Trajectory data provide a rich source of information on spatial and temporal speed fluctuations of individual vehicles. To assemble a complete picture of traffic operations, obtaining vehicle trajectories of the entire traffic flow is essential. The current techniques cannot fulfill this need sufficiently. To this end, we developed a hybrid approach for reconstructing vehicle trajectories at signalized intersections that accounts for queue dynamics. Specifically, an extended variational solution network was established and Kalman Filtering was applied to capture and reproduce the stochastic properties of queue boundary curves. The proposed method was demonstrated using both NGSIM data and simulation data. Results showed that the hybrid approach reproduces accurately the shockwave boundaries and trajectory reconstruction. By fusing different sources of traffic data, the proposed method does not rely on the common assumption of uniform arrival between adjacent probe vehicles, which is the main drive for estimation improvement.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Vehicle trajectory reconstruction for signalized intersections: A hybrid approach integrating Kalman Filtering and variational theory


    Contributors:
    Chen, Peng (author) / Wei, Lei (author) / Meng, Fangfang (author) / Zheng, Nan (author)

    Published in:

    Publication date :

    2021-01-01


    Size :

    20 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown






    Vehicle Trajectory Reconstruction for Signalized Intersections with Low-Frequency Floating Car Data

    Hua Wang / Changlong Gu / Washington Yotto Ochieng | DOAJ | 2019

    Free access

    SATURATION FLOW ESTIMATION FOR SIGNALIZED INTERSECTIONS USING VEHICLE TRAJECTORY DATA

    ZHENG JIANFENG / LIU XIANGHONG | European Patent Office | 2020

    Free access

    Signalized intersections

    Miller, A.J. | Engineering Index Backfile | 1968