male identity? Could autonomous automobility even degen- der the driver?

Pdf autonomous vehicle

Or will hegemonic masculinity merely be reconfigured in fu- ture mobility cultures? As history teaches us, gender stereotypes are highly flexible—but often this adaptability serves only to maintain the hierarchical gender relations.

Many scholars have explored the relationship between gender and auto- mobility over the years. Cultural historians have rendered the woman driver visible and made her an important part of automotive scholarship.

How might automa- tion affect the car as a symbol of masculinity? The self-driving car is already a feature of traffic on the roads of North America and Europe, though mostly in the form of a research vehicle, driven by engineers.

Whether autonomous cars will ever be designed for the pur- pose of mass transportation remains unclear. But the approach of our special section is to analyze representations of imagined futures—prototypes, media images, and popular discourses of driverless cars—in order to understand how global players are attempting to prefigure our mobile future.

We want to know whether the current media discourse genders or degenders the future user of an autonomous car. What kinds of images are used, what promises are made, and how is this discourse influenced by gendered norms? Do class and race interact with gender in the case of driverless cars? They give mobility scholars a means of accessing the contemporary imaginary of autonomous driving and perhaps of developing alternative narratives that may serve to weaken the hegemonic discourses.

We asked mobility studies scholars to think through these issues of gen- der reconfiguration from sociological and cultural perspectives. Their articles are centered around the assumption that automobility should be understood in the context of the intense emotions, passions, feelings, and desires it pro- vokes. Such responses are part of a gendered economy that ought to receive scholarly attention.

Pdf autonomous vehicle

Discursive Assertions of Mobility Futures. Manderscheid uses these layers to analyze two different visions of driverless automobility: the Google self-driving car—a project that started in and has been devel- oped since by the Google spinoff Waymo under the name Firefly—and the F concept car from Mercedes-Benz.

The Google car features a concept of autonomous driving that is short-range, shared, and inclusive: it includes nonhegemonic depictions of women, children, the elderly, and impaired people.

Autonomous Vehicles (AVs), Also Known as Self-Driving Cars

It contains a gender script that softens the masculine traits of the au- tomobile subject. The F promotes a long-range, more exclusive concept for the spatially detached and socially isolated business elite, based on the promise of a private space for the nomadic subject who depends on virtual mobility. With its detachment from any reproductive task, the gender script of this vision fits into the image of hegemonic masculinity.

Both narratives, therefore, reveal less about our future than about a contemporary social formation that is centered on present ideals of individualization, flexibilization, and mobilization of the subject. The two corporate visions constitute a discursive frame that serves to restrict the mul- tiple shapes driverless vehicles may take.

Other possible uses, such as autono- mous public transport, are excluded. Manderscheid concludes that gendered practices and subjectivities of mobility will not be subverted by driverless cars themselves.

Autonomous driving could be shaped by different social- technical scripts of future users in a way that cannot be anticipated today. For this reason, it is even more important to think of alternative modes of mobility that transcend the well-known norms of economic growth, traditional energy paradigms, and the hype of mobility as something desirable. The authors argue that autonomous driving can challenge the foundations of a gendered economy of pleasure and undermine the performance of masculinity that is based on risky and aggressive driving.

Autonomous trucks could lead to a demasculinization of very traditional fig- ures of working-class masculinity such as the truck driver. Typically feminized subject positions such as the car passenger could be accorded more value and associated with pleasure. The interior space of the vehicle could become a more social environment. The vehicles might still be anthropomor- phized, only this would occur beyond specific interpellative regimes based on masculinity, speed, risk taking, and calculation.

Nevertheless, this process is unlikely to take the form of degendering. The authors use a media ecological lens to analyze the gendered and racialized dimensions of two audiovisual concept car previews Nissan IDS and Volvo Concept 26 and the journalistic and aca- demic discourses surrounding them.

The Nissan clip features an autonomous vehicle that adopts traditionally femininized roles in domestic organization with subdued navigational control, suggesting an empowering partnership between its male owner and the machine. The Volvo preview depicts the in- terior design of a driverless car prototype, accompanied by comments from project representatives.

Both audiovisual previews place the white or honor- ary white male driver at the center of their narratives. They emphasize the active control and mastery exerted over the vehicle by the male user: even when he chooses to delegate the task of driving to the car, associations of pas- sivity are strictly avoided.

Masculinity remains actively bound to the mobile public space. The female body is delegated to the feminized passenger seat of the driverless car and remains associated with passivity, the domestic space, or the romantic partner.

Examining the representation of drivers in advertising, popular motoring magazines, games, and car-related TV shows, Redshaw argues that most of these popular imaginations of automobility are referring to combustion masculinity. The author sees this form of masculin- ity as the greatest obstacle to the introduction of autonomous cars. Another, rare form of hydraulic masculinity appears in a famous truck advertisement made by Volvo , which shows the actor Jean-Claude Van Damme doing the splits between two trucks in motion.

The second challenge is known as risk compensation: Semi-automated cars have been shown to suffer from this problem, for example with users of Tesla Autopilot ignoring the road and using electronic devices or other activities against the advice of the company that the car is not capable of being completely autonomous.

In the near future, pedestrians and bicyclists may travel in the street in a riskier fashion if they believe self-driving cars are capable of avoiding them. In order for people to download self-driving cars and vote for the government to allow them on roads, the technology must be trusted as safe.

Testing vehicles with varying degrees of automation can be done physically, in closed environments, [65] on public roads where permitted, typically with a license or permit [66] or adhering to a specific set of operating principles [67] or virtually, i. Apple is currently testing self-driven cars, and has increased the number of test vehicles from 3 to 27 in January , [71] and to 45 in March Russian internet-company Yandex started to develop self-driven cars in In February they tested the prototype of an unmanned taxi on the streets of Moscow.

On the territory of Innopolis they will operate two unmanned vehicles with five stops. Testing continued during the International Consumer Electronics Show CES 8—11 January [75] Yandex received permission from the Ministry of Transport of Israel to test a company's unmanned vehicle on public roads in One way to assess the progress of automated vehicles is to compute the average distance driven between "disengagements", when the automated system is turned off, typically by a human driver.

Waymo also traveled more distance in total than any other. Their rate of 0. In March , Uber reported an average of 0. Several companies are said to be testing automated technology in semi trucks. In , Anheuser-Busch Inc. No human action had involved in the driving process and the truck travelled miles.

Starsky Robotics became the first player in the self-driving truck game to drive in fully automated mode on a public road without a person in the cab. In Europe, truck platooning is being considered with the Safe Road Trains for the Environment approach. Lockheed Martin with funding from the U. Army developed an automated truck convoying system that uses a lead truck operated by a human driver with a number of trucks following autonomously. In Europe, cities in Belgium, France, Italy and the UK are planning to operate transport systems for automated cars, [87] [88] [89] and Germany, the Netherlands, and Spain have allowed public testing in traffic.

The experiments were planned to be extended to other cities such as Bordeaux and Strasbourg by In China, Baidu and King Long produce automated minibus, a vehicle with 14 seats, but without driving seat. With vehicles produced, will be the first year with commercial automated service in China. Those minibuses should be at level 4, that is driverless in closed roads. Driving safety experts predict that once driverless technology has been fully developed, traffic collisions and resulting deaths and injuries and costs , caused by human error , such as delayed reaction time , tailgating , rubbernecking , and other forms of distracted or aggressive driving should be substantially reduced.

According to motorist website "TheDrive. To help reduce the possibility of these confounding factors, some companies have begun to open-source parts of their driverless systems. Udacity for instance is developing an open-source software stack, [] and some companies are having similar approaches.

Automated cars could reduce labor costs ; [] [] relieve travelers from driving and navigation chores, thereby replacing behind-the-wheel commuting hours with more time for leisure or work; [99] [] and also would lift constraints on occupant ability to drive, distracted and texting while driving , intoxicated , prone to seizures , or otherwise impaired.

Large vehicles, such as motorhomes, would attain appreciably enhanced ease of use. Additional advantages could include higher speed limits ; [] smoother rides; [] and increased roadway capacity; and minimized traffic congestion , due to decreased need for safety gaps and higher speeds. These increases in highway capacity could have a significant impact in traffic congestion, particularly in urban areas, and even effectively end highway congestion in some places.

Safer driving is expected to reduce the costs of vehicle insurance. Vehicle automation can improve fuel economy of the car by optimizing the drive cycle. However, the improvement in vehicle energy efficiency does not necessarily translate to net reduction in energy consumption and positive environmental outcomes. It is expected that convenience of the automated vehicles encourages the consumers to travel more, and this induced demand may partially or fully offset the fuel efficiency improvement brought by automation.

This could dramatically reduce the need for parking space. Assuming the increased efficiency is not fully offset by increases in demand, more efficient traffic flow could free roadway space for other uses such as better support for pedestrians and cyclists. The vehicles' increased awareness could aid the police by reporting on illegal passenger behavior, while possibly enabling other crimes, such as deliberately crashing into another vehicle or a pedestrian. The future of passenger rail transport in the era of automated cars is not clear.

The sort of hoped-for potential benefits from increased vehicle automation described may be limited by foreseeable challenges, such as disputes over liability will each company operating a vehicle accept that they are its "driver" and thus responsible for what their car does, or will some try to project this liability onto others who are not in control?

Other obstacles could include de-skilling and lower levels of driver experience for dealing with potentially dangerous situations and anomalies, [] ethical problems where an automated vehicle's software is forced during an unavoidable crash to choose between multiple harmful courses of action 'the trolley problem ' , [] [] [] concerns about making large numbers of people currently employed as drivers unemployed at the same time as many other alternate blue collar occupations may be undermined by automation , the potential for more intrusive mass surveillance of location, association and travel as a result of police and intelligence agency access to large data sets generated by sensors and pattern-recognition AI making anonymous travel difficult , and possibly insufficient understanding of verbal sounds, gestures and non-verbal cues by police, other drivers or pedestrians.

A direct impact of widespread adoption of automated vehicles is the loss of driving-related jobs in the road transport industry. The automobile insurance industry might suffer as the technology makes certain aspects of these occupations obsolete.

Privacy could be an issue when having the vehicle's location and position integrated into an interface in which other people have access to. Self-driving cars could potentially be loaded with explosives and used as bombs.

The lack of stressful driving, more productive time during the trip, and the potential savings in travel time and cost could become an incentive to live far away from cities, where land is cheaper, and work in the city's core, thus increasing travel distances and inducing more urban sprawl , more fuel consumption and an increase in the carbon footprint of urban travel.

Some believe that once automation in vehicles reaches higher levels and becomes reliable, drivers will pay less attention to the road. Ethical and moral reasoning come into consideration when programming the software that decides what action the car takes in an unavoidable crash; whether the automated car will crash into a bus, potentially killing people inside; or swerve elsewhere, potentially killing its own passengers or nearby pedestrians.

The ethics of automated vehicles are still being articulated, and may lead to controversy. Different human drivers make various ethical decisions when driving, such as avoiding harm to themselves, or putting themselves at risk to protect others.

These decisions range from rare extremes such as self-sacrifice or criminal negligence, to routine decisions good enough to keep the traffic flowing but bad enough to cause accidents, road rage and stress. Human thought and reaction time may sometimes be too slow to detect the risk of an upcoming fatal crash, think through the ethical implications of the available options, or take an action to implement an ethical choice.

Whether a particular automated vehicle's capacity to correctly detect an upcoming risk, analyse the options or choose a 'good' option from among bad choices would be as good or better than a particular human's may be difficult to predict or assess.

This difficulty may be in part because the level of automated vehicle system understanding of the ethical issues at play in a given road scenario, sensed for an instant from out of a continuous stream of synthetic physical predictions of the near future, and dependent on layers of pattern recognition and situational intelligence, may be opaque to human inspection because of its origins in probabilistic machine learning rather than a simple, plain English 'human values' logic of parsable rules.

The depth of understanding, predictive power and ethical sophistication needed will be hard to implement, and even harder to test or assess.

Vehicle pdf autonomous

The scale of this challenge may have other effects. There may be few entities able to marshal the resources and AI capacity necessary to meet it, as well as the capital necessary to take an automated vehicle system to market and sustain it operationally for the life of a vehicle, and the legal and 'government affairs' capacity to deal with the potential for liability for a significant proportion of traffic accidents.

This may have the effect of narrowing the number of different system opertors, and eroding the presently quite diverse global vehicle market down to a small number of system suppliers. The traditional automobile industry is subject to changes driven by technology and market demands. These changes include breakthrough technological advances and when the market demands and adopts new technology quickly. In the rapid advance of both factors, the end of the era of incremental change was recognized.

When the transition is made to a new technology, new entrants to the automotive industry present themselves, which can be distinguished as mobility providers such as Uber and Lyft, as well as tech giants such as Google and Nvidia.

As new entrants to the industry arise, market uncertainty naturally occurs due to the changing dynamics. For example, the entrance of tech giants, as well as the alliances between them and traditional car manufacturers causes a variation in the innovation and production process of autonomous vehicles. Additionally, the entrance of mobility providers has caused ambiguous user preferences.

As a result of the rise of mobility providers, the number of vehicles per capita has flatlined. In addition, the rise of the sharing economy also contributes to market uncertainty and causes forecasters to question whether private ownership of vehicles is still relevant as new transportation technology and mobility providers are becoming preferred among consumers.

With the aforementioned ambiguous user preference regarding the private ownership of autonomous vehicles, it is possible that the current mobility provider trend will continue as it rises in popularity.

Established providers such as Uber and Lyft are already significantly present within the industry, and it is likely that new entrants will enter when business opportunities arise. With the increasing reliance of autonomous vehicles on interconnectivity and the availability of big data which is made usable in the form of real time maps, driving decisions can be made much faster in order to prevent collisions. As a result, major implications for the healthcare industry become apparent.

Numbers from the National Safety Council on killed and injured people on U. It is likely the anticipated decrease in traffic accidents will positively contribute to the widespread acceptance of autonomous vehicles, as well as the possibility to better allocate healthcare resources. As collisions are less likely to occur, and the risk for human errors is reduced significantly, the repair industry will face an enormous reduction of work that has to be done on the reparation of car frames.

Meanwhile, as the generated data of the autonomous vehicle is likely to predict when certain replaceable parts are in need of maintenance, car owners and the repair industry will be able to proactively replace a part that will fail soon.

This "Asset Efficiency Service" would implicate a productivity gain for the automotive repair industry.

Self-driving car - Wikipedia

As fewer collisions implicate less money spent on repair costs, the role of the insurance industry is likely to be altered as well. It can be expected that the increased safety of transport due to autonomous vehicles will lead to a decrease in payouts for the insurers, which is positive for the industry, but fewer payouts may imply a demand drop for insurances in general.

The insurance industry may have to create new insurance models in the near future to accommodate the changes. An unexpected disadvantage of the widespread acceptance of autonomous vehicles would be a reduction in organs available for transplant.

The technique used in autonomous driving also ensures life savings in other industries. The implementation of autonomous vehicles with rescue, emergency response, and military applications has already led to a decrease in deaths.

In addition, a future implication of adopting autonomous vehicles could lead to a reduction in deployed personnel, which will lead to a decrease in injuries, since the technological development allows Autonomous Vehicles AVs to become more and more autonomous.

Another future implication is the reduction of emergency drivers when autonomous vehicles are deployed as fire trucks or ambulances. An advantage could be the use of real-time traffic information and other generated data to determine and execute routes more efficiently than human drivers.

The time savings can be invaluable in these situations. For the interior design industry, there are exciting times ahead. The driver is decreasingly focused on the actual driving, this implies that the interior design- and media-entertainment industry has to reconsider what passengers of autonomous vehicles are doing when they are on the road. Vehicles need to be redesigned, and possibly even be prepared for multipurpose usage. In both cases, this gives increasing opportunities for the media-entertainment industry to demand attention.

Moreover, the advertisement business is able to provide location based ads without risking driver safety. As autonomous vehicles are producing enormous amounts of data that need to be transferred and analyzed, the upcoming 5G cellular network will play a pivotal role in doing so.

In addition, the earlier mentioned entertainment industry is also highly dependent on this network to be active in this market segment. This implies higher revenues for the telecommunication industry. Since many autonomous vehicles are going to rely on electricity to operate, the demand for lithium batteries increases. Similarly, radar, sensors, lidar , and high-speed internet connectivity require higher auxiliary power from vehicles, which manifests as greater power draw from batteries.

On the other hand, with the expected increase of battery powered autonomous vehicles, the petroleum industry is expected to undergo a decline in demand.

As this implication depends on the adoption rate of autonomous vehicles, it is unsure to what extent this implication will disrupt this particular industry. This transition phase of oil to electricity allows companies to explore whether there are business opportunities for them in the new energy ecosystem.

Driver interactions with the vehicle will be less common within the near future, and in the more distant future the responsibility will lie entirely with the vehicle. As indicated above, this will have implications for the entertainment- and interior design industry. For roadside restaurants, the implication will be that the need for customers to stop driving and enter the restaurant will vanish, and the autonomous vehicle will have a double function.

Moreover, accompanied with the rise of disruptive platforms such as Airbnb that have shaken up the hotel industry, the fast increase of developments within the autonomous vehicle industry might cause another implication for their customer bases. In the more distant future, the implication for motels might be that a decrease in guests will occur, since autonomous vehicles could be redesigned as fully equipped bedrooms.

The improvements regarding the interior of the vehicles might additionally have implications for the airline industry. In the case of relatively short-haul flights, waiting times at customs or the gate imply lost time and hassle for customers. With the improved convenience in future car travel, it is possible that customers might go for this option, causing a loss in customer bases for airline industry.

Autonomous vehicles will have a severe impact on the mobility options of persons that are not able to drive a vehicle themselves.

To remain socially engaged with society or even able to do groceries, the elderly people of today are depending on caretakers to drive them to these places.

In addition to the perceived freedom of the elderly people of the future, the demand for human aides will decrease. When we also consider the increased health of the elderly, it is safe to state that care centers will experience a decrease in the number of clients. Not only elderly people face difficulties of their decreased physical abilities, also disabled people will perceive the benefits of autonomous vehicles in the near future, causing their dependency on caretakers to decrease.

Both industries are largely depending on informal caregivers, who are mostly relatives of the persons in need. Since there is less of a reliance on their time, employers of informal caregivers or even governments will experience a decrease of costs allocated to this matter. Children and teens, who are not able to drive a vehicle themselves, are also benefiting of the introduction of autonomous cars.

Daycares and schools are able to come up with automated pick up and drop off systems, causing a decrease of reliance on parents and childcare workers. The extent to which human actions are necessary for driving will vanish. Since current vehicles require human actions to some extent, the driving school industry will not be disrupted until the majority of autonomous transportation is switched to the emerged dominant design.

It is plausible that in the distant future driving a vehicle will be considered as a luxury, which implies that the structure of the industry is based on new entrants and a new market. At this level the car can be automated but requires the full attention of the driver, who must be prepared to take control at a moment's notice. In urban driving the system will not read traffic signals or obey stop signs. The system also does not detect pedestrians or cyclists. On 20 January , the first known fatal crash of a Tesla with Autopilot occurred in China's Hubei province.

According to China's A similar fatal crash occurred four months later in Florida. The second known fatal accident involving a vehicle being driven by itself took place in Williston, Florida on 7 May while a Tesla Model S electric car was engaged in Autopilot mode.

The occupant was killed in a crash with an wheel tractor-trailer. According to the NHTSA, preliminary reports indicate the crash occurred when the tractor-trailer made a left turn in front of the Tesla at an intersection on a non-controlled access highway, and the car failed to apply the brakes.

The car continued to travel after passing under the truck's trailer. The agency also requested details of all design changes and updates to Autopilot since its introduction, and Tesla's planned updates schedule for the next four months. According to Tesla, "neither autopilot nor the driver noticed the white side of the tractor-trailer against a brightly lit sky, so the brake was not applied.

In July , the U. The NTSB is an investigative body that has the power to make only policy recommendations. An agency spokesman said "It's worth taking a look and seeing what we can learn from that event, so that as that automation is more widely introduced we can do it in the safest way possible. According to Tesla, starting 19 October , all Tesla cars are built with hardware to allow full self-driving capability at the highest safety level SAE Level 5. Waymo originated as a self-driving car project within Google.

According to Google's accident reports as of early , their test cars had been involved in 14 collisions, of which other drivers were at fault 13 times, although in the car's software caused a crash. In June , Brin confirmed that 12 vehicles had suffered collisions as of that date. Eight involved rear-end collisions at a stop sign or traffic light, two in which the vehicle was side-swiped by another driver, one in which another driver rolled through a stop sign, and one where a Google employee was controlling the car manually.

This was the first time that a collision resulted in injuries. During the maneuver it struck a bus. Google stated, "In this case, we clearly bear some responsibility, because if our car hadn't moved, there wouldn't have been a collision.

No injuries were reported in the crash. In March , an Uber test vehicle was involved in a crash in Tempe, Arizona when another car failed to yield, flipping the Uber vehicle.

There were no injuries in the accident. On 18 March , Elaine Herzberg became the first pedestrian to be killed by a self-driving car in the United States after being hit by an Uber vehicle, also in Tempe. Herzberg was crossing outside of a crosswalk , approximately feet from an intersection.

The first death of an essentially uninvolved third party is likely to raise new questions and concerns about the safety of automated cars in general. On 9 November , a Navya automated self-driving bus with passengers was involved in a crash with a truck. The truck was found to be at fault of the crash, reversing into the stationary automated bus.

The automated bus did not take evasive actions or apply defensive driving such as flash headlights, sound the horn, or as one passenger commented "The shuttle didn't have the ability to move back. The shuttle just stayed still. According to a Wonkblog reporter, if fully automated cars become commercially available, they have the potential to be a disruptive innovation with major implications for society.

The likelihood of widespread adoption is still unclear, but if they are used on a wide scale, policy makers face a number of unresolved questions about their effects. One fundamental question is about their effect on travel behavior.

Some people believe that they will increase car ownership and car use because it will become easier to use them and they will ultimately be more useful. Others argue that it will be easier to share cars and that this will thus discourage outright ownership and decrease total usage, and make cars more efficient forms of transportation in relation to the present situation. Policy-makers will have to take a new look at how infrastructure is to be built and how money will be allotted to build for automated vehicles.

The need for traffic signals could potentially be reduced with the adoption of smart highways. Other disruptive effects will come from the use of automated vehicles to carry goods. Self-driving vans have the potential to make home deliveries significantly cheaper, transforming retail commerce and possibly making hypermarkets and supermarkets redundant. As of right now the U. Government defines automation into six levels, starting at level zero which means the human driver does everything and ending with level five, the automated system performs all the driving tasks.

Also under the current law, manufacturers bear all the responsibility to self-certify vehicles for use on public roads. This means that currently as long as the vehicle is compliant within the regulatory framework, there are no specific federal legal barriers to a highly automated vehicle being offered for sale. Iyad Rahwan , an associate professor in the MIT Media lab said, "Most people want to live in a world where cars will minimize casualties, but everyone wants their own car to protect them at all costs.

The Vienna Convention on Road Traffic , subscribed to by over 70 countries worldwide, establishes principles to govern traffic laws. One of the fundamental principles of the Convention has been the concept that a driver is always fully in control and responsible for the behavior of a vehicle in traffic. In the United States, a non-signatory country to the Vienna Convention, state vehicle codes generally do not envisage — but do not necessarily prohibit — highly automated vehicles.

Incidents such as the first fatal accident by Tesla's Autopilot system have led to discussion about revising laws and standards for automated cars. In September , the US National Economic Council and Department of Transportation released federal standards that describe how automated vehicles should react if their technology fails, how to protect passenger privacy, and how riders should be protected in the event of an accident. The new federal guidelines are meant to avoid a patchwork of state laws, while avoiding being so overbearing as to stifle innovation.

In June , the Nevada Legislature passed a law to authorize the use of automated cars. Nevada thus became the first jurisdiction in the world where automated vehicles might be legally operated on public roads.

According to the law, the Nevada Department of Motor Vehicles NDMV is responsible for setting safety and performance standards and the agency is responsible for designating areas where automated cars may be tested.

Google had further lobbied for an exemption from a ban on distracted driving to permit occupants to send text messages while sitting behind the wheel, but this did not become law.

In April , Florida became the second state to allow the testing of automated cars on public roads, [] and California became the third when Governor Jerry Brown signed the bill into law at Google Headquarters in Mountain View. On 19 February , Assembly Bill No.

The Bill states the Department of Motor Vehicles would need to comply with these regulations by 1 July for these rules to take effect. This bill has yet to pass the house of origin. In September , the U. Department of Transportation released its Federal Automated Vehicles Policy, [] and California published discussions on the subject in October In December , the California Department of Motor Vehicles ordered Uber to remove its self-driving vehicles from the road in response to two red-light violations.

Uber immediately blamed the violations on "human-error", and has suspended the drivers. In , the government of the United Kingdom permitted the testing of automated cars on public roads. In , the Government of France announced that testing of automated cars on public roads would be allowed in At the ITS World Congress, a conference dedicated to intelligent transport systems, the very first demonstration of automated vehicles on open road in France was carried out in Bordeaux in early October In , a preemptive lawsuit against various automobile companies such as GM, Ford, and Toyota accused them of "Hawking vehicles that are vulnerable to hackers who could hypothetically wrest control of essential functions such as brakes and steering.

In , the Singapore Land Transit Authority in partnership with UK automotive supplier Delphi Automotive Plc will launch preparations for a test run of a fleet of automated taxis for an on-demand automated cab service to take effect in Self-driving car liability is a developing area of law and policy that will determine who is liable when an automated car causes physical damage to persons, or breaks road rules. It is claimed by proponents to have potential to affect the frequency of road accidents, although it is difficult to assess this claim in the absence of data from substantial actual use.

However, there is no obvious reason why they should escape liability if any such effects were found to be modest or nonexistent, since part of the purpose of such liability is to give an incentive to the party controlling something to do whatever is necessary to avoid it causing harm.

Potential users may be reluctant to trust an operator if it seeks to pass its normal liability on to others. In any case, a well-advised person who is not controlling a car at all Level 5 would be understandably reluctant to accept liability for something out of their control.

And when there is some degree of sharing control possible Level 3 or 4 , a well-advised person would be concerned that the vehicle might try to pass back control at the last seconds before an accident, to pass responsibility and liability back too, but in circumstances where the potential driver has no better prospects of avoiding the crash than the vehicle, since they have not necessarily been paying close attention, and if it is too hard for the very smart car it might be too hard for a human.

Since operators, especially those familiar with trying to ignore existing legal obligations under a motto like 'seek forgiveness, not permission' , such as Waymo or Uber, could be normally expected to try to avoid responsibility to the maximum degree possible, there is potential for attempt to let the operators evade being held liable for accidents while they are in control. As higher levels of automation are commercially introduced level 3 and 4 , the insurance industry may see a greater proportion of commercial and product liability lines while personal automobile insurance shrinks.

Vehicle networking may be desirable due to difficulty with computer vision being able to recognize brake lights, turn signals, buses, and similar things. However, the usefulness of such systems would be diminished by the fact current cars are equipped with them; they may also pose privacy concerns.

Individual vehicles may benefit from information obtained from other vehicles in the vicinity, especially information relating to traffic congestion and safety hazards. Vehicular communication systems use vehicles and roadside units as the communicating nodes in a peer-to-peer network, providing each other with information.

How China will help fuel the revolution in autonomous vehicles

As a cooperative approach, vehicular communication systems can allow all cooperating vehicles to be more effective. According to a study by the National Highway Traffic Safety Administration, vehicular communication systems could help avoid up to 79 percent of all traffic accidents. There have so far been no complete implementation of peer-to-peer networking on the scale required for traffic: In , computer scientists at the University of Texas in Austin began developing smart intersections designed for automated cars.

The intersections will have no traffic lights and no stop signs, instead of using computer programs that will communicate directly with each car on the road. It was shown that the Crossroads is resilient to network delay of V2I communication and Worst-case Execution time of the intersection manager.

Among connected cars, an unconnected one is the weakest link and will be increasingly banned from busy high-speed roads, predicted a Helsinki think tank in January A survey of 17, vehicle owners by J. In a US telephone survey by Insurance. In a questionnaire survey by Delft University of Technology explored the opinion of 5, people from countries on automated driving.

Results showed that respondents, on average, found manual driving the most enjoyable mode of driving. Finally, respondents from more developed countries in terms of lower accident statistics, higher education, and higher income were less comfortable with their vehicle transmitting data.

In , a survey in Germany examined the opinion of 1, people, who were representative in terms of age, gender, and education for the German population, towards partially, highly, and fully automated cars. Results showed that men and women differ in their willingness to use them. Men felt less anxiety and more joy towards automated cars, whereas women showed the exact opposite. The gender difference towards anxiety was especially pronounced between young men and women but decreased with participants' age.

In , a PwC survey, in the United States, showing the opinion of 1, people, highlights that "66 percent of respondents said they think autonomous cars are probably smarter than the average human driver".

People are still worried about safety and mostly the fact of having the car hacked. A Pew Research Center survey of 4, U. With the emergence of automated automobiles, various ethical issues arise. Those include, but are not limited to: There are different opinions on who should be held liable in case of a crash, especially with people being hurt. Many experts see the car manufacturers themselves responsible for those crashes that occur due to a technical malfunction or misconstruction.

However, there are also voices [ who? Experts [ who? Taking aside the question of legal liability and moral responsibility, the question arises how automated vehicles should be programmed to behave in an emergency situation where either passengers or other traffic participants like: A moral dilemma that a software engineer or car manufacturer might face in programming the operating software is described in an ethical thought experiment, the trolley problem: The car has to decide between the two options, either to run the person over or to avoid hitting the person by swerving into a wall, killing the passengers.

First, what moral basis would be used by an automated vehicle to make decisions? Second, how could those be translated into software code? Researchers have suggested, in particular, two ethical theories to be applicable to the behavior of automated vehicles in cases of emergency: The theory suggests that an automated car needs to follow strict written-out rules that it needs to follow in any situation.

Utilitarianism suggests the idea that any decision must be made based on the goal to maximize utility. This needs a definition of utility which could be maximizing the number of people surviving in a crash. Critics suggest that automated vehicles should adapt a mix of multiple theories to be able to respond morally right in the instance of a crash.

Many 'Trolley' discussions skip over the practical problems of how a probabilistic machine learning vehicle AI could be sophisticated enough to understand that a deep problem of moral philosophy is presenting itself from instant to instant while using a dynamic projection into the near future, what sort of moral problem it actually would be if any, what the relevant weightings in human value terms should be given to all the other humans involved who will be probably unreliably identified, and how reliably it can assess the probable outcomes.

These practical difficulties, and those around testing and assessment of solutions to them, may present as much of a challenge as the theoretical abstractions.

Privacy-related issues arise mainly from the interconnectivity of automated cars, making it just another mobile device that can gather any information about an individual. This information gathering ranges from tracking of the routes taken, voice recording, video recording, preferences in media that is consumed in the car, behavioral patterns, to many more streams of information.

Many industries, such as the auto insurance industry are indirectly affected. In December , Tesla CEO Elon Musk predicted that a completely automated car would be introduced by the end of ; [] in December , he announced that it would take another two years to launch a fully self-driving Tesla onto the market. It seems the clear leader in self driving cars, although its crash rate in California is still higher than a novice driver.

The automated and occasionally sentient self-driving car story has earned its place in both literary science fiction and pop sci-fi. Intelligent or self-driving cars are a common theme in science fiction literature. Examples include:. From Wikipedia, the free encyclopedia. This article is about the vehicle. For the system, see automated driving system. For the wider application of artificial intelligence to automobiles, see Unmanned ground vehicle. This article may be in need of reorganization to comply with Wikipedia's layout guidelines.

Please help by editing the article to make improvements to the overall structure. March Learn how and when to remove this template message. Main article: History of self-driving cars. Hybrid navigation. See also: List of self-driving car fatalities. Tesla Autopilot. Self-driving car liability. Vehicular communication systems. This article may contain an excessive amount of intricate detail that may interest only a particular audience. Please help by spinning off or relocating any relevant information, and removing excessive detail that may be against Wikipedia's inclusion policy.

August Learn how and when to remove this template message. Machine ethics. This section's tone or style may not reflect the encyclopedic tone used on Wikipedia. See Wikipedia's guide to writing better articles for suggestions.

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February Learn how and when to remove this template message. This section gives self-sourcing popular culture examples without describing their significance in the context of the article.

Please help improve this section by adding citations to reliable sources that describe the examples' significance, and by removing less pertinent examples. Unsourced or poorly sourced material may be challenged or removed. Robotics portal. Retrieved April 14, Communications of the ACM. Dead reckoning and cartography using stereo vision for an automated car. Motor Trend. Retrieved 1 September CNBC Videos. April 13, Retrieved April 14, — via Yahoo. The Milwaukee Sentinel. Retrieved 23 July Retrieved 26 July A History of Autonomous Vehicles".

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