Vehicle-Infrastructure Cooperative Autonomous Driving (CAD) is a new paradigm of autonomous driving, which relies on the cooperation between intelligent roads and autonomous vehicles. This paradigm has been shown to be safer and more efficient compared to the on-vehicle-only autonomous driving paradigm. Our real-world deployment data indicate that the effectiveness of Vehicle-Infrastructure CAD is constrained by the reliability and performance of commercial communication networks. This paper targets this exact problem and proposes Tentacles, a middleware to achieve high communication reliability between intelligent roads and autonomous vehicles, in the context of Vehicle-Infrastructure CAD. Specifically, Tentacles dynamically matches Vehicle-Infrastructure CAD applications and the underlying communication technologies based on varying communication performance and quality needs. Evaluation results confirm that Tentacles reduces deadline violations by more than 88%, significantly improving the reliability of Vehicle-Infrastructure CAD systems.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Tentacles: A Middleware with Multi-Network Communication Reliability for Vehicle-Infrastructure Cooperative Autonomous Driving


    Contributors:
    Wu, Tianze (author) / Wang, Sa (author) / Bao, Yungang (author) / Shi, Weisong (author)


    Publication date :

    2024-10-07


    Size :

    1020121 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Driving with tentacles: Integral structures for sensing and motion

    von Hundelshausen, F. / Himmelsbach, M. / Hecker, F. et al. | British Library Online Contents | 2008


    Enhancing Transportation Safety with Infrastructure Cooperative Autonomous Driving System

    Noh, Jinhong / Jo, Yongwoo / Kim, Jooyoung et al. | Springer Verlag | 2024


    Enhancing Transportation Safety with Infrastructure Cooperative Autonomous Driving System

    Noh, Jinhong / Jo, Yongwoo / Kim, Jooyoung et al. | Springer Verlag | 2024


    COOPERATIVE MULTI-VEHICLE BEHAVIOR COORDINATION FOR AUTONOMOUS DRIVING

    Kessler, Tobias / Knoll, Alois | British Library Conference Proceedings | 2019


    Evidential-Based Approach for Trajectory Planning With Tentacles, for Autonomous Vehicles

    Mouhagir, Hafida / Talj, Reine / Cherfaoui, Veronique et al. | IEEE | 2020