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Game Theory-Based Risk Assessment of the Use of Autonomous Cars in an Urbanized Area

Author

Listed:
  • Vasilena Adamova

    (Department of Power Electronics, Faculty of Electronic Engineering and Technologies, Technical University of Sofia, 1000 Sofia, Bulgaria)

  • Stoyan Popov

    (Department of Mathematical Modelling and Numerical Methods, Faculty of Applied Mathematics and Informatics, Technical University of Sofia, 1000 Sofia, Bulgaria)

  • Simona Todorova

    (Department of Informatics, Faculty of Applied Mathematics and Informatics, Technical University of Sofia, 1000 Sofia, Bulgaria)

  • Silvia Baeva

    (Department of Mathematical Modelling and Numerical Methods, Faculty of Applied Mathematics and Informatics, Technical University of Sofia, 1000 Sofia, Bulgaria)

  • Nikolay Hinov

    (Department of Power Electronics, Faculty of Electronic Engineering and Technologies, Technical University of Sofia, 1000 Sofia, Bulgaria)

Abstract

With the advancement of autonomous vehicles and their integration into urbanized areas, new challenges emerge related to safety and risk management. This paper presents an approach to assessing the risks of using autonomous cars in urban environments based on game theory. The analysis focuses on interactions between autonomous and traditional vehicles, as well as other road participants, such as pedestrians and cyclists. By employing game theory models, potential conflicts, risk scenarios, and their impact on traffic safety and efficiency are identified. The proposed methods provide a foundation for developing risk management strategies that contribute to the safe and sustainable integration of autonomous vehicles in urban areas.

Suggested Citation

  • Vasilena Adamova & Stoyan Popov & Simona Todorova & Silvia Baeva & Nikolay Hinov, 2025. "Game Theory-Based Risk Assessment of the Use of Autonomous Cars in an Urbanized Area," Mathematics, MDPI, vol. 13(4), pages 1-30, February.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:4:p:553-:d:1586059
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    References listed on IDEAS

    as
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