Probe vehicle trajectory data has the potential to transform the current practice of traffic signal optimization. Current scalable trajectory data is limited in both the penetration rate and the ping frequency, or the length of time between vehicle waypoints. This paper introduces a methodology to create binary vehicle trajectories which can be used in a neural network to predict when vehicles will arrive at a virtual detector. The methodology allows for vehicles with ping frequencies of up to 60 s to be utilized for the optimization of offsets at signalized intersections. A nine-signal corridor in west Michigan was used to test the proposed methodology. The neural network was compared to traditional linear interpolation strategies and found to improve the root mean squared error of the arrival times by up to 6.18 s. Using the virtual detector data stacked over time to optimize the offsets of the corridor resulted in 77% of the benefit of an offset optimization performed with continuously collected high resolution signal controller data. In the era of big data, this alternative approach can assist with the large-scale implementation of traffic signal performance measures for improved operations.


    Zugriff

    Download

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Replicating Advanced Detection using Low Ping Frequency Probe Vehicle Trajectory Data to Optimize Signal Progression


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:


    Erscheinungsdatum :

    06.06.2020




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Utilizing Low-Ping Frequency Vehicle Trajectory Data to Characterize Delay at Traffic Signals

    Waddell, Jonathan M. / Remias, Stephen M. / Kirsch, Jenna N. et al. | ASCE | 2020


    SYSTEM TO OPTIMIZE SCATS ADAPTIVE SIGNAL SYSTEM USING TRAJECTORY DATA

    ZHENG JIANFENG / LIU XIANGHONG / LI FULIANG | Europäisches Patentamt | 2020

    Freier Zugriff

    System to optimize SCATS adaptive signal system using trajectory data

    ZHENG JIANFENG / LIU XIANGHONG / LI FULIANG | Europäisches Patentamt | 2021

    Freier Zugriff

    SYSTEM TO OPTIMIZE SCATS ADAPTIVE SIGNAL SYSTEM USING TRAJECTORY DATA

    ZHENG JIANFENG / LIU XIANGHONG / LI FULIANG | Europäisches Patentamt | 2020

    Freier Zugriff

    System to optimize SCATS adaptive signal system using trajectory data

    ZHENG JIANFENG / LIU XIANGHONG / LI FULIANG | Europäisches Patentamt | 2020

    Freier Zugriff