Vehicular automation

 ( Ethics Of Science And Technology ) 

AAA Foundation for Traffic Safety tested two automatic emergency braking systems: some designed to prevent crashes and others that aim to make a crash less severe. The test looked at popular models like the 2016 Volvo XC90, Subaru Legacy, Lincoln MKX, Honda Civic, and Volkswagen Passat. Researchers tested how well each system stopped when approaching moving and nonmoving targets. It found that systems capable of preventing crashes reduced vehicle speeds by twice that of the systems designed to mitigate crash severity. When the two test vehicles traveled within 30 mph of each other, even those designed to lessen crash severity avoided crashes 60 percent of the time.

Drivers are directed to stay attentive, and safety warnings are implemented to alert the driver when corrective action is needed."Automated Vehicle Technology." King Coal Highway 292 (2014): 23-29. Tesla, Incorporated has one recorded incident that resulted in a fatality involving the automated driving system in the Tesla Model S. The accident report reveals the accident was a result of the driver being inattentive and the autopilot system not recognizing the obstruction ahead. Tesla has also had multiple instances where the vehicle crashed into a garage door. According to the book "The Driver in the Driverless Car: How Your Technology Choices Create the Future," Tesla automatically performs an update overnight. The morning after the update, the driver used his app to "summon" his car, and it crashed into his garage door.

Another flaw with automated driving systems is that unpredictable events, such as weather or the driving behavior of others, may cause fatal accidents due to sensors that monitor the surroundings of the vehicle not being able to provide corrective action.

To overcome some of the challenges for automated driving systems, novel methodologies based on virtual testing, traffic flow simulation and digital prototypes have been proposed, especially when novel algorithms based on Artificial Intelligence approaches are employed which require extensive training and validation data sets.

Implementing automated driving systems poses the possibility of changing built environments in urban areas, such as expanding the suburban regions due to the increased ease of mobility.

There are still many obstacles in developing fully autonomous Level 5 vehicles, which is the ability to operate in any conditions. Currently, companies are focused on Level 4 automation, which is able to operate under certain environmental circumstances.

There is still debate about what an autonomous vehicle should look like. For example, whether to incorporate lidar to autonomous driving systems is still being argued. Some researchers have come up with algorithms using camera-only data that achieve the performance that rival those of lidar. On the other hand, camera-only data sometimes draw inaccurate bounding boxes, and thus lead to poor predictions. This is due to the nature of superficial information that provide, whereas incorporating lidar gives autonomous vehicles precise distance to each point on the vehicle.

• Software Integration: Because of the large number of sensors and safety processes required by autonomous vehicles, software integration remains a challenging task. A robust autonomous vehicle should ensure that the integration of hardware and software can recover from component failures.
• Prediction and trust among autonomous vehicles: Fully autonomous cars should be able to anticipate the actions of other cars like humans do. Human drivers are great at predicting other drivers' behaviors, even with a small amount of data such as eye contact or hand gestures. In the first place, the cars should agree on traffic rules, whose turn it is to drive in an intersection, and so on. This scales into a larger issue when there exists both human-operated cars and self-driving cars due to more uncertainties. A robust autonomous vehicle is expected to improve on understanding the environment better to address this issue.
• Scaling up: The coverage of autonomous vehicles testing could not be accurate enough. In cases where heavy traffic and obstruction exist, it requires faster response time or better tracking algorithms from the autonomous vehicles. In cases where unseen objects are encountered, it is important that the algorithms are able to track these objects and avoid collisions.

These features require numerous sensors, many of which rely on MEMS (MEMS) to maintain a small size, high efficiency, and low cost. Foremost among MEMS sensors in vehicles are and to measure acceleration around multiple orthogonal axes—critical to detecting and controlling the vehicle's motion.

• The usefulness factor studies whether or not autonomous vehicles are useful in that they provide benefits that save consumers' time and make their lives simpler. How well the consumers believe autonomous vehicles will be useful compared to other forms of transportation solutions is a determining factor.
• The ease to use factor studies the user-friendliness of the autonomous vehicles. While the notion that consumers care more about ease to use than safety has been challenged. It still remains an important factor that has indirect effects on the public's intention to use autonomous vehicles.
• The trust factor studies the safety, data privacy and security protection of autonomous vehicles. A more trusted system has a positive impact on the consumer's decision to use autonomous vehicles.
• The social influence factor studies whether the influence of others would influence consumer's likelihood of having autonomous vehicles. Studies have shown that the social influence factor is positively related to behavioral intention. This might be due to the fact that cars traditionally serve as a status symbol that represents one's intent to use and his social environment.

This amendment will enter into force on 14 July 2022, unless it is rejected before 13 January 2022.

Ground vehicles employing automation and teleoperation include shipyard gantries, mining trucks, bomb-disposal robots, robotic insects, and driverless tractors.

There are many autonomous and semi-autonomous ground vehicles being made for the purpose of transporting passengers. One such example is the free-ranging on grid (FROG) technology which consists of autonomous vehicles, a magnetic track and a supervisory system. The FROG system is deployed for industrial purposes in factory sites and has been in use since 1999 on the ParkShuttle, a PRT-style public transport system in the city of Capelle aan den IJssel to connect the Rivium business park with the neighboring city of Rotterdam (where the route terminates at the Kralingse Zoom metro station). The system experienced a crash in 2005 that proved to be caused by a human error.

Applications for automation in ground vehicles include the following:

• Vehicle tracking system system ESITrack, Lojack.
• Rear-view alarm, to detect obstacles behind.
• Anti-lock braking system (ABS) (also Emergency Braking Assistance (EBA)), often coupled with Electronic brake force distribution (EBD), which prevents the brakes from locking and losing traction while braking. This shortens stopping distances in most cases and, more importantly, allows the driver to steer the vehicle while braking.
• Traction control system (TCS) actuates brakes or reduces throttle to restore traction if driven wheels begin to spin.
• Four wheel drive (AWD) with a centre differential. Distributing power to all four wheels lessens the chances of wheel spin. It also suffers less from oversteer and understeer.
• Electronic Stability Control (ESC) (also known for Mercedes-Benz proprietary Electronic Stability Program (ESP), Acceleration Slip Regulation (ASR) and Electronic differential lock (EDL)). Uses various sensors to intervene when the car senses a possible loss of control. The car's control unit can reduce power from the engine and even apply the brakes on individual wheels to prevent the car from or .
• Dynamic steering response (DSR) corrects the rate of power steering system to adapt it to vehicle's speed and road conditions.

Research is ongoing and prototypes of autonomous ground vehicles exist.

Semi-autonomous designs could be implemented sooner as they rely less on technology that is still at the forefront of research. An example is the dual mode monorail. Groups such as RUF (Denmark) and TriTrack (USA) are working on projects consisting of specialized private cars that are driven manually on normal roads but also that dock onto a monorail/guideway along which they are driven autonomously.

As a method of automating cars without extensively modifying the cars as much as a robotic car, Automated highway systems (AHS) aims to construct lanes on highways that would be equipped with, for example, magnets to guide the vehicles. Automation vehicles have auto-brakes named as Auto Vehicles Braking System (AVBS). Highway computers would manage the traffic and direct the cars to avoid crashes.

In 2006, The European Commission has established a smart car development program called the Intelligent Car Flagship Initiative. The goals of that program include:

• Adaptive cruise control
• Lane departure warning system
• Project AWAKE for drowsy drivers

There are further uses for automation in relation to cars. These include:

• Assured Clear Distance Ahead
• Adaptive headlamps
• Advanced Automatic Collision Notification, such as OnStar
• Intelligent Parking Assist System
• Automatic Parking
• Automotive night vision with pedestrian detection
• Blind spot monitoring
• Driver Monitoring System
• Robotic car or self-driving car which may result in less-stressed "drivers", higher efficiency (the driver can do something else), increased safety and less pollution (e.g. via completely automated gasoline control)
• Precrash system
• Safe speed governing
• Traffic sign recognition
• Following another car on a motorway – "enhanced" or "adaptive" cruise control, as used by Ford Motor Company and Vauxhall
• Distance control assist – as developed by Nissan
• Dead man's switch – there is a move to introduce deadman's braking into automotive application, primarily heavy vehicles, and there may also be a need to add to .

Singapore also announced a set of provisional national standards on January 31, 2019, to guide the autonomous vehicle industry. The standards, known as Technical Reference 68 (TR68), will promote the safe deployment of fully driverless vehicles in Singapore, according to a joint press release by Enterprise Singapore (ESG), Land Transport Authority (LTA), Standards Development Organisation and Singapore Standards Council (SSC).

In the 2010s, self-driving shuttle became able to run in mixed traffic without the need for embedded guidance markers. So far the focus has been on low speed, , with short, fixed routes for the "last mile" of journeys. This means issues of collision avoidance and safety are significantly less challenging than those for automated cars, which seek to match the performance of conventional vehicles. Many trials have been undertaken, mainly on quiet roads with little traffic or on public pathways or private roadways and specialised test sites. The capacity of different models varies significantly, between 6-seats and 20-seats. (Above this size there are conventional buses that have driverless technology installed.)

In December 2016, the Jacksonville Transportation Authority has announced its intention to replace the Jacksonville Skyway monorail with driverless vehicles that would run on the existing elevated superstructure as well as continue onto ordinary roads. The project has since been named the "Ultimate Urban Circulator" or "U2C" and testing has been carried out on shuttles from six different manufacturers. The cost of the project is estimated at $379 million.

In January 2017, it was announced the ParkShuttle system in the Netherlands will be renewed and expanded including extending the route network beyond the exclusive right of way so vehicles will run in mixed traffic on ordinary roads. The plans were delayed and the extension into mixed traffic was expected in 2021.

In July 2018, Baidu stated it had built 100 of its 8-seat Apolong model, with plans for commercial sales. As of July 2021, they had not gone into volume production.

In August 2020, it was reported there were 25 autonomous shuttle manufacturers, including the ParkShuttle, Local Motors, Navya SAS, Baidu, Easymile, Toyota and Ohmio.

In December 2020, Toyota showcased its 20-passenger "e-Palette" vehicle, which is due to be used at the 2021 Tokyo Olympic Games. Toyota announced it intends to have the vehicle available for commercial applications before 2025.

In January 2021, Navya released an investor report which predicted global autonomous shuttle sales will reach 12,600 units by 2025, with a market value of EUR 1.7 billion.

In June 2021, Chinese maker Yutong claimed to have delivered 100 models of its 10-seat Xiaoyu 2.0 autonomous bus for use in Zhengzhou. Testing has been carried out in a number of cities since 2019 with trials open to the public planned for July 2021.

Self-driving shuttles are already in use on some private roads, such as at the Yutong factory in Zhengzhou where they are used to transport workers between buildings of the world's largest bus factory.

The first autonomous bus trial in the United Kingdom commenced in mid-2019, with an Alexander Dennis Enviro200 MMC single-decker bus modified with autonomous software from Fusion Processing able to operate in driverless mode within Stagecoach Manchester's Sharston bus depot, performing tasks such as driving to the washing station, refueling point and then parking at a dedicated parking space in the depot. Passenger-carrying driverless bus trials in Scotland commenced in January 2023, with a fleet of five identical vehicles to the Manchester trial used on a Stagecoach Fife park-and-ride route across the Forth Road Bridge, from the north bank of the Forth to Edinburgh Park station.

Another autonomous trial in Oxfordshire, England, which uses a battery electric Fiat Ducato minibus on a circular service to Milton Park, operated by FirstBus with support from Fusion Processing, Oxfordshire County Council and the University of the West of England, entered full passenger service also in January 2023. The trial route will be extended to Didcot Parkway railway station after acquiring a larger single-decker by the end of 2023.

In July 2020 in Japan, AIST Human-Centered Mobility Research Center with Nippon Koei and Isuzu started a series of demonstration tests for mid-sized buses, Isuzu "Erga Mio" with autonomous driving systems, in five areas; Ōtsu city in Shiga prefecture, Sanda city in Hyōgo Prefecture and other three areas in sequence.

In October 2023, Imagry, an Israeli AI startup, introduced its mapless autonomous driving solution at Busworld Europe, leveraging a real-time image recognition system and a spatial deep convolutional neural network (DCNN) to mimic human driving behavior.

Companies such as Suncor Energy, a Canadian energy company, and Rio Tinto Group were among the first to replace human-operated trucks with driverless commercial trucks run by computers. In April 2016, trucks from major manufacturers including Volvo and the Daimler Company completed a week of autonomous driving across Europe, organized by the Dutch, in an effort to get self-driving trucks on the road. With developments in self-driving trucks progressing, U.S. self-driving truck sales is expected to reach 60,000 by 2035 according to a report released by IHS Incorporated in June 2016.

As reported in June 1995 in Popular Science magazine, self-driving trucks were being developed for combat convoys, whereby only the lead truck would be driven by a human and the following trucks would rely on satellite, an inertial guidance system and ground-speed sensors. Caterpillar Incorporated made early developments in 2013 with the Robotics Institute at Carnegie Mellon University to improve efficiency and reduce cost at various mining and construction sites.