Vehicle trajectories clustering plays an increasingly essential role in understanding urban traffic patterns. In order to improve the clustering effect, we propose a novel clustering method integrated with multidimensional trajectory information based on ST-OPTICS clustering algorithm. This density-based algorithm utilizes spatial, temporal, road segment and direction angle information to form clusters of varying density based on spatial and temporal closeness. Furthermore, we utilize DTW to build a similarity model to measure the similarity between vehicle trajectories. Then we conduct experiments on a large-scale vehicle trajectory dataset consisting of 2172 trajectories collected from the GPS traces nearby Beijing Olympic Parks. Compared with four general clustering frameworks: DBSCAN, ST-DBSCAN, OPTICS and ST-OPTICS, we demonstrate that our method performs better than other clustering methods by evaluated on two internal cluster validity measures. Finally, we explore route choosing strategy according to the travel time of different trajectories and discover some abnormal trajectories.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Spatial-Temporal Trajectory Clustering and Anomaly Analysis Based on Improved OPTICS Method


    Beteiligte:
    Zhang, Ke (Autor:in) / Li, Huiping (Autor:in) / Shan, Yu (Autor:in) / Li, Meng (Autor:in)

    Kongress:

    21st COTA International Conference of Transportation Professionals ; 2021 ; Xi’an, China


    Erschienen in:

    CICTP 2021 ; 189-198


    Erscheinungsdatum :

    2021-12-14




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Similarity based vehicle trajectory clustering and anomaly detection

    Zhouyu Fu, / Weiming Hu, / Tieniu Tan, | IEEE | 2005


    Similarity Based Vehicle Trajectory Clustering and Anomaly Detection

    Fu, Z. / Hu, W. / Tan, T. | British Library Conference Proceedings | 2005


    Detecting Taxi Trajectory Anomaly Based on Spatio-Temporal Relations

    Qian, Shiyou / Cheng, Bin / Cao, Jian et al. | IEEE | 2022


    Trajectory anomaly detection system and online trajectory anomaly detection method

    LI WENBIN / YAO DI / BI JINGPING | Europäisches Patentamt | 2024

    Freier Zugriff

    Grid-Based Anomaly Detection of Freight Vehicle Trajectory considering Local Temporal Window

    Zixian Zhang / Geqi Qi / Avishai (Avi) Ceder et al. | DOAJ | 2021

    Freier Zugriff