Vehicle Group Intelligence (VGI) represents a significant research domain that contributes to the advancement of intelligent transportation systems. This study employs bibliometric approaches to uncover knowledge bases and prevailing research perspectives within the VGI field. We collected 2821 publications from the SCIE and SSCI databases for the literature survey. A visual analysis is conducted from five distinct perspectives to reveal the overall distribution of these publications. Two analytical techniques (document co-citation and keyword co-occurrence) are utilized to highlight highly co-cited publications and popular research topics. According to the analysis of the document co-citation, six representative knowledge bases are identified: string stability of vehicle platoons, wireless communication of vehicle platoons, cooperative driving in merging areas, the influence of Cooperative Adaptive Cruise Control (CACC) platoon on traffic flow, platoon management of heavy-duty vehicles, and cooperative control of multi-agent systems. These knowledge bases have provided significant contributions to the exploration and development of the VGI field. Based on the knowledge mapping related to the keyword co-occurrence, the core research trends include five categories: vehicle platooning in different traffic scenarios, cooperative merging of Connected and Automated Vehicles (CAVs), active safety control of vehicle groups, stability analysis of vehicle platoons, and wireless communication of cooperative driving. Furthermore, we illustrate potential research opportunities at four levels, including control architectures, issues in the application of vehicle platoons, cooperative strategies of vehicle groups, and communication protocols and security. The research findings provide valuable guidance for researchers by clarifying the direction of academic exploration in the VGI field.


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    Titel :

    A Review of Vehicle Group Intelligence in a Connected Environment


    Beteiligte:
    Wu, Chaozhong (Autor:in) / Cai, Zhenggan (Autor:in) / He, Yi (Autor:in) / Lu, Xiaoyun (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2024-01-01


    Format / Umfang :

    22308804 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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