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Evolutionary dilemma game for conflict resolution at unsignalized traffic intersection

Author

Listed:
  • Saif Islam Bouderba

    (LAROSERI, Department of Computer Science, University of Chouaib Doukkali, Faculty of Science EL Jadida, Morocco)

  • Najem Moussa

    (LAROSERI, Department of Computer Science, University of Chouaib Doukkali, Faculty of Science EL Jadida, Morocco)

Abstract

A dilemma game is presented to study the crossing conflicts at unsignalized intersection. Each driver has two possible strategies: cooperation (driver who respects the right-hand priority rule) or defection (driver who crosses quickly or aggressively the intersection without any caution). A evolutionary dilemma game is played when two drivers (left and right drivers) attempt to cross simultaneously the intersection. In this game, the left driver has a trade-off between crossing the intersection safely and doing it quickly. In addition, each driver, within a distance DZ from the intersection, may be able to change his strategy, at time t+1, by imitating the driver in front of him and who got through the crossroad at time t. We study the outcomes of these behavior strategies and their impacts on the traffic capacity of the system. An analysis of these results shows that the strategies adopted by drivers at unsignalized intersection are intrinsically linked to the occurrence of collisions between left and right drivers and can have subconscious effects on their decisions making. The traffic flow capacity is computed using computer simulations for various values of the system parameters and we found that it is extremely dependent on the decisions of drivers crossing the intersection.

Suggested Citation

  • Saif Islam Bouderba & Najem Moussa, 2019. "Evolutionary dilemma game for conflict resolution at unsignalized traffic intersection," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 30(02n03), pages 1-16, February.
    • Handle: RePEc:wsi:ijmpcx:v:30:y:2019:i:02n03:n:s0129183119500189
    DOI: 10.1142/S0129183119500189
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    Cited by:

    1. Xu Chen & Xuan Di & Zechu Li, 2023. "Social Learning for Sequential Driving Dilemmas," Games, MDPI, vol. 14(3), pages 1-12, May.
    2. Rachid Marzoug & Noureddine Lakouari & José Roberto Pérez Cruz & Carlos Jesahel Vega Gómez, 2022. "Cellular Automata Model for Analysis and Optimization of Traffic Emission at Signalized Intersection," Sustainability, MDPI, vol. 14(21), pages 1-20, October.

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