Engineering:Automated driving system

From HandWiki

An automated driving system is a complex combination of various components that can be defined as systems where perception, decision making, and operation of the automobile are performed by electronics and machinery instead of a human driver, and as introduction of automation into road traffic. This includes handling of the vehicle, destination, as well as awareness of surroundings. While the automated system has control over the vehicle, it allows the human operator to leave all responsibilities to the system.

Automated vehicle system technology hierarchy

Overview

The automated driving system is generally an integrated package of individual automated systems operating in concert. Automated driving implies that the driver have given up the ability to drive (i.e., all appropriate monitoring, agency, and action functions) to the vehicle automation system. Even though the driver may be alert and ready to take action at any moment, automation system controls all functions.

Automated driving systems are often conditional, which implies that the automation system is capable of automated driving, but not for all conditions encountered in the course of normal operation. Therefore, a human driver is functionally required to initiate the automated driving system, and may or may not do so when driving conditions are within the capability of the system. When the vehicle automation system has assumed all driving functions, the human is no longer driving the vehicle but continues to assume responsibility for the vehicle's performance as the vehicle operator. The automated vehicle operator is not functionally required to actively monitor the vehicle's performance while the automation system is engaged, but the operator must be available to resume driving within several seconds of being prompted to do so, as the system has limited conditions of automation. While the automated driving system is engaged, certain conditions may prevent real-time human input, but for no more than a few seconds. The operator is able to resume driving at any time subject to this short delay. When the operator has resumed all driving functions, he or she reassumes the status of the vehicle's driver.

Success in the technology

AAA Foundation for Traffic Safety conducted a test of two automatic emergency braking systems: those 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 both a moving and nonmoving target. It found that systems capable of preventing crashes reduced vehicle speeds by twice that of the systems designed to merely mitigate crash severity. When the two test vehicles traveled within 30 mph of each other, even those designed to simply lessen crash severity avoided crashes 60 percent of the time.[1]

The success in the automated driving system has been known to be successful in situations like rural road settings. Rural road settings would be a setting in which there is lower amounts of traffic and lower differentiation between driving abilities and types of drivers. "The greatest challenge in the development of automated functions is still inner-city traffic, where an extremely wide range of road users must be considered from all directions." [2] This technology is progressing to a more reliable way of the automated driving cars to switch from auto-mode to driver mode. Auto-mode is the mode that is set in order for the automated actions to take over, while the driver mode is the mode set in order to have the operator controlling all functions of the car and taking the responsibilities of operating the vehicle (Automated driving system not engaged).

This definition would include vehicle automation systems that may be available in the near term—such as traffic-jam assist, or full-range automated cruise control—if such systems would be designed such that the human operator can reasonably divert attention (monitoring) away from the performance of the vehicle while the automation system is engaged. This definition would also include automated platooning (such as conceptualized by the SARTRE project).

The SARTRE Project

The SARTRE project's main goal is to create platooning, a train of automated cars, that will provide comfort and have the ability for the driver of the vehicle to arrive safely to a destination. Along with the ability to be along the train, drivers that are driving past these platoons, can join in with a simple activation of the automated driving system that correlates with a truck that leads the platoon. The SARTRE project is taking what we know as a train system and mixing it with automated driving technology. This is intended to allow for an easier transportation though cities and ultimately help with traffic flow through heavy automobile traffic.

SARTRE & modern day

In some parts of the world the self-driving car has been tested in real life situations such as in Pittsburgh.[3] The Self-driving Uber has been put to the test around the city, driving with different types of drivers as well as different traffic situations. Not only have there been testing and successful parts to the automated car, but there has also been extensive testing in California on automated busses. The lateral control of the automated buses uses magnetic markers such as the platoon at San Diego, while the longitudinal control of the automated truck platoon uses millimeter wave radio and radar. Current examples around today's society include the Google car and Tesla's models. Tesla has redesigned automated driving, they have created car models that allow drivers to put in the destination and let the car take over. These are two modern day examples of the automated driving system cars.

Levels of automation according to SAE

The U.S Department of Transportation National Highway Traffic Safety Administration (NHTSA) provided a standard classification system in 2013 which defined five different levels of automation, ranging from level 0 (no automation) to level 4 (full automation).[4] Since then, the NHTSA updated their standards to be in line with the classification system defined by SAE International.[5] SAE International defines six different levels of automation in their new standard of classification in document SAE J3016 that ranges from 0 (no automation) to 5 (full automation).[6]

Level 0 – No automation

The driver is in complete control of the vehicle and the system does not interfere with driving.[6] Systems that may fall into this category are forward collision warning systems and lane departure warning systems.[7]

Level 1 – Driver assistance

The driver is in control of the vehicle, but the system can modify the speed and steering direction of the vehicle.[6] Systems that may fall into this category are adaptive cruise control and lane keep assist.[7]

Level 2 – Partial automation

The driver must be able to control the vehicle if corrections are needed, but the driver is no longer in control of the speed and steering of the vehicle.[6] Parking assistance is an example of a system that falls into this category[7] along with Tesla's autopilot feature.[8] A system that falls into this category is the DISTRONIC PLUS system created by Mercedes-Benz.[9] It is important to note the driver must not be distracted in Level 0 to Level 2 modes.

Level 3 – Conditional automation

The system is in complete control of vehicle functions such as speed, steering, and monitoring the environment under specific conditions. Such specific conditions may be fulfilled while on fenced-off highway with no intersections, limited driving speed, boxed-in driving situation etc. A human driver must be ready to intervene when requested by the system to do so.[6] If the driver does not respond within a predefined time or if a failure occurs in the system, the system needs to do a safety stop in ego lane (no lane change allowed) [citation needed]. The driver is only allowed to be partially distracted, such as checking text messages, but taking a nap is not allowed.

Level 4 – High automation

The system is in complete control of the vehicle and human presence is no longer needed, but its applications are limited to specific conditions.[6] An example of a system being developed that falls into this category is the Waymo self-driving car service.[10] If the actual motoring condition exceeds the performance boundaries, the system does not have to ask the human to intervene but can choose to abort the trip in a safe manner, e.g. park the car.

Level 5 – Full automation

The system is capable of providing the same aspects of a Level 4, but the system can operate in all driving conditions.[6] The human is equivalent to "cargo" in Level 5[citation needed]. Currently, there are no driving systems at this level.[11]

Risks and liabilities

Many automakers such as Ford and Volvo have announced plans to offer fully automated cars in the future.[12] Extensive research and development is being put into automated driving systems, but the biggest problem automakers cannot control is how drivers will use system.[12] Drivers are stressed to stay attentive and safety warnings are implemented to alert the driver when corrective action is needed.[13] Tesla Motor's has one recorded incident that resulted in a fatality involving the automated driving system in the Tesla Model S.[14] The accident report reveals the accident was a result of the driver being inattentive and the autopilot system not recognizing the obstruction ahead.[14]

Another flaw with automated driving systems is that in situations where 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.[13]

To overcome some of the challenges for automated driving systems, novel methodologies based on virtual testing, traffic flow simulatio and digital prototypes have been proposed,[15], especially when novel algorithms based on Artificial Intelligence approaches are employed which require extensive training and validation data sets.

The implementation of automated driving systems poses the possibility of changing build environments in urban areas, such as the expansion of suburban areas due to the increased ease of mobility.[16]

See also

  • Autonomous car

References

  1. ↑ "AAA Studies Technology Behind Self-Driving Cars" (in en-US). 2019-02-18. https://magazine.northeast.aaa.com/daily/life/technology/aaa-studies-technology-behind-self-driving-cars/. 
  2. ↑ "The next steps". http://products.bosch-mobility-solutions.com/en/de/specials/specials_safety/automated_driving/technology_and_development_1/challenge_1/challenge.html. 
  3. ↑ "Pittsburgh, your Self-Driving Uber is arriving now" (in en-US). Uber Global. 2016-09-14. https://newsroom.uber.com/pittsburgh-self-driving-uber/. 
  4. ↑ "U.S. Department of Transportation Releases Policy on Automated Vehicle Development". http://www.nhtsa.gov/About-NHTSA/Press-Releases/U.S.-Department-of-Transportation-Releases-Policy-on-Automated-Vehicle-Development. Retrieved 9 December 2016. 
  5. ↑ "Updated: Autonomous driving levels 0 to 5: Understanding the differences". http://www.techrepublic.com/article/autonomous-driving-levels-0-to-5-understanding-the-differences/. Retrieved 9 December 2016. 
  6. ↑ 6.0 6.1 6.2 6.3 6.4 6.5 6.6 "AUTOMATED DRIVING LEVELS OF DRIVING AUTOMATION ARE DEFINED IN NEW SAE INTERNATIONAL STANDARD J3016". http://www.sae.org/misc/pdfs/automated_driving.pdf. Retrieved 9 December 2016. 
  7. ↑ 7.0 7.1 7.2 Etemad, Aria; Bartels, Arne. "A Stepwise Market Introduction of Automated Driving". https://www.adaptive-ip.eu/files/adaptive/content/downloads/Deliverables%20&%20papers/AdaptIVe-ITS-WC%202014_A%20Stepwise%20Market%20Introduction%20of%20Automated%20Driving_V02.pdf. Retrieved 9 December 2016. 
  8. ↑ Assis, Claudia. "Tesla's latest autopilot update is still not hands free". http://www.marketwatch.com/story/teslas-latest-autopilot-update-is-still-not-hands-free-2015-10-14. Retrieved 9 December 2016. 
  9. ↑ "DISTRONIC PLUS". https://www.mbusa.com/mercedes/owners/videos/detail/videoId-6f31735fd7cee310VgnVCM1000007c184335RCRD. Retrieved 9 December 2016. 
  10. ↑ "Google Self-Driving Car Project". https://www.google.com/selfdrivingcar/faq/. Retrieved 9 December 2016. 
  11. ↑ Luckerson, Victor. "Yep, Driverless Cars Have Power Rankings". https://theringer.com/here-are-your-autonomous-car-power-rankings-dd7a4070e1c0#.u2dvsikj5. Retrieved 9 December 2016. 
  12. ↑ 12.0 12.1 Mearian, Lucas. "Ford remains wary of Tesla-like autonomous driving features". http://www.computerworld.com/article/3109217/car-tech/ford-wary-of-tesla-like-autonomous-driving-features.html. Retrieved 9 December 2016. 
  13. ↑ 13.0 13.1 "Automated Vehicle Technology." King Coal Highway 292 (2014): 23-29.
  14. ↑ 14.0 14.1 "A Tragic Loss". https://www.tesla.com/blog/tragic-loss. Retrieved 10 December 2016. 
  15. ↑ Hallerbach, Sven; Xia, Yiqun; Eberle, Ulrich; Koester, Frank (3 April 2018). "Simulation-based Identification of Critical Scenarios for Cooperative and Automated Vehicles". SAE Technical Paper 2018-01-1066. https://www.researchgate.net/publication/324194968_Simulation-based_Identification_of_Critical_Scenarios_for_Cooperative_and_Automated_Vehicles. Retrieved 23 December 2018. 
  16. ↑ Yigitcanlar; Wilson; Kamruzzaman (2019-04-24). "Disruptive Impacts of Automated Driving Systems on the Built Environment and Land Use: An Urban Planner’s Perspective" (in en). Journal of Open Innovation: Technology, Market, and Complexity 5 (2): 24. doi:10.3390/joitmc5020024. ISSN 2199-8531. https://www.mdpi.com/2199-8531/5/2/24. 




Retrieved from "https://handwiki.org/wiki/index.php?title=Engineering:Automated_driving_system&oldid=241167"