An accurate and robust localization system is crucial for autonomous vehicles (AVs) to enable safe driving in urban scenes. While existing global navigation satellite system (GNSS)-based methods are effective at locating vehicles in open-sky regions, achieving high-accuracy positioning in urban canyons such as lower layers of multi-layer bridges, streets beside tall buildings, tunnels, etc., remains a challenge. In this paper, we investigate the potential of cellular-vehicle-to-everything (C-V2X) wireless communications in improving the localization performance of AVs under GNSS-denied environments. Specifically, we propose the first roadside unit (RSU)-based cooperative localization framework, namely CV2X-LOCA, that only uses C-V2X channel state information to achieve lane-level positioning accuracy. CV2X-LOCA consists of four key parts: data processing module, coarse positioning module, environment parameter correcting module, and vehicle trajectory filtering module. These modules jointly handle challenges present in dynamic C-V2X networks. Extensive simulation and field experiments show that CV2X-LOCA achieves state-of-the-art performance for vehicle localization even under noisy conditions with high-speed movement and sparse RSU coverage environments. While focusing on AV localization, CV2X-LOCA also can extend to other C-V2X-equipped road users. The study results also provide insights into future investment decisions for transportation agencies regarding deploying RSUs cost-effectively.


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    Title :

    Toward C-V2X Enabled Connected Transportation System: RSU-Based Cooperative Localization Framework for Autonomous Vehicles


    Contributors:
    Huang, Zilin (author) / Chen, Sikai (author) / Pian, Yuzhuang (author) / Sheng, Zihao (author) / Ahn, Soyoung (author) / Noyce, David A. (author)

    Published in:

    Publication date :

    2024-10-01


    Size :

    3773910 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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