With the improvement of rail transportation automation level, obstacle detection technology gradually becomes a key technology for trains to realize unmanned driving in a complex environment. Traditional obstacle detection efficiency is low and labor-intensive; existing in-vehicle sensor obstacle detection limited by the work characteristics of different sensors have low detection rates and false alarms in the detection process. In this paper, we propose a target grid-based method for radar to sense the environment in the track area. We fuse millimeter wave radar and LIDAR two-source data and combine them with target grid algorithms to achieve environment sensing and obstacle detection in rail transit track areas. The relevant experiments show that the target grid-based environment sensing method for radar track area proposed in this paper effectively removes the flash-out noise, improves the accuracy of the information obtained by millimeter wave radar, and has a false alarm rate of 0.3% and a target detection rate of more than 99.2%, in a multi-noise target scenario, providing a reference for researchers in related fields.


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    Title :

    Rail Track Area Environment Perception Based on Rader Target Gird


    Contributors:
    Lu, Wenxue (author) / Wang, Qi (author) / Ding, Junzhe (author) / Niu, Weilong (author) / Sheng, Jie (author)


    Publication date :

    2022-12-01


    Size :

    1146762 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Räder

    Owen, Wilfred ;Bowen, Ezra | SLUB | 1967


    Area speed flow relationships by micro simulation : gird networks

    May, Anthony D. ;Shepherd, Simon P. | SLUB | 1994


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