An autonomous car (also known as a car without a driver , self-driving cars and robot cars ) is a vehicle that able to feel its environment and navigate without human input.
Autonomous cars incorporate various techniques to view their environment, including radar, laser light, GPS, odometry, and computer vision. An advanced control system interprets sensor information to identify the correct navigation path, as well as relevant obstacles and marks.
Potential benefits of autonomous cars include reduced mobility and infrastructure costs, increased safety, increased mobility, increased customer satisfaction, and reduced crime. In particular significant reductions in traffic collisions; the resulting injury; and related costs, including less need for insurance. Autonomous cars are predicted to increase traffic flow; provide increased mobility for children, the elderly, the disabled and the poor; frees travelers from driving and navigation tasks; lower fuel consumption; significantly reducing the need for parking spaces; reduce crime; and facilitate the business model for transportation as a service, mainly through economic sharing. This demonstrates the huge disruptive potential of emerging technologies.
Regardless of the potential benefits for automated vehicle upgrades, there are unresolved issues, such as security, technological issues, disputes about responsibility, individual resistance to loss of control of their cars, customer concerns about car safety without drivers, application of legal frameworks and regulatory enforcement government; the risk of losing privacy and security issues, such as hackers or terrorism; concerns about job losses related to driving in the road transport industry; and the risk of increased suburbanization as travel becomes cheaper and time-consuming. Many of these problems arise because autonomous objects, for the first time, will allow computers to roam freely, with many safety and security issues involved.
Video Autonomous car
History
Experiments have been made to automate driving since at least the 1920s; promising trials occurred in the 1950s. The Tsukuba Mechanical Engineering Lab in Japan created the first autonomous and intelligent vehicle in 1977. It tracked white street markers and reached speeds of up to 30 kilometers per hour (tech faq.com). Autonomous prototype cars emerged in the 1980s, with the Navlab and ALV Carnegie Mellon University projects in 1984 and Mercedes-Benz and Bundeswehr University Munich's EUREKA Prometheus Project in 1987. Since then, many companies and research organizations have developed prototypes. By 2015, the US states of Nevada, Florida, California, Virginia, and Michigan, together with Washington, D.C. enables autonomous car testing on public roads.
In 2017, Audi stated that the latest A8 will be autonomous at speeds of up to 60 km/h using "Audi AI". The driver does not need to perform security checks as it often grips the steering wheel. The Audi A8 is claimed to be the first production car to reach level 3 autonomous driving, and Audi will be the first manufacturer to use a laser scanner other than cameras and ultrasonic sensors for their systems.
In November 2017, Waymo announced that it had begun testing the car without a driver without a driver's safety in the driver's position; But there is still an employee in the car. In February 2018, Waymo announced that the test vehicle had traveled autonomously for over 5 million miles.
Maps Autonomous car
Definition
By involving new and varied concepts, the new technologies must determine accurate vocabulary.
Autonomous vs. auto
Autonomy means to self-regulate. Many historic projects related to autonomous vehicles have been automated subject to heavy dependence on artificial aids in their environment, such as magnetic stripes. Autonomic control implies satisfactory performance under significant uncertainty in the environment and the ability to compensate for system failures without external intervention.
One approach is to implement a network of communications both in the immediate vicinity (to avoid collisions) and further (for congestion management). External influences such as in the decision process reduce the autonomy of individual vehicles, while still not requiring human intervention.
Wood et al. (2012) writes, "This article generally uses the term 'autonom,' and not the term 'automatic'." The term "autonom" is chosen "because it is a term that is currently used more widely (and thus more familiar to the general public) , But the latter term is more accurate: 'Automatically' connotes control or operation by the machine, while 'autonomous' connotes acting alone or independently Most of the vehicle concepts (which we currently realize) have someone in the driver's seat, communications to Cloud or other vehicles, and do not independently select any of the destinations or routes to reach them.Thus, the term 'automated' will more accurately depict the concept of this vehicle. In 2017, most commercial projects focus on autonomous vehicles that do not communicate with other vehicles or with a wrapping management regime.
Classification
A classification system based on six different levels (from fully manual systems to fully automated systems) was published in 2014 by SAE International, an automotive standardization body, such as the J3016, Taxonomy and Definition for Terms Related to On-Road Motor Vehicle Automated Driving System . This classification system is based on the amount of driver intervention and attention required, rather than the ability of the vehicle, although this is very loosely related. In the United States in 2013, the National Highway Traffic Safety Administration (NHTSA) released a formal classification system, but ignored this system for SAE standards by 2016. Also in 2016, SAE renewed its classification, called J3016_201609.
Automation level driving
In the definition of SAE autonomy level, "driving mode" means "the type of driving scenario with dynamic driving duty requirements (eg, highway tolls, high speed voyages, low speed traffic jams, closed campus operations, etc.)"
- Level 0: Automatic system issue warning and may interfere briefly but have no ongoing vehicle control.
- Level 1 ("hands on"): Drivers and automated systems share control of the vehicle. An example is the Adaptive Cruise Control (ACC), where the driver controls the steering wheel and the system automatically controls the speed; and Parking Assistance, where the automatic steering while speed is manual. The driver must be ready to take full control at any time. Lane Keeping Assistance (LKA) Type II is a further example of level 1 self driving.
- Level 2 ("hands off"): The automated system takes full control of the vehicle (acceleration, braking, and steering). The driver should monitor the driving and be ready to intervene immediately at any time if the automatic system fails to respond properly. Handwritten "hands-off" is not meant to be taken literally. In fact, contact between the hand and the wheel is often required during SAE 2 driving, to ensure that the driver is ready to intervene.
- Level 3 ("turn off"): Drivers can distract them from safe driving assignments, e.g. the driver can send text or watch movies. Vehicles will handle situations that demand an immediate response, such as emergency braking. The driver must remain ready to intervene within a limited time, which is determined by the manufacturer, when called by the vehicle to do so. For example, the Audi A8 Luxury Sedan 2018 is the first commercial car that claims to be capable of personal level 3 driving. This car has what is called the Pilot Traffic Jam. When powered by human drivers, the car takes full control of all aspects of driving in slow moving traffic of up to 60 kilometers per hour. Function only works on the highway with a physical barrier separating one traffic stream from incoming traffic.
- Level 4 ("objection"): Like level 3, but no driver's attention is required for safety, ie the driver can safely go to bed or leave the driver's seat. Self-driving is only supported in geofenced spatial areas or in special circumstances, such as traffic congestion. Outside these areas or circumstances, the vehicle must be able to safely cancel the trip, ie park the car, if the driver does not reclaim control.
- Level 5 ("steering wheel optional"): No human intervention is required. An example is a robotic taxi.
In the formal SAE definition below, note specifically what happens in the shift from SAE 2 to SAE 3: human drivers no longer have to monitor the environment. This is the last aspect of the "dynamic driving task" that is now passed from human to automated system. In SAE 3, human drivers still have a responsibility to intervene when asked to do so by an automated system. In SAE 4, human drivers are exempt from that responsibility and in SAE 5 automated systems will not need to ask for intervention.
Technical challenge
The challenge for car designers without drivers is to produce a control system capable of analyzing sensory data to provide accurate detection of other vehicles and road ahead. Modern self-driving cars generally use localization algorithms and bayesian mapping (SLAM), which combines data from multiple sensors and off-line maps to current location estimates and map updates. Google is developing a variant called SLAM, with the detection and tracking of other moving objects (DATMO), which also handles obstacles like cars and pedestrians. A simpler system can use real-time roadside real-time system (RTLS) system technology to assist localization. Common sensors include Lidar, stereo vision, GPS and IMU. Udacity develops open source software piles. Autonomous car control systems can use the Fusion Sensor, an approach that integrates information from various sensors on the car to produce a more consistent, accurate, and useful environment view.
Vehicles without drivers require some form of machine vision for visual object recognition purposes. Autonomous cars are being developed with deep neural networks, a kind of deep learning architecture with many stages of computing, or levels, in which neurons are simulated from environments that activate the network. Neural networks rely on very much data taken from real-life driving scenarios, allowing neural networks to "learn" how to perform the best course of action.
In May 2018, researchers from MIT announced that they had built an autonomous car that could navigate uncharted roads. Researchers at their Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a new system, called MapLite, which allows self-driving cars to drive on roads they've never visited before, without using 3D maps. This system incorporates vehicle GPS positions, "sparse topology maps" such as OpenStreetMap, (ie features 2D from the road only), and a series of sensors that observe road conditions.
Test
Testing vehicles of varying degrees of autonomy can be done physically, in closed environments, on public roads (where permitted, usually by license or permit or adheres to certain set of operating principles) or virtually, in computer simulations.
When driving on a public road, an autonomous vehicle requires someone to monitor their proper operation and "take over" when needed.
Apple is currently testing self-propelled cars, and has increased the number of test vehicles from 3 to 27 in January 2018. This number increased to 45 in March 2018.
One way to assess the progress of an autonomous vehicle is to calculate the average number of miles driven between "discharges", when the autonomous system is turned off, usually by a human driver. By 2017, Waymo reported 63 discharges during a 352,545 mile test, or an average of 5596 miles, the highest among companies reporting those numbers. Waymo also traveled more miles than others. The 2017 rate of 0.18 discharges per 1000 miles represents an increase of 0.2 discharges per 1000 miles in 2016 and 0.8 by 2015. In March 2017, Uber reported an average of 0.67 miles per discharge. In the last three months of 2017, Cruise Automation (now owned by GM) averages 5224 miles per interruption over 62,689 miles.
Application field
Autonomous truck
Some companies are said to test autonomous technology in semi trucks. Otto, the self-driving truck company acquired by Uber in August 2016, showed their truck on the highway before it was acquired. In May 2017, a San Francisco-based startup announced a partnership with Peterbilt truck manufacturers to test and deploy autonomous technology in Peterbilt vehicles. Google Waymo is also said to test autonomous technology in trucks, but no time is given for the project.
In March 2018, Starsky Robotics, an autonomous trucking company headquartered in San Francisco, completed a 7-mile-long uninstalled drive in Florida without a single human in the truck. Starsky Robotics became the first player in a self-driving truck game to drive in a fully autonomous fashion on public roads without someone inside the cabin.
In Europe, Platooning trucks are considered with the Safe Road Trains for Environment approach.
Automation of vehicles also includes other types of vehicles such as Buses, Trains, Trucks.
Transportation system
In Europe, cities in Belgium, France, Italy and the United Kingdom plan to operate transportation systems for autonomous cars, and Germany, the Netherlands and Spain have allowed public testing in traffic. In 2015, the UK launched a public trial of the LUTZ Pathfinder autonomous pod at Milton Keynes. Beginning in the summer of 2015 the French government allows PSA Peugeot-Citroen to make a test in real-life conditions in the Paris area. The experiments are planned to be extended to other cities such as Bordeaux and Strasbourg in 2016. The alliance between the French company THALES and Valeo (the first provider of its own car park system that complements Audi and Mercedes premiums) is testing its own system. New Zealand plans to use autonomous vehicles for public transport in Tauranga and Christchurch.
Potential benefits
Security
Driving safety experts predict that once technology without drivers has been fully developed, traffic collisions (and resulting in deaths and injuries and costs), caused by human error, such as delayed reaction time, tailgating, rubbernecking, and other forms of distracted transfers or aggressive must be done. much reduced. McKinsey & amp; The company estimates that widespread use of autonomous vehicles can "eliminate 90% of all auto accidents in the United States, prevent up to US $ 190 billion in damages and healthcare costs annually and save thousands of lives."
According to the "TheDrive.com" motorist website operated by Time magazine, none of the driving safety experts they can contact can judge driving under the autopilot system because it has not reached a greater safety level. from the entirely traditional hand-driving.
Welfare
Autonomous cars can reduce labor costs; frees travelers from driving and navigation tasks, thereby replacing the commuter clocks behind the wheel with more time to relax or work; and will also lift barriers to occupants' ability to drive, distract and send messages while driving, getting drunk, prone to seizures, or other distractions. For young people, the elderly, people with disabilities, and low-income citizens, autonomous cars can provide improved mobility. The removal of the steering wheel - along with the remaining rider interface and requirements for each passenger to take forward - positions will give cabin interior greater ergonomic flexibility. Large vehicles, such as motorhomes, will achieve a substantial increase in ease of use.
Traffic
Additional benefits may include higher speed limits; smoother rides; and increased road capacity; and minimize traffic congestion, due to the declining need for higher security gaps and speeds. Currently, the maximum access-throughput or highway access capacity accessible in accordance with the US Highway Capacity Guideline is approximately 2,200 passenger vehicles per hour per lane, with about 5% of the available road space taken by the car. One study estimates that autonomous cars can increase capacity by 273% (~ 8,200 cars per hour per lane). The study also estimated that with 100% of vehicles connected using vehicle-to-vehicle communications, the capacity could reach 12,000 passenger vehicles per hour (up 445% from 2,200 pcs/hour per lane) travel safely at 120 km/h (75 mph ) with the following slit about 6 m (20 feet) to each other. Currently, on the road speed riders keep the guard between 40 to 50 m (130 to 160 feet) from the car in front. Increasing the capacity of this highway can have a significant impact in traffic congestion, especially in urban areas, and even effectively end road congestion in some places. The ability of authorities to regulate traffic flow will increase, given additional data and encourage predictability of behavior. combined with less need for traffic police and even road signs.
Cost cutting
Safer driving is expected to reduce the cost of vehicle insurance. Reducing traffic density and increasing traffic flows due to the widespread use of autonomous cars will also translate into better fuel efficiency.
Related effects
By reducing (mobility and other) mobility costs as services, autonomous cars can reduce the number of individually owned cars, replaced by taxis/pooling and other car sharing services. This can dramatically reduce the need for parking spaces, freeing up scarce land for other uses. It will also dramatically reduce the size of the automotive production industry, with associated environmental and economic effects. Assuming efficiency improvements are not fully offset by increased demand, more efficient traffic flows can free up road space for other uses such as better support for pedestrians and cyclists.
Increased vehicle awareness can assist police by reporting illegal passenger behavior, while possibly enabling other crimes, such as intentionally crashing into other vehicles or pedestrians.
The future of passenger train transportation in the autonomous car era is unclear.
Potential limit and obstacle
In spite of the numerous benefits for increased automation of vehicles, some predictable challenges exist, such as disputes over liabilities, the time required to change existing vehicle stocks from non-autonomous to autonomous, resistance by individuals to loss of control over their cars, car security without drivers, and implementation of a legal framework and government regulatory enforcement for self-driving cars. Other obstacles may be lost from the driver's experience in potentially dangerous situations, ethical issues in situations where autonomous software is forced during an unavoidable accident to choose between some dangerous actions, and possibly Adaptation to Gestures and non-verbal cues that do not adequate by police and pedestrians.
Possible technological barriers to autonomous cars are:
- Artificial Intelligence still can not function properly in a chaotic city environment.
- Potentially compromised car computers, like communication systems between cars.
- Vulnerability of car sensors and navigation systems for various types of weather (such as snow) or deliberate interference, including jam and spoofing.
- Avoiding large animals requires recognition and tracking, and Volvo finds that the software suited for caribou, deer, and deer are not effective with kangaroos.
- Autonomous cars may require high-quality custom maps to operate properly. If these maps may be outdated, they should be able to return to reasonable behavior.
- Competition for desired radio spectrum for car communication.
- The field program capabilities for the system will require careful evaluation of product development and component supply chain.
- The current road infrastructure may require changes in order for the autonomous car to function optimally.
- Non-compliance between people's beliefs about necessary government intervention can lead to delays in receiving autonomous cars on the road. Does the public want no change in existing law, federal regulations, or other solutions; the regulatory framework is likely to produce dissent.
Potential loss
The direct impact of the widespread adoption of autonomous vehicles is the loss of work related to driving in the road transport industry. There may be resistance from professional drivers and unions threatened by job loss. In addition, there may be job losses in public transport services and accident workshops. The auto insurance industry may suffer as technology makes certain aspects of this work obsolete. A paper often quoted by Michael Osborne and Carl Benedikt Frey found that autonomous cars would make a lot of work in excess.
Privacy can be a problem when having the location and position of the vehicle integrated into the interface where others have access to. In addition, there is a risk of automotive hacking through information sharing through the V2V (Vehicle to Vehicle) and V2I (Vehicle to Infrastructure) protocols. There is also the risk of terrorist attacks. The self-driving car is potentially loaded with explosives and used as a bomb.
The lack of stressful driving, more productive time during the trip, and potential savings in time and travel costs can be an incentive to live away from the city, where land is cheaper, and work in the city center, thereby increasing the travel distance and encouraging more urban sprawl, more fuel consumption and increased carbon footprint from urban travel. There is also the risk that traffic congestion may increase, rather than decrease. Appropriate public policies and regulations, such as zoning, pricing, and urban design are required to avoid the negative impact of increasing suburbanisation and long distance travel.
Some believe that once the automation in the vehicle reaches a higher level and becomes reliable, the driver will pay less attention to the road. Research shows that drivers in autonomous cars react later when they have to intervene in critical situations, than if they were driving manually. Depending on the autonomous vehicle capability and the frequency of human intervention required, this may still improve safety compared to driving all humans.
Ethical and moral reasoning are taken into consideration when programming software that decides what action a car does in an accident that can not be avoided; whether an autonomous car will hit a bus, potentially killing people in it; or turning elsewhere, potentially killing its own passengers or the nearest pedestrian. An emerging question that is difficult for programmers to understand is "what decisions should a car make the smallest 'damage' when it comes to people's lives?" Ethical autonomous vehicles are still in the process of being solved and may cause controversy. However, human drivers are known to make ethical decisions that are biased when driving (often unconsciously, such as avoiding damage to themselves). In many cases, human thought and reaction time are too slow to detect future accidents, consider the ethical implications of the options available, and take action to implement ethical choices.
Incident
Mercedes' standalone shipping control system
In 1999, Mercedes introduced Distronic, the first radar-assisted ACC, to the Mercedes-Benz S-Class (W220) and CL-Class. Distronic system is able to adjust the vehicle speed automatically to the car in front to always keep a safe distance to another car on the road.
In 2005, Mercedes perfected the system (from this point called "Distronic Plus") with the Mercedes-Benz S-Class (W221) being the first car to receive an enhanced Distronic Plus system. Distronic Plus can now completely stop the car if necessary on the E-Class and most of the Mercedes sedans. In the episode of Top Gear Jeremy Clarkson demonstrates the effectiveness of a cruise control system in the S-class with a total stop from motor speed to round and out, without touching the pedal.
In 2017, Mercedes has broadly expanded its autonomous drive features on production cars: In addition to the standard Distonia Plus features such as active brake assistance, Mercedes now includes steering pilots, parking pilots, cross-traffic assistance systems, sight cameras with automatic hazard warning and braking ( in terms of animals or pedestrians are on the way for example), and various other autonomous-driving features. In 2016, Mercedes also introduced Active Brake Assist 4, which is the first emergency braking assistant with pedestrian recognition in the market.
Because Mercedes history has gradually applied the progress of their autonomous driving features that have been extensively tested, not many crashes are caused by it being known. One of the known accidents occurred in 2005, when the German news magazine " Stern " was testing the old Distronic system of Mercedes. During testing, the system does not always work on the brakes on time. Ulrich Mellinghoff, then Head of Safety, NVH, and Testing at the Mercedes-Benz Technology Center, stated that some tests failed because the vehicle was being tested in a metal hall, causing problems with the system's radar. Then the iterations of the Distronic system have improved radar and many other sensors, which are not vulnerable to the metal environment anymore. In 2008, Mercedes conducted a study comparing the accident rates of their vehicles equipped with Distronic Plus and vehicles without it, and concluded that those equipped with Distronic Plus had an accident rate of about 20% lower. In 2013, Germany's Formula One driver Michael Schumacher was invited by Mercedes to try to crash a Mercedes C-Class vehicle, which features all the safety features offered by Mercedes for its current production vehicle, which includes Active Blind Spot Assist, Active Assist Lane Maintenance, Plus Brakes, Collision Prevention Aid, Distronic Plus with Steering Assist, Pre-Safe Brake, and Stop & amp; Go Pilot. Due to security features, Schumacher can not hit the vehicle in a realistic scenario.
Tesla Autopilot
In mid-October 2015 Tesla Motors launched version 7 of their software in the US that included the capabilities of Tesla Autopilot. On January 9, 2016, Tesla launched version 7.1 as an over-the-air update, adding a new "summon" feature that allows the car to self-park in a parking lot without a driver in the car. Tesla's autonomous driving features can be classified as somewhere between level 2 and level 3 under the National Highway Traffic Safety Administration of the US Department of Transport (NHTSA) five-level automobile automation. At this level the car can act autonomously but requires the full attention of the driver, who must be ready to take control on the spot. An autopilot should be used only on restricted access roads, and will sometimes fail to detect track markers and release itself. In urban driving systems will not read traffic signals or obey stop signs. The system also does not detect pedestrians or cyclists.
On January 20, 2016 the first known fatal accident from Tesla with Autopilot occurred in China's Hubei province. According to China's 163.com news channel, this marks "China's first crash accident due to Tesla's automated driving (system)." Initially, Tesla showed that the vehicle was severely damaged from the impact that their recorders could not prove to be certain that the car was in Autopilot at the time, but 163.com showed that other factors, such as the car were absolute. failure to take evasive action before a high-speed crash, and a good driver's driving record, seems to indicate a strong possibility that the car was on the Autopilot at the time. A similar fatal accident happened four months later in Florida. In 2018, in the subsequent civil suit between the dead driver's father and Tesla, Tesla does not deny that the car was in the Autopilot at the time of the accident, and sent evidence to the victim's father documenting the fact.
A second known fatal accident involving a vehicle being driven by itself takes place in Williston, Florida on May 7, 2016 while the Tesla Model S electric car is engaged in the Autopilot mode. The occupant was killed in an accident with a tractor-trailer 18 wheels. On June 28, 2016, the National Highway Traffic Safety Administration (NHTSA) opened an official inquiry into an accident that worked with the Florida Highway Patrol. According to NHTSA, preliminary reports indicate an accident occurred when the tractor-trailer turned left in front of Tesla at the intersection on an uncontrolled access highway, and the car failed to apply the brakes. The car continued to run after passing under a truck trailer. The initial evaluation of NHTSA was opened to examine the design and performance of the automated drive system used at the time of the accident, involving a population of approximately 25,000 Model S. cars. On July 8, 2016, NHTSA requested Tesla Motors provide detailed information to the agency about the design, operation and testing of the Autopilot technology -his. The agency also requested details of all design changes and updates for Autopilot since its introduction, and Tesla's planned update schedule for the next four months.
According to Tesla, "neither autopilots nor drivers pay attention to the white side of the tractor-trailer against the bright sky, so the brakes are not applied." The car was trying to drive at full speed under the trailer, "with the bottom of the trailer affecting the Model S. windscreen" Tesla also claims that this is Tesla's first known autopilot death in over 130 million miles (208 million km) driven by his customers with Autopilot involved, but with this statement, Tesla seems to refuse to recognize the claim that January 2016 victims in Hubei China is also the result of an autopilot system error. According to Tesla, there are deaths of every 94 million miles (150 million km) among all types of vehicles in the US. However, this figure also includes the death of a collision, for example, a motorcycle driver with a pedestrian.
In July 2016, the US National Transportation Safety Agency (NTSB) opened an official investigation into the fatal accident while Autopilot was involved. NTSB is an investigative body that has the power to make only policy recommendations. A spokeswoman for the agency said, "It is worth looking at and seeing what we can learn from the event, so when the automation is introduced more broadly, we can do it in the safest way possible." In January 2017, NTSB released a report concluding Tesla not guilty; The investigation revealed that for Tesla cars, the accident rate fell by 40 percent after the Autopilot was installed.
According to Tesla, starting October 19, 2016, all Tesla cars are built with hardware to enable full self-driving capabilities at the highest level of security (SAE Level 5). The hardware includes eight surround cameras and twelve ultrasonic sensors, in addition to front-facing radar with enhanced processing capabilities. The system will operate in "shadow mode" (process without taking action) and send data back to Tesla to upgrade its capabilities until the software is ready for deployment via over-the-air upgrades. After the necessary testing, Tesla expects to activate yourself by the end of 2019 under certain conditions.
Google self-driving car
In August 2012, Google announced that their vehicles had completed more than 300,000 miles of autonomous driving (500,000 km) of accident-free, typically involving about a dozen cars on the road at any given time, and that they started testing with a single driver instead of pairing. At the end of May 2014, Google revealed a new prototype that does not have a steering wheel, accelerator, or brake pedal, and is fully autonomous. As of March 2016, Alphabet has test-driven their fleet in a total autonomous mode of 1,500,000 mi (2,400,000 km). In December 2016, Google Corporation announced that the technology would be split into a new subsidiary named Waymo.
According to Google crash reports, their test car has been involved in 14 crashes, where another driver was wrong 13 times, even though in 2016 the car software caused the accident.
In June 2015, Brin confirmed that 12 vehicles had collisions on that date. Eight involved a rear-end collision at a stop sign or a traffic light, two where the vehicle was brushed aside by another driver, one where another driver rolled over a stop sign, and one in which Google employees controlled the car manually. In July 2015, three Google employees suffered minor injuries when their vehicle ended up behind a car whose driver failed to brake on a traffic light. This is the first time a collision resulted in an injury. On February 14, 2016 a Waymo vehicle tried to avoid sandbags blocking its path. During the maneuver it hit the bus. Google stated, "In this case, we clearly bear responsibility, because if our car does not move, there will be no collision." Google marked the accident as a misunderstanding and learning experience. No injuries were reported in the accident.
Uber
In March 2017, the Uber test vehicle was involved in an accident in Tempe, Arizona when another car failed to produce, reversing the Uber vehicle. There was no injury in the accident.
On December 22, 2017, Uber has completed 2,000,000 miles in an autonomous fashion.
On March 18, 2018, Elaine Herzberg became the first pedestrian to be killed by a driverless car in the United States after being hit by a Uber vehicle, also in Tempe. Herzberg was crossing outside the crossing, about 400 meters from the intersection. The cause of the accident is unclear. This marks the first time a person outside a car that is steered is automatically known to have been killed by the car. The first death of a basically uninvolved third party may raise new questions and concerns about the safety of the autonomous car in general. Some experts say a human driver could avoid a fatal accident. Arizona Governor Doug Ducey subsequently suspended the company's ability to test and operate its autonomous car on a public road on the grounds of "unquestionable failure" of the hope that Uber made public safety a top priority. Uber has withdrawn from all self-driving-car testing in California as a result of the accident. On May 24, 2018 the National Transportation Safety Agency issued a preliminary report.
On November 9, 2017, an autonomous self-driving bus with passengers was involved in an accident with a truck. The truck was found because of the accident, turned to a stationary autonomous bus. Autonomous buses do not take evasive actions or apply defensive driving like flash headlights, honking, or when a passenger comments, "The space shuttle has no ability to back down. The shuttle is just silent."
Policy implications
City planning
According to Wonkblog reporter, if autonomous cars are fully commercially available, they have the potential to be a disturbing innovation with major implications for society. The widespread adoption possibility remains unclear, but if they are used on a large scale, policymakers face a number of unresolved questions about their effects.
One fundamental question is about its effect on travel behavior. Some people believe that they will increase car ownership and car use because it will become easier to use and they will eventually be more useful. This in turn will encourage urban sprawl and ultimately total use of private vehicles. Others argue that it would be easier to share cars and that this would thus prevent direct ownership and reduce total usage, and make cars more efficient form of transport in relation to the present situation.
Policymakers should take a fresh look at how the infrastructure will be built and how money will be allocated to build autonomous vehicles. The need for traffic signals can potentially be reduced by the adoption of smart highways. Due to the intelligent highways and with the help of intelligent technological advances that are carried out by policy changes, dependence on oil imports can be reduced because less time is spent on the road by individual cars that can impact energy policy. On the other hand, autonomous vehicles can increase the overall number of cars on the road that could lead to greater dependence on oil imports if the smart system is insufficient to reduce the impact of more vehicles. However, due to future uncertainty of autonomous vehicles, policymakers may wish to plan effectively by implementing improved infrastructure that could benefit human drivers and autonomous vehicles. Caution should be taken in recognition of public transport and that its use can be greatly reduced if autonomous vehicles are served through infrastructure policy reforms with this resulting in job losses and rising unemployment.
Other disturbing effects will come from the use of autonomous vehicles to carry goods. Self-driving cars have the potential to make home deliveries significantly cheaper, changing retail trade and possibly making hypermarkets and supermarkets redundant. The US government currently defines automation into six levels, starting at the zero level which means the human driver does everything and ends with level five, the automated system does all the driving tasks. Also under current legislation, producers assume all responsibility for authorizing vehicles for use on public roads. This means that as long as the vehicle complies within the regulatory framework, there is no federal legal obstacle specifically for highly automated vehicles being offered for sale. Iyad Rahwan, a professor at the MIT Media lab said, "Most people want to live in a world where cars will minimize casualties, but everyone wants their own cars to protect them by all means." In addition, industry standards and best practices are still needed in the system before it can be considered safe enough under real-world conditions.
Legislation
The Vienna Convention of 1968 on Road Traffic, which was followed by more than 70 countries around the world, established the principles for governing traffic laws. One of the fundamental principles of the Convention is the concept that drivers are always in full control and responsible for the behavior of vehicles in traffic. Technological advances that assist and take over the functions of drivers undermine this principle, implying that most of the runway must be rewritten.
Regulations in the United States
In the United States, countries that do not sign the Vienna Convention, country vehicle codes generally do not envisage - but do not always prohibit - highly automated vehicles. To clarify the legal status and otherwise regulate the vehicle, some states have enacted or are considering a special law. In 2016, 7 states (Nevada, California, Florida, Michigan, Hawaii, Washington, and Tennessee), together with the District of Columbia, have enacted laws for autonomous vehicles. Incidents such as the first fatal accident by the Tesla Autopilot system have led to discussions on revising laws and standards for autonomous cars.
In September 2016, the US National Economic Council and the Department of Transportation issued a federal standard describing how automated vehicles should react if their technology fails, how to protect passengers' privacy, and how motorists 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 arrogant as to discourage innovation.
In June 2011, the Nevada Legislature passed a law to authorize the use of autonomous cars. Nevada thus becomes the first jurisdiction in the world where autonomous vehicles may be legally operated on public roads. According to the law, Nevada's Department of Motor Vehicles (NDMV) is responsible for setting safety and performance standards and the agency is responsible for determining the areas in which autonomous cars can be tested. This law is endorsed by Google in an attempt to conduct further legal testing of cars without Google drivers. Nevada's law defines an autonomous vehicle to be "a motor vehicle that uses artificial intelligence, sensors and coordinates a global positioning system to mobilize itself without the active intervention of the human operator." The law also recognizes that operators do not need to pay attention when the car operates on its own. Google has further lobbied for the exclusion of an uninterrupted driving ban to allow residents to send text messages while sitting behind the wheel, but this is not legal. Furthermore, Nevada regulations require a person behind the wheel and one in the passenger seat during the test.
On February 19, 2016, Assembly Bill No. 2866 introduced in California that will allow fully autonomous vehicles to operate on the road, including those without drivers, steering wheel, accelerator pedals, or brake pedals. The bill states the Department of Motor Vehicles will need to comply with this regulation on July 1, 2018 for this regulation to take effect. The bill has not passed the house of origin.
In September 2016, the US Department of Transportation released the Federal Auto Vehicle Policy, and California published a discussion on the issue in October 2016.
In December 2016, the California Department of Motor Vehicles ordered Uber to move his own vehicle off the road in response to two red light violations. Uber immediately blames the offense on "human error", and has stopped the driver.
Legislation in the EU and in the UK
In 2013, the British government allowed autonomous car testing on public roads. Prior to this, all robotic vehicle testing in the UK had been carried out on private property.
In 2014 the French Government announces that testing autonomous cars on public roads will be allowed by 2015. The 2000 km road will be opened through national territory, especially in Bordeaux, in IsÃÆ'¨re, ÃÆ'Žle-de-France and Strasbourg. At the 2015 ITS World Congress, a conference dedicated to the intelligent transportation system, the first demonstration of autonomous vehicles on the open road in France was conducted in Bordeaux in early October 2015.
By 2015, preemptive claims against automakers like GM, Ford, and Toyota have accused them of "Hawking vehicles that are vulnerable to hackers who can hypothetically control important functions like brakes and steering."
In the spring of 2015, the Swiss Department of Environment, Transport, Energy and Communications (UVEK) allowed Swisscom to test the Volkswagen Passat without drivers on Zurich's streets.
In April 2017 it is possible to conduct general road tests for development vehicles in Hungary, further the construction of a closed test track, the Zala Zala test track, which is suitable for testing highly automated functions also underway near the city of Zalaegerszeg.
Regulations in Asia
In 2016, the Singapore Land Transit Authority in partnership with British automotive supplier Delphi Automotive Plc will launch preparations for piloting an automated taxi fleet for an on-demand autonomous cab service to be implemented by 2017.
Liability
Autonomous car liability is a growing field of law and policy that will determine who is responsible when an autonomous car causes physical damage to a person or property. When autonomous automobiles shift driving responsibilities from human to autonomous car technology, there is a need for existing legal obligations to evolve to fairly identify the right solutions for damage and injury. Increased use of autonomous car technology (eg advanced driver assistance system) not only leads to a gradual shift in driving responsibilities but also reduces the frequency of road accidents. When higher levels of autonomy are introduced commercially (level 3 & 4), the insurance industry stands to see a greater proportion of commercial product lines and liabilities, while private vehicle insurance is shrinking.
Motor vehicle communication system
Private vehicles may benefit from information obtained from other vehicles in the vicinity, especially information relating to traffic congestion and safety hazards. Vehicle communication systems use vehicles and roadside units as communications nodes in a peer-to-peer network, providing each other with information. As a cooperative approach, vehicle communication systems can enable all cooperating vehicles to be more effective. According to the 2010 study by the National Highway Traffic Safety Administration, vehicle communication systems can help avoid up to 79 percent of all traffic accidents.
In 2012, computer scientists at the University of Texas at Austin began to develop intelligent intersections designed for autonomous cars. Intersections will have no traffic lights and no stop sign, rather than using a computer program that will communicate directly with every car on the road.
An efficient intersection management technique called Crossroads is proposed in 2017 for strong delays in the V2I communication network and the worst execution time of the intersection manager.
Among connected cars, unrelated ones is the weakest link and will be increasingly banned from the busy high-speed streets predicted by the Helsinki think tank in January 2016.
Public opinion survey
In the 2011 online survey of 2,006 US and British consumers by Accenture, 49% said they would feel comfortable using a "car without a driver".
A 2012 survey of 17,400 vehicle owners by J.D. Power and Associates found 37% initially said they would be interested in buying a fully autonomous car. However, that figure drops to 20% if it says the technology will cost $ 3,000 more.
In a 2012 survey of about 1,000 German drivers by automotive researchers Puls, 22% of respondents had a positive attitude towards these cars, 10% hesitant, 44% skeptical and 24% hostile.
A 2013 survey of 1,500 consumers in 10 countries by Cisco Systems found 57% "said they would be inclined to ride cars controlled entirely by technologies that do not require human drivers", with Brazil, India and China most keen to believe in autonomous technology.
In a US telephone survey of 2014 by Insurance.com, more than three-quarters of licensed drivers said they would at least consider buying a self-driving car, rising to 86% if car insurance is cheaper. 31.7% said they would not keep driving after an autonomous car was available instead.
In a February 2015 survey of automotive journalists, 46% predicted that Tesla or Daimler would be the first to market with fully autonomous vehicles, while (at 38%) Daimler is predicted to be the most functional, secure, and in autonomous -demand vehicles.
In 2015 a questionnaire survey by Delft University of Technology explores the opinions of 5,000 people from 109 countries with automatic driving. The results show that respondents, on average, find manual driving in the most enjoyable driving mode. 22% of respondents did not want to spend money on a fully automated driving system. Respondents were found to be most concerned about software hacking/abuse, and also concerned about legal and security issues. Finally, respondents from more advanced countries (in terms of lower crash statistics, higher education, and higher incomes) are less comfortable with their vehicle transmission data. The survey also gave results to potential consumer opinion about automakers' auto buying interest, stating that 37% of current owners surveyed were "definitely" or "likely" interested in buying automated cars.
In 2016, a survey in Germany examined the views of 1,603 people, representing in terms of age, gender, and education for the German population, toward a partially, highly, and fully automatic car. The results show that men and women differ in their willingness to use it. Men feel less anxious and more joyful about automated cars, while women show the opposite. The gender distinction to anxiety is specifically spoken between young men and women but declines with the age of the participants.
In 2016, the PwC survey, in the United States, showed 1,584 people, highlighting that "66 percent of respondents say they think autonomous cars may be smarter than average human drivers". People are still worried about safety and most facts have a hacked car. Nevertheless, only 13% of the respondents did not see an advantage in this new type of car.
The Pew Research Center survey of 4,135 US adults conducted 1-15 May 2017 found that many Americans anticipated the significant impact of various automation technologies over their lifetime - from widespread adoption of autonomous vehicles to replacement of all job categories with worker robots.
Moral issues
With the advent of autonomous cars there are various ethical issues that arise. While morally, the introduction of autonomous vehicles to the mass market seems inevitable due to a 90% collision reduction and their accessibility to disabled passengers, the elderly and young, there are still some ethical issues that have not been fully resolved.. It includes, but is not limited to: moral, financial, and criminal responsibility for accidents, decisions the car makes just before the accident (fatal), privacy issues, and potential job loss.
There are different opinions about who should be responsible in the event of an accident, especially with those who are injured. Many experts see the car manufacturer itself responsible for accidents that occur due to technical malfunction or technical errors. In addition to the fact that car manufacturers will be the source of trouble in situations where automobiles fall due to technical problems, there is another important reason why car manufacturers can be responsible: it will encourage them to innovate and invest heavily. fix the problem, not only because of the protection of the brand image, but also because of financial and criminal consequences. However, there are also voices that deny those who use or own a vehicle should be held accountable because they know the risks involved in using the vehicle. Experts advise to introduce taxes or insurance that will protect the owners and users of autonomous vehicles from claims made by accident victims. Other parties who may be responsible in case of technical failure include software engineers who program code for autonomous operation of vehicles, and AV component suppliers.
Putting aside the question of legal responsibility and moral responsibility, the question arises how autonomous vehicles should be programmed to behave in emergency situations where either passengers or other traffic participants are threatened with extinction. A very visual example of the moral dilemma that software engineers or automobile engineers may encounter in operating software programming is explained in ethical thinking experiments, the trolley problem: the trolley conductor has the option of staying on the track planned and executed. more than 5 people, or turn the trolley to a track where it will kill just one person, assuming no traffic on it. There are two main considerations that need attention. First, what moral basis will autonomous vehicle use to make a decision? Second, how can it be translated into software code? Researchers have suggested, in particular, two ethical theories to apply to autonomous vehicle behavior in emergency cases: deontology and utilitarianism. The three laws of the robot Asimov are typical examples of deontological ethics. This theory suggests that autonomous cars need to follow strict written rules that must be followed in any situation. Utilitarianism suggests the idea that any decision should be made on the basis of a goal to maximize utility. This requires the definition of utility that can maximize the number of survivors in an accident. Critics point out that autonomous vehicles must adapt a mix of several theories to be able to respond morally right in case of an accident.
Problems related to privacy arise primarily from autonomous car interconnectivity, making it the only other mobile device that can gather any information about a person. The collection of this information ranges from route tracking taken, sound recording, video recording, preference in media consumed in the car, behavior patterns, to more information flow.
Implementing autonomous vehicles into the mass market may cost up to 5 million jobs in the US alone, making up nearly 3% of the workforce. The work includes taxi drivers, buses, vans, trucks, and e-hailing vehicles. Many industries, such as the automotive insurance industry are indirectly affected. The industry alone generates annual revenues of about $ 220 billion, supporting 277,000 jobs. To put this into perspective - it is about the amount of engineering machinery work. The potential loss of most of these jobs because the estimated drop in accidents by up to 90% will have a tremendous impact on the people involved. Both India and China have put a ban on automated cars with protection that mentions previous jobs.
Suspected launch of self-driving car
In December 2015, CEO Tesla Elon Musk predicted that a fully autonomous car would be introduced by the end of 2018; in December 2017, he announced that it would take two more years to launch his own Tesla into the market.
BMW's all-electric autonomous car, called iNext, is expected to be ready by 2021; Toyota's first self-driving car is due to hit the market in 2020, like a car without a driver developed by Nissan. According to the International Organization for the Prevention of Road Accidents, over 90% of the causes of accidents are human error or negligence to traffic rules and also Appropriate with Market Insight, about 30,000 lives can be saved annually in the US alone. Thus, the requirement to reduce the accidental death rate on the road will provide a boost to the autonomous car market as a whole during the forecast period.
In fiction
In the movie
The story of an autonomous self-driving car and sometimes life has earned its place in science fiction literature and sci-fi pop.
- The VW Beetle was named the Dudu feature in German Superbug (film series) 1978 to 1978 from a movie similar to Disney's Herbie but with an electronic brain. (Herbie, also Beetle, is portrayed as an anthropomorphic car in its own spirit.)
- In the movie Batman (1989), starring Michael Keaton, Batmobile is proven to be driving to Batman's current location with several navigation commands from Batman and possibly some autonomy.
- Movie Total Recall (1990), starring Arnold Schwarzenegger, features a cab called Johnny Cabs controlled by artificial intelligence in cars or residents of Android. The film Demolition Man (1993), starring Sylvester Stallone and set in 2032, features self-propelled or ordered vehicles to "Automatic Mode" where a voice-controlled computer operates a vehicle.
- The Timecop film (1994), starring Jean-Claude Van Damme, set in 2004 and 1994, has an autonomous car.
- Another Arnold Schwarzenegger movie, The 6th Day (2000), featuring an autonomous car ordered by Michael Rapaport.
- Movie Minority Report (2002), created in Washington, D.C. in 2054, featuring a long pursuit sequence involving autonomous cars. Vehicle protagonist John Anderton transported it when his system was overwritten by police in an attempt to bring him into custody.
- The movie, The Incredibles (2004), Mr. Incredible keeps his car autonomous for him while it turns him into a supersuit while driving to save the cat from the tree.
In the literature
Source of the article : Wikipedia
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