Due to complex types of traffic participants and large randomness of traffic behaviors, intersection has become a typical scenario of urban traffic accident and a severe challenge for the application of autonomous driving urbanization. This paper extracts typical cross shaped intersection conflict scenarios through theoretical derivation in the first place. Next, to evaluate if single vehicle multi-sensor information fusion technology is reliable at intersections, a high mileage real road test is conducted. Then the potential risks of this scheme at intersection scene are analyzed. Finally, a technical concept of automatic driving perception combining V2I and multi sensor information fusion at intersections is proposed.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Research on Autonomous Driving Perception and Recognition Technology at Intersection


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Long, Shengzhao (editor) / Dhillon, Balbir S. (editor) / Ye, Long (editor) / Liu, Mingyang (author) / Guo, Kuiyuan (author) / Chen, Shuai (author) / Liu, Haoting (author) / Wang, Xu (author) / Zhou, Lusha (author)

    Conference:

    International Conference on Man-Machine-Environment System Engineering ; 2024 ; Beijing, China October 18, 2024 - October 20, 2024



    Publication date :

    2024-09-29


    Size :

    8 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





    3D LIDAR Point Cloud Based Intersection Recognition for Autonomous Driving

    Zhu, Q. / Chen, L. / Li, Q. et al. | British Library Conference Proceedings | 2012


    3D LIDAR point cloud based intersection recognition for autonomous driving

    Zhu, Quanwen / Chen, Long / Li, Qingquan et al. | IEEE | 2012


    Intersection detection and recognition for autonomous urban driving using a virtual cylindrical scanner

    Li, Qingquan / Chen, Long / Zhu, Quanwen et al. | Wiley | 2014

    Free access

    Intersection detection and recognition for autonomous urban driving using a virtual cylindrical scanner

    Li, Qingquan / Chen, Long / Zhu, Quanwen et al. | IET | 2014

    Free access