Millimeter-Wave radar has been widely applied in the field of autonomous driving due to an excellent performance under complex weather conditions. However, in practical roadside scenarios, the challenge of sparse point clouds leading to clustering difficulties and the issue of large vehicle point clouds dispersing, resulting in fragmentation, currently hampers the practical ap-plication of radar sensors. We propose an adaptive point cloud clustering algorithm based on DBSCAN. First, we propose an improved DBSCAN clustering algorithm based on distance and speed thresholds, which enhances the differentiation of point clouds between different vehicles, and an adaptive ellipse gate strategy to solve the large vehicle point clouds fragmentation problem. Then, a secondary clustering algorithm based on azimuth is exploited, effectively addressing the issues of large vehicle fragmentation and anomalous speed values. Practical roadside experimental results demonstrate that our proposed algorithm significantly outperforms traditional algorithms, showing considerable potential in practical applications.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Adaptive Point Cloud Clustering Algorithm for Practical Roadside MmWave Radar Systems


    Beteiligte:
    Zhang, Luyi (Autor:in) / Zhang, Jinhang (Autor:in) / Shi, Haixin (Autor:in) / Gao, Lu (Autor:in) / Hu, Xiaopeng (Autor:in) / Chen, Rui (Autor:in)


    Erscheinungsdatum :

    24.06.2024


    Format / Umfang :

    6350601 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    4D High-Resolution Imagery of Point Clouds for Automotive mmWave Radar

    Jiang, Mengjie / Xu, Gang / Pei, Hao et al. | IEEE | 2024


    Fast-Spherical-Projection-Based Point Cloud Clustering Algorithm

    Chen, Zhihui / Xu, Hao / Zhao, Junxuan et al. | Transportation Research Record | 2022


    A probability distribution-based point cloud clustering algorithm

    Yuan,X. / Zhao,C. / Zhang,H. et al. | Kraftfahrwesen | 2012


    A Novel Adaptive Calibration Method for Distributed Roadside Millimeter-Wave Radar Pairs

    Li, Chengmin / Wang, Junhua / Fu, Ting et al. | IEEE | 2024