The collision prevention early warning technology is critical in vehicle safety field because early warning technology has a significant influence on the vehicle reliability. However, collision prevention early warning is a challenging problem due to different special scenes. For the scene of parking lot, this study proposes the early warning method based on vision. First, the working condition of the parking lot is introduced, mainly including the perceivable working condition and imperceivable working condition. Next, the improved YOLOv5 algorithm is used to detect vehicles in the perceivable working condition through binocular camera, while an imperceivable collision avoidance safety distance model is designed to avoid collision in advance in the imperceivable working condition. The results of the experiment and simulation have a satisfying performance.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Research on collision prevention early warning technology of parking lot vehicles


    Contributors:
    Zhu, Guanyu (author) / Zang, Liguo (author) / Wang, Zhi (author) / Lin, Fen (author)


    Publication date :

    2022-10-28


    Size :

    1569795 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Vehicle parking collision early warning method and device

    LIU YIN / TIAN XIAOKANG / REN FAN et al. | European Patent Office | 2023

    Free access

    Parking collision early warning device and using method thereof

    JIA XIAOPING / LIU JINFANG | European Patent Office | 2023

    Free access

    Automobile rear-end collision prevention early warning system

    YOU YUANJUN | European Patent Office | 2020

    Free access

    Collision early warning method and collision early warning device

    ZHANG SHICHEN / MA BING / WANG DENGJIANG et al. | European Patent Office | 2021

    Free access

    Automobile rear-end collision prevention early warning system

    WANG JIANHUI / WANG HAOYUAN / ZHANG LI et al. | European Patent Office | 2023

    Free access