Cooperative perception that integrates sensing capabilities from both infrastructure and vehicle perception sensors can greatly benefit the transportation system with respect to safety and data acquisition. In this study, we conduct a preliminary evaluation of such a system by integrating a portable lidar-based infrastructure detection system (namely, Traffic Scanner [TScan]) with a Society of Automotive Engineers (SAE) Level 4 connected and automated vehicle (CAV). Vehicle-to-everything (V2X) communication devices are installed on both the TScan and the CAV to enable real-time message transmission of detection results in the form of SAE J2735 basic safety messages. We validate the concept using a case study, which aims at improving CAV situation awareness and protecting vulnerable road user (VRU) safety. Field testing results demonstrate the safety benefits of cooperative perception from infrastructure sensors in detecting occluded VRUs and helping CAVs to plan safer (i.e., higher post-encroachment time) and smoother (i.e., lower deceleration rates) trajectories.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Cooperative Perception System for Aiding Connected and Automated Vehicle Navigation and Improving Safety


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2024-06-06




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations

    Shan, Mao / Narula, Karan / Wong, Ricky et al. | ArXiv | 2020

    Free access

    Cooperative UAV-navigation-aiding based on UGV vision systems

    Seibold, J. / Frietsch, N. / Gut, J. et al. | Tema Archive | 2010


    Infrastructure sensor-based cooperative perception for early stage connected and automated vehicle deployment

    Chen, Chenxi / Tang, Qing / Hu, Xianbiao et al. | Taylor & Francis Verlag | 2024


    Redundancy Mitigation in Cooperative Perception for Connected and Automated Vehicles

    Thandavarayan, Gokulnath / Sepulcre, Miguel / Gozalvez, Javier | IEEE | 2020


    Consensus-Based Distributed Cooperative Perception for Connected and Automated Vehicles

    Cai, Kunyang / Qu, Ting / Gao, Bingzhao et al. | IEEE | 2023