With the concept of cloud control system (CCS) for intelligent and connected vehicles proposed and developed, the vehicles and traffic safety and economy have a comprehensive improvement. However, the current research mostly stays in vehicle-to-vehicle or vehicle-to-infrastructure, which requires an on-board calculator with large computational and storage capacity, and the planning range is short. To solve these problems, a predictive adaptive cruise control (PACC) algorithm based on CCS is proposed. Hierarchical control architecture of PACC between vehicle and cloud is constructed, coordinating free cruising mode with car-following mode. For the free cruising mode, an ergodic optimization method placed in the cloud is designed. A multi-objective optimization algorithm based on model predictive control is designed for the car-following mode, which can plan the vehicle speed in advance. Finally, the simulation results show that the PACC algorithm can achieve 8.16% fuel saving with consuming less time for free cruising, and for car-following, it can achieve 3.23% fuel saving. More importantly, the results also show that the CCS has significant potential and feasibility for intelligent and connected vehicles application.


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    Titel :

    Predictive Adaptive Cruise Control for Heavy-duty Vehicle based on Cloud Control System


    Beteiligte:
    Li, Shuyan (Autor:in) / Li, Rui (Autor:in) / Gao, Bolin (Autor:in) / Wan, Keke (Autor:in) / Li, Keqiang (Autor:in) / Wang, Xuepeng (Autor:in) / Wang, Daniel (Autor:in) / Yang, Dongbo (Autor:in)


    Erscheinungsdatum :

    08.10.2022


    Format / Umfang :

    679388 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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