Large-scale road network traffic state analysis faces challenges like network complexity, road coupling, and state variability. Advanced algorithms such as deep learning and reinforcement learning have shown promise. However, relying solely on neural networks often lacks interpretability. Although many existing studies focus on the spatiotemporal correlation, the abnormal state fluctuations are hardly overcome. This paper presents a novel information aggregation method, considering both spatial and temporal dimensions, inspired by the reverse K-nearest neighbor algorithm. It adaptively determines spatial relationships and temporal correlations to enhance practical applications. Using California’s PeMS data, the proposed method’s effectiveness has been validated. It has been demonstrated that spatiotemporal information aggregation can play a pivotal role in traffic predicting performance with the transformer-based method. A comprehensive congestion analysis of the California highway network can obtain the spatiotemporal distribution of congestion, the frequency of congestion for roads, and the identification of congestion regions.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Road Network Traffic Analysis Utilizing Spatiotemporal Information Aggregation


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Jia, Limin (Herausgeber:in) / Wang, Yanhui (Herausgeber:in) / Easa, Said (Herausgeber:in) / Wang, Gang (Autor:in) / Cai, Pinlong (Autor:in) / Qu, Guixian (Autor:in) / Dai, Rongjian (Autor:in) / Zhang, Junjie (Autor:in) / Shi, Botian (Autor:in)

    Kongress:

    International Conference on SmartRail, Traffic and Transportation Engineering ; 2024 ; Chongqing, China October 25, 2024 - October 27, 2024



    Erscheinungsdatum :

    19.07.2025


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Spatiotemporal Analysis of Road Traffic Accidents in Tekirdag Province

    Emre ÖZŞAHİN / Onurcan YILMAZ | DOAJ | 2023

    Freier Zugriff

    Road and traffic information system utilizing XML technology

    Masaoka, H. / ITS Congress Association | British Library Conference Proceedings | 2000


    Analysis of Spatiotemporal Impact of Traffic Incidents on Road Networks

    Zhang, Hui / Zhang, Weibin / Li, Jun et al. | British Library Conference Proceedings | 2022


    Analysis of Spatiotemporal Impact of Traffic Incidents on Road Networks

    Zhang, Hui / Zhang, Weibin / Li, Jun et al. | Springer Verlag | 2022


    Analysis of Spatiotemporal Impact of Traffic Incidents on Road Networks

    Zhang, Hui / Zhang, Weibin / Li, Jun et al. | TIBKAT | 2022