Investigation of Following Vehicles’ Driving Patterns Using Spectral Analysis Techniques

Chandle Chae and Youngho Kim ()
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Chandle Chae: Division for Road Transport Policy, Korea Transport Institute, Sejong-si 30147, Republic of Korea
Youngho Kim: Department of Mobility Transformation Research, Korea Transport Institute, Sejong-si 30147, Republic of Korea

Sustainability, 2023, vol. 15, issue 13, 1-15

Abstract: Despite the potential benefits of autonomous vehicles (AVs) of reducing human driver errors and enhancing traffic safety, a comprehensive evaluation of recent AV collision data reveals a concerning trend of rear-end collisions caused by following vehicles. This study aimed to address this issue by developing a methodology that identifies the relationship between driving patterns and the risk of collision between leading and following vehicles using spectral analysis. Specifically, we propose a process for computing three indices: reaction time, stimulus compliance index, and collision-risk aversion index. These indices consistently produced reliable results under various traffic conditions. Our findings align with existing research on the driving patterns of following vehicles. Given the consistency and robustness of these indices, they can be effectively utilized in advanced driver assistance systems or incorporated into AVs to assess the likelihood of collision risk posed by following vehicles and develop safer driving strategies accordingly.

Keywords: sustainable traffic management; autonomous vehicle; driving behavior; car following; spectral analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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