Effect of autonomous vehicles on car-following behavior of human drivers: Analysis based on structural equation models

Xia Li, Zhijian You, Xinwei Ma, Xiaomin Pang, Xuefeng Min and Hongjun Cui

Physica A: Statistical Mechanics and its Applications, 2024, vol. 633, issue C

Abstract: Road traffic will experience a transition towards a mixed traffic flow, consisting of both autonomous vehicles (AVs) and human-driving vehicles (HVs), scenarios where HV drivers follow AVs will inevitably arise. This necessitates a comprehensive and in-depth exploration of driver behavior in such contexts, particularly focusing on the changes in their following behavior. To investigate the factors that influence the following behavior of HV drivers when following AVs in a human-machine mixed driving environment. Specifically, this study examines the impact of four variables on following intentions and following distance: driver’s understanding of AV performance, safety trust, tolerance for slow driving, and the driver’s perception of traffic flow conditions. To this end, a model framework is constructed that captures the relationships among these factors. A total of 376 valid samples were obtained through a survey. After verifying the internal consistency and reliability of the data, a structural equation model was utilized to conduct path analysis and mediation effect analysis to examine the relationships among the influencing factors. The results indicate that safety trust has a significant positive impact on following intentions, while traffic environmental perception has a significant negative impact. Safety trust has a significant negative impact on following distance, while tolerance for slow driving has a significant positive impact. Environmental perception and understanding of vehicle performance only indirectly influence following distance through their effects on safety trust and tolerance for slow driving. Among all factors, safety trust has the greatest impact on both following intentions and following distance. The results of this study can serve as a foundation for analyzing vehicle interactive behavior in human-machine mixed driving environments and as a basis for parameter calibration of car-following models.

Keywords: Human-machine mixed traffic flows; Car-following behavior; Car-following intention; Structural equation model; Mediation effect (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:633:y:2024:i:c:s0378437123009159

DOI: 10.1016/j.physa.2023.129360

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