Driver-Automated Vehicle Interaction in Mixed Traffic: Types of Interaction and Drivers’ Driving Styles

感觉 人为因素与人体工程学 毒物控制 驾驶模拟器 相互作用 应用心理学 工程类 运输工程 模拟 心理学 计算机科学 社会心理学 医学 机器学习 医疗急救
作者
Zheng Ma,Yiqi Zhang
出处
期刊:Human Factors [SAGE Publishing]
卷期号:66 (2): 544-561 被引量:20
标识
DOI:10.1177/00187208221088358
摘要

Objective This study investigated drivers’ subjective feelings and decision making in mixed traffic by quantifying driver’s driving style and type of interaction. Background Human-driven vehicles (HVs) will share the road with automated vehicles (AVs) in mixed traffic. Previous studies focused on simulating the impacts of AVs on traffic flow, investigating car-following situations, and using simulation analysis lacking experimental tests of human drivers. Method Thirty-six drivers were classified into three driver groups (aggressive, moderate, and defensive drivers) and experienced HV-AV interaction and HV-HV interaction in a supervised web-based experiment. Drivers’ subjective feelings and decision making were collected via questionnaires. Results Results revealed that aggressive and moderate drivers felt significantly more anxious, less comfortable, and were more likely to behave aggressively in HV-AV interaction than in HV-HV interaction. Aggressive drivers were also more likely to take advantage of AVs on the road. In contrast, no such differences were found for defensive drivers indicating they were not significantly influenced by the type of vehicles with which they were interacting. Conclusion Driving style and type of interaction significantly influenced drivers’ subjective feelings and decision making in mixed traffic. This study brought insights into how human drivers perceive and interact with AVs and HVs on the road and how human drivers take advantage of AVs. Application This study provided a foundation for developing guidelines for mixed transportation systems to improve driver safety and user experience.
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