Vehicular automation
Vehicular automation involves the use of mechatronics, artificial intelligence, and multi-agent systems to assist the operator of a vehicle such as a car, lorries, aircraft, or watercraft.[2][3] A vehicle using automation for tasks such as navigation to ease but not replace human control, qualify as semi-autonomous, whereas a fully self-operated vehicle is termed autonomous.[3]
For vehicles relying completely either on automation or remote control, see Uncrewed vehicle.
Automated vehicles may include self-driving cars, unmanned surface vehicles, autonomous trains, advanced airliner autopilots, drone aircraft, and planetary rovers, as well as guided rockets and missiles.
Automated vehicles in the European Union legislation are also more specifically motor vehicles (car, truck or bus).[4] That is a road traffic vehicles. For those vehicles, a specific difference is legally defined between advanced driver-assistance system and (more advanced) autonomous/automated vehicles due to differences of liability for the driver and/or the entity driving the vehicle.
The technology involved in implementing autonomous vehicles ranges from changes to the vehicle to providing support in the driving environment.
Automated vehicles present safety concerns, especially in land transport, and in road traffic, given the complexity of driving, geographical/cultural differences, and road conditions. Various technological challenges need to be overcome to make autonomous vehicles robust and scalable.[5]
Vehicular automation topic is notable for road traffic due to the number of vehicles and drivers but present specific concerns in an environment subject to traffic collisions due to the need to share the road with other road users.
Autonomy implies that the vehicle is responsible for all perceptual, monitoring and control functions. Automated systems may not be capable of operating under all conditions, leaving the rest for a human operator. A further subtlety is that while a vehicle may attempt to operate under all circumstances, the vehicle may require a human to assume control in unanticipated circumstance arises or when the vehicle misbehaves.[6]
Autonomy in motor vehicles is often categorized in six levels:[7] The level system was developed by the Society of Automotive Engineers (SAE).[8]
Level 0 refers, for instance, to vehicles which do not have adaptive cruise control.
Level 1 and 2 refer to vehicles where one part of the driving task is performed by the vehicle advanced driver-assistance systems (ADAS) under the responsibility/accountability/liability of the driver.
From level 3, the driver can conditionally transfer the driving task to the vehicle, but the driver must take back control when the conditional automation is no longer available. For instance an automated traffic jam pilot can drive in the traffic jam but the driver should take back control when traffic jam is over.
Level 5 refers to a vehicle which does not need any (human) driver.
Level 0:
No Driving Automation
Level 1:
Driver Assistance
Level 2:
Partial Driving Automation
Level 3:
Conditional Driving Automation
Level 4:
High Driving Automation
Level 5:
Full Driving Automation[9]
Technology used in vehicular automation[edit]
The primary means of implementing autonomous vehicles is through the use of Artificial Intelligence (AI). In order for full autonomous vehicles to be implemented, the lower levels of automation must be thoroughly tested and implemented before moving on to the next level.[10] Through implementing autonomous systems, such as navigation, collision avoidance and steering, autonomous vehicle manufacturers work towards higher levels of autonomy by designing and implementing different systems of the car.[10] These autonomous systems, along with the use of artificial intelligence methods, can use the machine learning aspect of AI in order for the vehicle to control each of the other autonomous systems and processes. Thus, autonomous vehicle manufacturers are researching and developing appropriate AI specifically for autonomous vehicles.[11] While many of these companies are continuously developing technologies to be implemented into their autonomous vehicles, the general consensus is that the underlying technology is still in need of further development before fully autonomous vehicles are possible.[12]
Arguably one of the most important systems of any autonomous vehicle, the perception system must be fully developed and well-tested in order for autonomy to advance.[12] With the development and implementation of the perception system on autonomous vehicles, much of the safety standards of autonomous vehicles are being addressed by this system, which places an unequivocal emphasis on it to be flawless, as human lives would be subject to harm if a faulty system were to be developed.[12] The main purpose for the perception system is to constantly scan the surrounding environment and determine which objects in the environment pose a threat to vehicles.[12] In a sense, the perception system's main goal is to act like human perception, allowing the system to sense hazards and to prepare or correct for these hazards.[12] In terms of the detection part of the perception system, many solutions are being tested for accuracy and compatibility, such as radar, lidar, sonar and moving image processing.[12]
With the development of these autonomous subsystems of the car, autonomous vehicle manufacturers have already developed systems which act as assistance features on a vehicle. These systems are known as advanced driver-assistance systems, and contain systems to do such actions as parallel parking and emergency braking.[11] Along these systems, autonomous navigation systems play a role in the development of autonomous vehicles. In implementing the navigation system, there are two ways in which navigation can be implemented: sensing from one vehicle to another or sensing from the infrastructure.[11] These navigation systems would work in tandem with already well established navigation systems, such as the Global Positioning System (GPS), and be able to process route information, detecting such things as traffic jams, tolls and or road construction. From this information, the vehicle can then take the appropriate action to either avoid the area or plan accordingly.[12] However, there may be problems in using this method, such as outdated information, in which case vehicle to infrastructure communication can play a large role in constantly having up-to-date information.[12] An instance of this is having street signs and other regulatory markers display information to the vehicle, which allows the vehicle to make decisions based on the current information.[12]
Along with the development of autonomous vehicles, many of these vehicles are expected to be primarily electric, meaning that the main power source of the vehicle will be battery-based rather than fossil fuel-based.[10] Along with that, there comes the extra demand on autonomous vehicle manufacturers to produce higher quality electric cars in order to implement all the autonomous systems associated with the vehicle.[13] However, much of modern-day vehicle components can still be used in autonomous vehicles, such as the use of the automatic transmissions and operator protection equipment like airbags.[13]
In consideration of the development of autonomous vehicles, companies also are considering operator preferences and needs. These instances include allowing the user to minimize time, follow a precise route and accommodate any possible disabilities that the operator may have.[14] Along with accommodating the driver, autonomous vehicles also impose a technological factor onto the environment around it, generally needing a higher sense of connectivity in the vehicle's environment. With this new factor to consider, many urban governments are considering becoming a smart city in order to provide a sufficient foundation for autonomous vehicles.[14] Along these same lines of the vehicle's environment accommodating the vehicle, the user of these vehicles may also have to be technologically connected in order to operate these autonomous vehicles. With the advent of smartphones, it is predicted that autonomous vehicles will be able to have this connection with the user's smartphone or other technological devices similar to a smartphone.[14]
Assistance robots[edit]
Spot[edit]
This robot is a four-legged nimble robot that was created to be able to navigate through many different terrain outdoors and indoors. It can walk on its own without colliding into anything. It utilizes many different sensors, including 360 vision cameras and gyroscopes. It is able to keep its balance even when pushed over. This vehicle, while it is not intended to be ridden, can carry heavy loads for construction workers or military personnel through rough terrain.[151]
Concerns[edit]
Lack of control[edit]
Through the autonomy level, it is shown that the higher the level of autonomy, the fewer control humans have on their vehicles (highest level of autonomy needing zero human interventions). One of the few concerns regarding the development of vehicular automation is related to the end-users’ trust in the technology that controls automated vehicles.[153] According to a nationally conducted survey made by Kelley Blue Book (KBB) in 2016, it is shown that the majority of people would still choose to have a certain level of control behind their own vehicle rather than having the vehicle operate in Level 5 autonomy, or in other words, completely autonomous.[154] According to half of the respondents, the idea of safety in an autonomous vehicle diminishes as the level of autonomy increases.[154] This distrust of autonomous driving systems proved to be unchanged throughout the years when a nationwide survey conducted by AAA Foundation for Traffic and Safety (AAAFTS) in 2019 showed the same outcome as the survey KBB did in 2016. AAAFTS survey showed that even though people have a certain level of trust in automated vehicles, most people also have doubts and distrust towards the technology used in autonomous vehicles, with most distrust in Level 5 autonomous vehicles.[155] It is shown by AAAFTS’ survey that people's trust in autonomous driving systems increased when their level of understanding increased.[155]