Freeway traffic state estimation based on macroscopic traffic flow model METANET and extended Kalman filtering used to be conducted with fixed sensing data only. Recently the work was extended to the mixed sensing case of fixed and mobile sensors, and evaluated using the NGSIM data, with some significant conclusions. However, the highway stretch covered by NGSIM is unfortunately very short, the corresponding data duration is quite limited, and the involved congestion is not strong. To further demonstrate the performance of the designed traffic state estimator and verify the conclusions obtained with NGSIM, the estimator is studied and evaluated in this paper in microscopic simulation based on AIMSUN for a long freeway stretch of on/off-ramps and heavy congestion.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Freeway Traffic State Estimation using Fixed and Mobile Sensing Data with Microscopic Simulation Evaluation


    Beteiligte:
    Ma, Qiwei (Autor:in) / Zhao, Mingming (Autor:in) / Wang, Yibing (Autor:in)


    Erscheinungsdatum :

    2022-10-08


    Format / Umfang :

    1399791 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Real-time Freeway Traffic State Estimation with Fixed and Mobile Sensing Data

    Zhao, Mingming / Yu, Xianghua / Hu, Yonghui et al. | IEEE | 2020



    New Behavioral Model for Microscopic Freeway Traffic-Flow Simulation

    Harding, Jochen | Transportation Research Record | 2008



    State Estimation in Freeway Traffic Systems

    Ferrara, Antonella / Sacone, Simona / Siri, Silvia | Springer Verlag | 2018