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

Author

Listed:
  • 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
    Civil and Environmental Engineering, University of Hawaii, Honolulu, HI 96822, USA)

  • 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)

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.

Suggested Citation

  • Tianpei Tang & Yuntao Guo & Guohui Zhang & Hua Wang & Quan Shi, 2020. "Understanding the Interaction between Cyclists’ Traffic Violations and Enforcement Strategies: An Evolutionary Game-Theoretic Analysis," IJERPH, MDPI, vol. 17(22), pages 1-29, November.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:22:p:8457-:d:445375
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    References listed on IDEAS

    as
    1. Daniel Friedman, 1998. "On economic applications of evolutionary game theory," Journal of Evolutionary Economics, Springer, vol. 8(1), pages 15-43.
    2. Mohammed Abdellaoui, 2002. "A Genuine Rank-Dependent Generalization of the Von Neumann-Morgenstern Expected Utility Theorem," Econometrica, Econometric Society, vol. 70(2), pages 717-736, March.
    3. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    4. Hirshleifer, Jack, 1977. "Economics from a Biological Viewpoint," Journal of Law and Economics, University of Chicago Press, vol. 20(1), pages 1-52, April.
    5. Cherry, Christopher & Cervero, Robert, 2007. "Use characteristics and mode choice behavior of electric bike users in China," Transport Policy, Elsevier, vol. 14(3), pages 247-257, May.
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Ji Ang & David Levinson, 2020. "A Review of Game Theory Models of Lane Changing," Working Papers 2022-01, University of Minnesota: Nexus Research Group.
    8. Jou, Rong-Chang & Chen, Ke-Hong, 2013. "An application of cumulative prospect theory to freeway drivers’ route choice behaviours," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 123-131.
    9. Wong, S.C. & Wong, C.W. & Sze, N.N., 2008. "Attitudes of public light bus drivers to penalties to combat red light violations in Hong Kong," Transport Policy, Elsevier, vol. 15(1), pages 43-54, January.
    Full references (including those not matched with items on IDEAS)

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