Comprehensive Evaluation of Freeway Driving Risks Based on Fuzzy Logic

Lian Xie, Jiaxin Zhang and Rui Cheng ()
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Lian Xie: Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China
Jiaxin Zhang: Guangxi Key Laboratory of ITS, Guilin University of Electronic Technology, Guilin 541004, China
Rui Cheng: Guangxi Key Laboratory of ITS, Guilin University of Electronic Technology, Guilin 541004, China

Sustainability, 2023, vol. 15, issue 1, 1-20

Abstract: The quantitative evaluation of driving risk is a crucial prerequisite for intelligent vehicle accident warning, and it is necessary to predict it comprehensively and accurately. Therefore, a simulated driving experiment was conducted with 16 experimental scenarios designed through an orthogonal design, and 44 subjects were recruited to explore the driving risks in different situations. A two-layer fuzzy integrated evaluation model was constructed, which considered the workload as an important element for balancing driving risk and driving behavior. Workload and road environment indicators were taken as the underlying input variables. The results show that the comprehensive evaluation model is well-suited to identify the risks of each scenario. The effectiveness of the proposed method is further confirmed by comparing the results with those of the technique for order preference by similarity to an ideal solution (TOPSIS) model. The proposed method could be used for real-time vehicle safety warning and provide a reference for accident prevention.

Keywords: fuzzy logic; workload; driving risks; multilevel modeling; traffic safety (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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