To address the coordination issue of connected automated vehicles (CAVs) at urban scenarios, a game-theoretic decision-making framework is proposed that can advance social benefits, including the traffic system efficiency and safety, as well as the benefits of individual users. Under the proposed decision-making framework, in this work, a representative urban driving scenario, i.e. the unsignalized intersection, is investigated. Once the vehicle enters the focused zone, it will interact with other CAVs and make collaborative decisions. To evaluate the safety risk of surrounding vehicles and reduce the complexity of the decision-making algorithm, the driving risk assessment algorithm is designed with a Gaussian potential field approach. The decision-making cost function is constructed by considering the driving safety and passing efficiency of CAVs. Additionally, decision-making constraints are designed and include safety, comfort, efficiency, control and stability. Based on the cost function and constraints, the fuzzy coalitional game approach is applied to the decision-making issue of CAVs at unsignalized intersections. Two types of fuzzy coalitions are constructed that reflect both individual and social benefits. The benefit allocation in the two types of fuzzy coalitions is associated with the driving aggressiveness of CAVs. Finally, the effectiveness and feasibility of the proposed decision-making framework are verified with three test cases.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Decision Making for Connected Automated Vehicles at Urban Intersections Considering Social and Individual Benefits


    Contributors:
    Hang, Peng (author) / Huang, Chao (author) / Hu, Zhongxu (author) / Lv, Chen (author)

    Published in:

    Publication date :

    2022-11-01


    Size :

    3356805 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Platooning of Connected Automated Vehicles at Intersections

    Hsu, Tsung-Ming / Tian, Jheng-Hong | IEEE | 2023


    DECOUPLED COOPERATIVE TRAJECTORY OPTIMIZATION FOR CONNECTED HIGHLY AUTOMATED VEHICLES AT URBAN INTERSECTIONS

    Krajewski, R. / Themann, P. / Eckstein, L. | British Library Conference Proceedings | 2016


    Decision-making for automated vehicles at intersections adapting human-like behavior

    de Beaucorps, Pierre / Streubel, Thomas / Verroust-Blondet, Anne et al. | IEEE | 2017


    Decision-Making for Automated Vehicles at Intersections Adapting Human-Like Behavior

    de Beaucorps, Pierre / Streubel, Thomas / Verroust-Blondet, Anne et al. | British Library Conference Proceedings | 2017


    Optimisation-based coordination of connected, automated vehicles at intersections

    Hult, Robert / Zanon, Mario / Gros, Sébastien et al. | Taylor & Francis Verlag | 2020

    Free access