Understanding the Interaction between Cyclists’ Traffic Violations and Enforcement Strategies: An Evolutionary Game-Theoretic Analysis

Tianpei Tang, Yuntao Guo, Guohui Zhang, Hua Wang and Quan Shi
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Tianpei Tang: School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China
Yuntao Guo: Department of Traffic Engineering & Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai 201804, China
Guohui Zhang: Civil and Environmental Engineering, University of Hawaii, Honolulu, HI 96822, USA
Hua Wang: Department of Civil and Environmental Engineering, National University of Singapore, Kent Ridge 119077, Singapore
Quan Shi: School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China

IJERPH, 2020, vol. 17, issue 22, 1-29

Abstract: An evolutionary game-theoretic analysis method is developed in this study to understand the interactions between cyclists’ traffic violations and the enforcement strategies. The evolutionary equilibrium stabilities were analysed under a fixed (FPS) and a dynamic penalty strategy (DPS). The simulation-based numerical experiments show that: (i) the proposed method can be used to study the interactions between traffic violations and the enforcement strategies; (ii) FPS and DPS can reduce cyclists’ probability of committing traffic violations when the perceived traffic violations’ relative benefit is less than the traffic violation penalty and the enforcement cost is less than the enforcement benefit, and using DPS can yield a stable enforcement outcome for law enforcement compared to using FPS; and (iii) strategy-related (penalty amount, enforcement effectiveness, and enforcement cost) and attitudinal factors (perceived relative benefit, relative public image cost, and cyclists’ attitude towards risk) can affect the enforcement strategy’s impacts on reducing cyclists’ traffic violations.

Keywords: cyclists; traffic violations; enforcement strategy; evolutionary game theory; cumulative prospect theory (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
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