Driving risk field modeling and the influencing factors analysis for intelligent connected vehicle

Haiqing Li; Sijun Li; Fuhao Xia; Jiufei Luo

doi:10.1117/12.2628008

14 March 2022 Driving risk field modeling and the influencing factors analysis for intelligent connected vehicle

Haiqing Li, Sijun Li, Fuhao Xia, Jiufei Luo

Proceedings Volume 12165, International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2021); 1216520 (2022) https://doi.org/10.1117/12.2628008
Event: 2021 International Conference on Intelligent Traffic Systems and Smart City, 2021, Zhengzhou, China

Abstract

Intelligent connected vehicle (ICV) is an important application area of artificial intelligence and has received more and more attention. In the current autonomous development of intelligent driving, it is a key and hot issue to improve the driving safety and autonomous decision-making ability of ICV under dynamic traffic flow. The existing driving safety theory mainly considers the vehicle's attributes, which cannot reflect the influence of traffic elements, and driver's behavior on driving safety. Based on the field theory, a driving risk field model considering traffic elements, vehicle state and driver behavior under dynamic traffic flow is established, and the influencing factors of each parameter in the driving risk field model are analyzed. The results of the study can provide an important theoretical basis for ICV autonomous driving decision-making.

Citation Download Citation

Haiqing Li, Sijun Li, Fuhao Xia, and Jiufei Luo "Driving risk field modeling and the influencing factors analysis for intelligent connected vehicle", Proc. SPIE 12165, International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2021), 1216520 (14 March 2022); https://doi.org/10.1117/12.2628008

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