Critical aspects when implementing artificial intelligence in the industry of unmanned vehicles

DOI: 10.31673/2786-8362.2023.010303

Abstract

The article is devoted to critical aspects during the implementation of artificial intelligence in the field of unmanned vehicles. The task is to determine the critical aspects that will have a negative impact based on the analysis of the introduction of artificial intelligence to solve the set of tasks of managing an unmanned vehicle in the external environment. To solve this problem in the article: an analysis of the methods of full autonomy of vehicles is performed and the classification of control systems of unmanned vehicles in the external environment is considered; a description of the levels of autonomy/automation of the Automated driving system, which allow distinguishing autonomous vehicles based on the SAE J3016 standard; performed analysis of tasks of each level regarding the possibility of applying artificial intelligence; explore the possibilities of driverless vehicle control systems using a variety of automotive computer networks, in which vehicles and roadside devices are communication nodes providing each other with information such as safety warnings and traffic information.
Based on the analysis, the following conclusions are drawn: firstly, to manage a fully autonomous system of an unmanned vehicle, it is necessary to use artificial intelligence, which will be able to process information from navigation aids, sensors and means of communication between unmanned vehicles in the external environment in a timely manner; secondly, it will require a complex multi-level artificial intelligence system with a single interface to make the right decisions at the right time to achieve the intended result requires; thirdly, the use of artificial intelligence in the field of unmanned vehicles today faces the problem of the need to have large computing power on this autonomous vehicle, which leads to the appearance of critical aspects, namely: the problem of power supply and cooling of many processors in the computing system.

Keywords: intelligent systems, vulnerability of autonomous driving, autonomous vehicle.

References:
1. National Highway Traffic Safety Administration US / [електронний ресурс] – режим доступу: / https://www.nhtsa.gov/(Дата перегляду 20 червня 2023).
2. Statistical Annex, World report on road traffic injury prevention/ [електронний ресурс] – режим доступу: / https://en.wikipedia.org/wiki/Road_traffic_safety#cite_note-5/(Дата перегляду 20 червня 2023).
3. "World report on road traffic injury prevention". World Health Organisation. Retrieved 14 April 2010. / https://en.wikipedia.org/wiki/Road_traffic_safety#cite_note-5/(Дата перегляду 20 червня 2023).
4. Про схвалення Концепції Державної цільової програми підвищення рівня безпеки дорожнього руху в Україні на період до 2016 року/ [електронний ресурс] – режим доступу: /https://zakon.rada.gov.ua/laws/show/771-2012-%D0%BF#Text/(Дата перегляду20червня 2023).
5. Self-driving car (autonomous car or driverless car) / [електронний ресурс] – режим доступу: / https://www.techtarget.com/searchenterpriseai/definition/driverless-car/(Дата перегляду 20 червня 2023).
6. What is an Autonomous Car? / [електронний ресурс] – режим доступу:/ https://www.synopsys.com/automotive/what-is-autonomous-car.html#:~:text=Ultrasonic%20sensors%20in%20the%20wheels,acceleration%2C%20braking%2C%20and%20steering//(Дата перегляду 20 червня 2023).
7. How do self-driving cars work? / [електронний ресурс] – режим доступу: / https://www.bankrate.com/insurance/car/how-do-self-driving-cars-work//(Дата перегляду 20 червня 2023).
8. Artificial intelligence and machine learning for unmanned vehicles - April 26, 2021/ [електронний ресурс] – режим доступу: / https://www.militaryaerospace.com/unmanned/article/14202040/artificial-intelligence-and-machine-learning-for-unmanned-vehicles (Дата перегляду 20 червня 2023).
9. SAE J3016 2018, Sistemy avtomatizirovannogo upravleniya dvizheniem ATS. Klassifikaciya, terminy i opredeleniya (Taxonomy and Definitions for Terms Related to OnRoad Motor Vehicle Automated Driving Systems), SAE, 2018, 35 p.
10. 7 Types of Vehicle Connectivity/ [електронний ресурс] – режим доступу: https://blog.rgbsi.com/7-types-of-vehicle-connectivity/(Дата перегляду 20 червня 2023).
11. Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles J3016_201806 / [електронний ресурс] – режим доступу: / https://www.sae.org/standards/content/j3016_201806/(Дата перегляду 20 червня 2023).
12. The Drive for Vehicle-To-Everything Connectivity/ [електронний ресурс] — режим доступу: /https://www.electronicdesign.com/markets/automotive/article/21215345/mouser-the-drive-for-vehicletoeverything-connectivity/(Дата перегляду 20 червня 2023).
13. VEHICLE-TO-GRID (V2G) IS A TECHNOLOGY THAT HAS THE POWER TO TRANSFORM THE ENERGY SYSTEM. / [електронний ресурс] – режим доступу: https://www.virta.global/vehicle-to-grid-v2g/(Дата перегляду 20 червня 2023).
14. Small-form-factor embedded computing offers new SWaP-based distributed design paradigm/ [електронний ресурс] – режим доступу: https://www.militaryaerospace.com/computers/article/16714704/smallformfactor-embedded-computing-offers-new-swapbased-distributed-design-paradigm (Дата перегляду 20 червня 2023).