Hazard perception in driving style based on virtual reality technology

Autor: Wu He, Xuan Wang, Cailian Xu, Zijing Zheng, Yan Mao
Rok vydání: 2022
Popis: The aim of this paper is to directly investigate the influence of driving style on hazards and to test the hazard perception of drivers with driving style variability in different scenarios. To achieve these goals, we use a VR system for simulation. In the experiment, we compare the hazard perception abilities of drivers with four driving styles (dangerous, angry, anxious, and cautious) in three different hazard conditions (lane change, pedestrian presence phenomenon, and U-turn). Participants ’ driving decisions and hazard perception behaviors were recorded simultaneously. The results show that (1) the VR technology provides a realistic representation of the hazard situation, and the participants were able to react more realistically. (2) Dangerous drivers had the weakest hazard perception, cautious drivers had the strongest hazard perception, and there was little difference in hazard perception of anxious and angry drivers. (3) Lane changing was the most hazard-prone scenario, and drivers ’ hazard perception was the weakest in this scenario, leading to an increased rate of traffic accidents. (4) Male drivers had stronger hazard perceptions than female drivers. The results of this study have important implications for road safety as targeted training can improve hazard perception based on driving style, and the study provides a new paradigm for detecting hazard perception ability.
Databáze: OpenAIRE