Self-driving car

A self-driving car, also known as an autonomous car (AC), driverless car, robotic car or robo-car,

ACs have the potential to impact the automotive industry, mobility costs, health, welfare, urban planning, traffic, insurance, labor market, and other domains. Appropriate regulations are necessary to integrate ACs into the existing driving environment.

Multiple vendors are pursuing autonomy, although as of early 2024, no system had achieved full autonomy. Waymo was the first to offer rides in self-driving taxis ("robotaxis") to the public,

History

Experiments have been conducted on advanced driver assistance systems (ADAS) since at least the 1920s.

Trials began in the 1950s. The first semi-autonomous car was developed in 1977, by Japan's Tsukuba Mechanical Engineering Laboratory.

Carnegie Mellon University's Navlab

The US allocated US$650�million in 1991 for research on the National Automated Highway System,

From 2016 to 2018, the European Commission funded development for connected and automated driving through Coordination Actions CARTRE and SCOUT programs.

In November 2017, Waymo announced testing of autonomous cars without a safety driver.

In December 2018, Waymo was the first to commercialize a robotaxi service, in Phoenix, Arizona.

In March 2019, ahead of Roborace, Robocar set the Guinness World Record as the world's fastest autonomous car. Robocar reached 282.42�km/h (175.49�mph).

In March 2021, Honda began leasing in Japan a limited edition of 100 Legend Hybrid EX sedans equipped with newly approved Level 3 automated driving equipment that had been safety certified, using their autonomous "Traffic Jam Pilot" driving technology, and legally allowed drivers to take their eyes off the road.

In December 2020, Waymo became the first service provider to offer driverless taxi rides to the general public, in a part of Phoenix, Arizona. In March 2021, Honda was the first manufacturer to sell a legally approved Level 3 car.

As of August�2023

Definitions

Organizations such as SAE have proposed terminology standards. However, most terms have no standard definition and are employed variously by vendors and others. Proposals to adopt aviation automation terminology for cars have not prevailed.

Names such as AutonoDrive, PilotAssist, Full-Self Driving or DrivePilot are used even though the products offer an assortment of features that may not match the names.

Automated driving system

An ADS is an SAE J3016 level 3 or higher system.

Advanced driver assistance system

An ADAS is a system that automates specific driving features, such as keeping the car within its lane, cruise control, and emergency braking. An ADAS requires a human driver to handle tasks that the ADAS does not support.

Autonomy versus automation

Autonomy implies that an automation system is under the control of the vehicle rather than a driver. Automation is function-specific, handling issues such as speed control, but leaves broader decision-making to the driver.

Euro NCAP defined autonomous as "the system acts independently of the driver to avoid or mitigate the accident".

In Europe, the words automated and autonomous can be used together. For instance, Regulation (EU) 2019/2144 supplied:

Cooperative system

A remote driver is a driver that operates a vehicle at a distance, using a video and data connection.

According to SAE J3016,

Some driving automation systems may indeed be autonomous if they perform all of their functions independently and self-sufficiently, but if they depend on communication and/or cooperation with outside entities, they should be considered cooperative rather than autonomous.

Operational design domain

Operational design domain (ODD) is a term for a particular operating context for an automated system, often used in the field of autonomous vehicles. The context is defined by a set of conditions, including environmental, geographical, time of day, and other conditions. For vehicles, traffic and roadway characteristics are included. Manufacturers use ODD to indicate where/how their product operates safely. A given system may operate differently according to the immediate ODD.

Vendors have taken a variety of approaches to the self-driving problem. Tesla's approach is to allow their "full self-driving" (FSD) system to be used in all ODDs as a Level 2 (hands/on, eyes/on) ADAS.

Self-driving

The Union of Concerned Scientists defined self-driving as "cars or trucks 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."

The British Automated and Electric Vehicles Act 2018 law defines a vehicle as "driving itself" if the vehicle is "not being controlled, and does not need to be monitored, by an individual".

Another British government definition stated,"Self-driving vehicles are vehicles that can safely and lawfully drive themselves".

British definitions

In British English, the word automated alone has several meanings, such as in the sentence: "Thatcham also found that the automated lane keeping systems could only meet two out of the twelve principles required to guarantee safety, going on to say they cannot, therefore, be classed as 'automated driving', preferring 'assisted driving'".

In November 2023 the British Government introduced the Automated Vehicles Bill. It proposed definitions for related terms:

SAE classification

A six-level classification system � ranging from fully manual to fully automated � was published in 2014 by SAE International as J3016, Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems; the details are revised occasionally.

A "driving mode", aka driving scenario, combines an ODD with matched driving requirements (e.g., expressway merging, traffic jam).

Above Level 1, level differences are related to how responsibility for safe movement is divided/shared between ADAS and driver rather than specific driving features.

SAE Automation Levels have been criticized for their technological focus. It has been argued that the structure of the levels suggests that automation increases linearly and that more automation is better, which may not be the case.

Mobileye

Mobileye CEO Amnon Shashua and CTO Shai Shalev-Shwartz proposed an alternative taxonomy for autonomous driving systems, claiming that a more consumer-friendly approach was needed. Its categories reflect the amount of driver engagement that is required.

The first level, hands-on/eyes-on, implies that the driver is fully engaged in operating the vehicle, but is supervised by the system, which intervenes according to the features it supports (e.g., adaptive cruise control, automatic emergency braking). The driver is entirely responsible, with hands on the wheel, and eyes on the road.

Eyes-on/hands-off allows the driver to let go of the wheel. The system drives, the driver monitors and remains prepared to resume control as needed.

Eyes-off/hands-off means that the driver can stop monitoring the system, leaving the system in full control. Eyes-off requires that no errors be reproducible (not triggered by exotic transitory conditions) or frequent, that speeds are contextually appropriate (e.g., 80 mph on limited-access roads), and that the system handle typical maneuvers (e.g., getting cut off by another vehicle). The automation level could vary according to the road (e.g., eyes-off on freeways, eyes-on on side streets).

The highest level does not require a human driver in the car: monitoring is done either remotely (telepresence) or not at all.

A critical requirement for the higher two levels is that the vehicle be able to conduct a Minimum Risk Maneuver and stop safely out of traffic without driver intervention.

Technology

Architecture

The perception system processes visual and audio data from outside and inside the car to create a local model of the vehicle, the road, traffic, traffic controls and other observable objects, and their relative motion. The control system then takes actions to move the vehicle, considering the local model, road map, and driving regulations.

Several classifications have been proposed to describe ADAS technology. One proposal is to adopt these categories: navigation, path planning, perception, and car control.

Navigation

Navigation involves the use of maps to define a path between origin and destination. Hybrid navigation is the use of multiple navigation systems. Some systems use basic maps, relying on perception to deal with anomalies. Such a map understands which roads lead to which others, whether a road is a freeway, a highway, are one-way, etc. Other systems require highly detailed maps, including lane maps, obstacles, traffic controls, etc.

ACs need to be able to perceive the world around them. Supporting technologies include combinations of cameras, LiDAR, radar, audio, and ultrasound,

Maps are necessary for navigation. Map sophistication varies from simple graphs that show which roads connect to each other, with details such as one-way vs two-way, to those that are highly detailed, with information about lanes, traffic controls, roadworks, and more.

Sensors are necessary for the vehicle to properly respond to the driving environment. Sensor types include cameras, LiDAR, ultrasound, and radar. Control systems typically combine data from multiple sensors.

Path planning finds a sequence of segments that a vehicle can use to move from origin to destination. Techniques used for path planning include graph-based search and variational-based optimization techniques. Graph-based techniques can make harder decisions such as how to pass another vehicle/obstacle. Variational-based optimization techniques require more stringent restrictions on the vehicle's path to prevent collisions.

Drive by wire

Drive by wire is the use of electrical or electro-mechanical systems for performing vehicle functions such as steering or speed control that are traditionally achieved by mechanical linkages.

Driver monitoring

Driver monitoring is used to assess the driver's attention and alertness. Techniques in use include eye monitoring, and requiring the driver to maintain torque on the steering wheel.

Vehicle communication

Vehicles can potentially benefit from communicating with others to share information about traffic, road obstacles, to receive map and software updates, etc.

ISO/TC 22 specifies in-vehicle transport information and control systems,

Rather than communicating among vehicles, they can communicate with road-based systems to receive similar information.

Software update

Software controls the vehicle, and can provide entertainment and other services. Over-the-air updates can deliver bug fixes and additional features over the internet. Software updates are one way to accomplish recalls that in the past required a visit to a service center. In March 2021, the UNECE regulation on software update and software update management systems was published.

Safety model

A safety model is software that attempts to formalize rules that ensure that ACs operate safely.

IEEE is attempting to forge a standard for safety models as "IEEE P2846: A Formal Model for Safety Considerations in Automated Vehicle Decision Making".

Notification

The US has standardized the use of turquoise lights to inform other drivers that a vehicle is driving autonomously. It will be used in the 2026 Mercedes-Benz EQS and S-Class sedans with Drive Pilot, an SAE Level 3 driving system.

As of 2023, the Turquoise light had not been standardized by the P.R.C or the UN-ECE.

Challenges

Obstacles

The primary obstacle to ACs is the advanced software and mapping required to make them work safely across the wide variety of conditions that drivers experience.

Other obstacles include cost, liability,

Concerns

Tesla calls its Level 2 ADAS "Full Self-Driving (FSD) Beta".

Mercedes-Benz was criticized for a misleading US commercial advertising E-Class models.

With the Automated Vehicles Bill (AVB) self-driving car-makers could face prison for misleading adverts in the United-Kingdom.

In the 2020s, concerns over ACs' vulnerability to cyberattacks and data theft emerged.

In 2018 and 2019 former Apple engineers were charged with stealing information related to Apple's self-driving car project.

Cellular Vehicle-to-Everything technologies are based on 5G wireless networks.

Testing of Chinese automated cars in the US has raised concern over which US data are collected by Chinese vehicles to be stored in Chinese country and concern with any link with the Chinese communist party.

ACs complicate the need for drivers to communicate with each other, e.g., to decide which car enters an intersection first. In an AC without a driver, traditional means such as hand signals do not work (no driver, no hands).

ACs must be able to predict the behavior of possibly moving vehicles, pedestrians, etc in real time in order to proceed safely.

The ADAS has to be able to safely accept control from and return control to the driver.

Risk compensation is a common human behavior. The safer a system is perceived to be, the more likelier people are to test its limits by engaging in riskier behavior. (People who wear seat belts drive faster). For example Tesla Autopilot users in some cases stop monitoring the vehicle.

Consumers will avoid ACs unless they trust them as safe.

Ethical issues

Standards for liability have yet to be adopted to address crashes and other incidents. Liability could rest with the vehicle occupant, its owner, the vehicle manufacturer, or even the ADAS technology supplier, possibly depending on the circumstances of the crash.

The trolley problem is a thought experiment in ethics. Adapted for ACs, it considers an AC carrying one passenger confronts a pedestrian who steps in its way. The ADAS notionally has to choose between killing the pedestrian or swerving into a wall, killing the passenger.

One public opinion survey reported that harm reduction was preferred, except that passengers wanted the vehicle to prefer them, while pedestrians took the opposite view. Utilitarian regulations were unpopular.

Some ACs require an internet connection to function, opening the possibility that a hacker might gain access to private information such as destinations, routes, camera recordings, media preferences, and/or behavioral patterns, although this is true of an internet-connected device.

Road infrastructure

ACs make use of road infrastructure (e.g., traffic signs, turn lanes) and may require modifications to that infrastructure to fully achieve their safety and other goals.

Testing

Approaches

ACs can be tested via digital simulations,

2010s and disengagements

In California, self-driving car manufacturers are required to submit annual reports describing how often their vehicles autonomously disengaged from autonomous mode.

In 2017, Waymo reported 63 disengagements over 352,545�mi (567,366�km) of testing, an average distance of 5,596�mi (9,006�km) between disengagements, the highest (best) among companies reporting such figures. Waymo also logged more autonomous miles than other companies. Their 2017 rate of 0.18 disengagements per 1,000�mi (1,600�km) was an improvement over the 0.2 disengagements per 1,000�mi (1,600�km) in 2016, and 0.8 in 2015. In March 2017, Uber reported an average of 0.67�mi (1.08�km) per disengagement. In the final three months of 2017, Cruise (owned by GM) averaged 5,224�mi (8,407�km) per disengagement over 62,689�mi (100,888�km).

2020s

Reporting companies use varying definitions of what qualifies as a disengagement, and such definitions can change over time.

In April 2021, WP.29 GRVA proposed a "Test Method for Automated Driving (NATM)".

In October 2021, Europe's pilot test, L3Pilot, demonstrated ADAS for cars in Hamburg, Germany, in conjunction with ITS World Congress 2021. SAE Level 3 and 4 functions were tested on ordinary roads.

In November 2022, an International Standard ISO 34502 on "Scenario based safety evaluation framework" was published.

In April 2022, collision avoidance testing was demonstrated by Nissan.

In September 2022, Biprogy released Driving Intelligence Validation Platform (DIVP) as part of Japanese national project "SIP-adus", which is interoperable with Open Simulation Interface (OSI) of ASAM.

In November 2022, Toyota demonstrated one of its GR Yaris test cars, which had been trained using professional rally drivers.

In 2023 David R. Large, senior research fellow with the Human Factors Research Group at the University of Nottingham, disguised himself as a car seat in a study to test people's reactions to driverless cars. He said, "We wanted to explore how pedestrians would interact with a driverless car and developed this unique methodology to explore their reactions." The study found that, in the absence of someone in the driving seat, pedestrians trust certain visual prompts more than others when deciding whether to cross the road.

Incidents

Tesla

As of 2023, Tesla's ADAS Autopilot/Full Self Driving (beta) was classified as Level 2 ADAS.

On 20 January 2016, the first of five known fatal crashes of a Tesla with Autopilot occurred, in China's Hubei province.

Another fatal Autopilot crash occurred in May in Florida in a Tesla Model S

Google Waymo

In June 2015, Google confirmed that 12 vehicles had suffered collisions as of that date. Eight involved rear-end collisions at a stop sign or traffic light, in two of which the vehicle was side-swiped by another driver, one in which another driver rolled a stop sign, and one where a driver was controlling the car manually.

According to Google Waymo's accident reports as of early 2016, their test cars had been involved in 14 collisions, of which other drivers were at fault 13 times, although in 2016 the car's software caused a crash.

Uber's Advanced Technologies Group (ATG)

In March 2018, Elaine Herzberg died after she was hit by an AC tested by Uber's Advanced Technologies Group (ATG) in Arizona. A safety driver was in the car. Herzberg was crossing the road about 400 feet from an intersection.

NTSB's final report determined that the immediate cause of the accident was that safety driver Rafaela Vasquez failed to monitor the road, because she was distracted by her phone, but that Uber's "inadequate safety culture" contributed. The report noted that the victim had "a very high level" of methamphetamine in her body.

In September 2020, Vasquez pled guilty to negligent homicide.

NIO Navigate on Pilot

On 12 August 2021, a 31-year-old Chinese man was killed after his NIO ES8 collided with a construction vehicle.

Pony.ai

In November 2021, the California Department of Motor Vehicles (DMV) notified Pony.ai that it was suspending its testing permit following a reported collision in Fremont on 28 October.

Cruise

In April 2022, Cruise's testing vehicle was reported to have blocked a fire engine on emergency call, and sparked questions about its ability to handle unexpected circumstances.

Public opinion surveys

2010s

In a 2011 online survey of 2,006 US and UK consumers, 49% said they would be comfortable using a "driverless car".

A 2012 survey of 17,400 vehicle owners found 37% who initially said they would be interested in purchasing a "fully autonomous car". However, that figure dropped to 20% if told the technology would cost US$3,000 more.

In a 2012 survey of about 1,000 German drivers, 22% had a positive attitude, 10% were undecided, 44% were skeptical and 24% were hostile.

A 2013 survey of 1,500 consumers across 10 countries found 57% "stated they would be likely to ride in a car controlled entirely by technology that does not require a human driver", with Brazil, India and China the most willing to trust automated technology.

In a 2014 US telephone survey, over three-quarters of licensed drivers said they would consider buying a self-driving car, rising to 86% if car insurance were cheaper. 31.7% said they would not continue to drive once an automated car was available.

In 2015, a survey of 5,000 people from 109 countries reported that average respondents found manual driving the most enjoyable. 22% did not want to pay more money for autonomy. Respondents were found to be most concerned about hacking/misuse, and were also concerned about legal issues and safety. Finally, respondents from more developed countries were less comfortable with their vehicle sharing data.

In 2016, a survey of 1,603 people in Germany that controlled for age, gender, and education reported that men felt less anxiety and more enthusiasm, whereas women showed the opposite. The difference was pronounced between young men and women and decreased with age.

In a 2016 US survey of 1,584 people, "66 percent of respondents said they think autonomous cars are probably smarter than the average human driver". People were worried about safety and hacking risk. Nevertheless, only 13% of the interviewees saw no advantages in this new kind of cars.

In a 2017 survey of 4,135 US adults found that many Americans anticipated significant impacts from various automation technologies including the widespread adoption of automated vehicles.

In 2019, results from two opinion surveys of 54 and 187 US adults respectively were published. The questionnaire was termed the autonomous vehicle acceptance model (AVAM), including additional description to help respondents better understand the implications of various automation levels. Users were less accepting of high autonomy levels and displayed significantly lower intention to use autonomous vehicles. Additionally, partial autonomy (regardless of level) was perceived as requiring uniformly higher driver engagement (usage of hands, feet and eyes) than full autonomy.

In the 2020s

In 2022, a survey reported that only a quarter (27%) of the world's population would feel safe in self-driving cars.

Opinion surveys may have little salience given that few respondents had any personal experience with ACs.

Regulation

AC regulation liability, approvals, and international conventions.

In the 2010s, researchers openly worried that delayed regulations could delay deployment.

Commercialization

Vehicles operating below Level 5 still offer many advantages.

As of 2023

Level 2 - Partial Automation

SAE Level 2 features are available as part of the ADAS systems in many vehicles. In the US, 50% of new cars provide driver assistance for both steering and speed.

Ford started offering BlueCruise service on certain vehicles in 2022; the system is named ActiveGlide in Lincoln vehicles. The system provided features such as lane centering, street sign recognition, and hands-free highway driving on more than 130,000 miles of divided highways. The 2022 1.2 version added features including hands-free lane changing, in-lane repositioning, and predictive speed assist.

Tesla's Autopilot and its Full Self-Driving (FSD) ADAS suites are available on all Tesla cars. FSD offers highway and street driving (without geofencing), navigation/turn management, steering, and dynamic cruise control, collision avoidance, lane-keeping/switching, emergency braking, obstacle avoidance, but still requires the driver to remain ready to control the vehicle at any moment. Its driver management system combines eye tracking with monitoring pressure on the steering wheel to ensure that drives are both hands on and eyes on.

General Motors is developing the "Ultra Cruise" ADAS system, that will be a dramatic improvement over their current "Super Cruise" system. Ultra Cruise will cover "95 percent" of driving scenarios on 2 million miles of roads in the US, according to the company. The system hardware in and around the car includes multiple cameras, short- and long-range radar, and a LiDAR sensor, and will be powered by the Qualcomm Snapdragon Ride Platform. The luxury Cadillac Celestiq electric vehicle will be one of the first vehicles to feature Ultra Cruise.

Tesla's FASD rewrite V12 (released in 2024) uses a single deep learning transformer model for all aspects of perception, monitoring, and control. It relies on its 8 cameras for its vision-only perception system, without use of LIDAR, radar, or ultrasound. As of January 2024, FSD V12 was undergoing testing in a limited number of customer vehicles. Tesla has not initiated requests for Level 3 status for its systems and has not disclosed its reason for not doing so.

Europe is developing a new "Driver Control Assistance Systems" (DCAS) level 2 regulation to no longer limit the use of lane changing systems to roads with 2 lanes and a physical separation from traffic in the opposite direction.

Level 3 - Conditional Automation

As of 2023, three car manufacturers had registered Level 3 cars: Honda in Japan, Mercedes in Germany, Nevada and California

Honda continued to enhance its Level 3 technology.

Mercedes-Benz received authorization in early 2023 to pilot its Level 3 software in Las Vegas.

BMW commercialized its AC in 2021.

In 2023, in China, IM Motors, Mercedes, and BMW obtained authorization to test vehicles with Level 3 systems on motorways.

In September 2021, Stellantis presented its findings from its Level 3 pilot testing on Italian highways. Stellantis's Highway Chauffeur claimed Level 3 capabilities, as tested on the Maserati Ghibli and Fiat 500X prototypes.

Polestar, a Volvo Cars' brand, announced in January 2022 its plan to offer Level 3 autonomous driving system in the Polestar 3 SUV, a Volvo XC90 successor, with technologies from Luminar Technologies, Nvidia, and Zenseact.

In January 2022, Bosch and the Volkswagen Group subsidiary CARIAD released a collaboration for autonomous driving up to Level 3. This joint development targets Level 4 capabilities.

Hyundai Motor Company is enhancing cybersecurity of connected cars to offer a Level 3 self-driving Genesis G90.

Level 4 - High Automation

Waymo offers robotaxi services in parts of a few North-American cities, as fully autonomous vehicles without safety drivers.

In April 2023 in Japan, a Level 4 protocol became part of the amended Road Traffic Act.

In July 2020, Toyota started public demonstration rides on Lexus LS (fifth generation) based TRI-P4 with Level 4 capability.

In September 2020, Mercedes-Benz introduced world's first commercial Level 4 Automated Valet Parking (AVP) system named Intelligent Park Pilot for its new S-Class.

In September 2021, Cruise, General Motors, and Honda started a joint testing programme, using Cruise AV.

In January 2023, Holon ann autonomous shuttle during the 2023 CES. The company claimed the vehicle is the world's first Level 4 shuttle built to automotive standard.