Game-theoretic Collision Avoidance

Game-Theoretic Collision Avoidance is a collision avoidance control strategy that belongs to the class of game-theoretic decision-making frameworks, distinguished by its explicit modeling of multi-agent interactions as strategic games in which each agent’s maneuvering policy is optimized with respect to both safety constraints and the anticipated actions of others.

66

Publications

3.1K

Citations

165

Authors

77

Institutions

Publications per year

2017–2026

37

Authors

165

  1. MS
    Mac Schwager

    Stanford University, United States

    6 publications · 332 citations

    6

    h-index

  2. MS
    Mario Sassano

    University of Rome Tor Vergata, Italy

    4 publications · 327 citations

    4

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  3. MW
    Mingyu Wang

    Stanford University, United States

    4 publications · 282 citations

    4

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  4. TM
    Thulasi Mylvaganam

    Imperial College London, United Kingdom

    4 publications · 327 citations

    4

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  5. ZW
    Zijian Wang

    Stanford University, United States

    3 publications · 234 citations

    3

    h-index

1–5 of 165

Venues

  1. IEEE Transactions on Robotics

    3 publications · 200 citations

    3

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  2. Transportation Research Part B Methodological

    3 publications · 137 citations

    3

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  3. 2

    h-index

  4. 2

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  5. Ocean Engineering

    2 publications · 107 citations

    2

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1–5