Transportation systems serve as a crucial foundation for maintaining the normal operation of cities and satisfying the requirements of public life. With the development of next-generation information technologies, automated driving technologies have brought new opportunities to improve the performance of traffic systems and the intelligence level of cities. Currently, significant research efforts have been conducted to develop automated driving systems in three major industries, i.e., automobile, roadway, and telecommunication. However, the collaboration and integration of automated driving systems among automobile, roadway, and telecommunications are still lacking, especially for collaborative development of system architecture and objectives. To address the need, this study first proposes a system architecture of vehicle–road-cloud collaborative automated driving system (VRC-CADS). Three levels of collaborative development, i.e., collaborative sensing, collaborative decision-making, and collaborative control, are designed for the VRC-CADS. Based on that, the typical scenarios of automated driving for each level of the system are further defined and interpreted. Moreover, feasible and systematic suggestions for the collaborative development of the VRC-CADS are provided, considering the cross-cutting collaboration among government agencies, academia, and industry. The proposed system architecture of the VRC-CADS will facilitate the optimization of urban lifelines and the evolution of intelligent cities.


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    Title :

    Architecture design of a vehicle–road-cloud collaborative automated driving system


    Additional title:

    Urban Lifeline


    Contributors:
    Ran, Bin (author) / Zheng, Yuan (author) / Luo, Kaijie (author) / Ma, Haozhan (author) / Rui, Yikang (author) / Li, Linheng (author) / Li, Xiaolong (author) / Hu, Jinling (author) / Hu, Yanming (author)

    Published in:

    Publication date :

    2023-12-19




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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