The paper validates an improved adaptive Kalman filter model (AKFM) for short-term traffic flow prediction on intersections in Shanghai, China. In this field, much research has been conducted in developed countries. However, less work has been done in China, a typical developing country, particularly dealing with the realtime prediction method with mixed traffic flow characteristics. This paper studies the adaptive mechanism method of time-window and the state transition parameters for improved model in detail, and carries out the characteristic and predictability analysis of the traffic flow volume using the detector data of an intersection in Shanghai, China. In addition, this paper has implemented the improved adaptive model in C++ and simulation results show it is effective, stable and self-adaptive. The findings of this study provide some useful insights into the short-term traffic flow prediction in urban intersections or other similar intersections in China.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Examples of Validating an Adaptive Kalman Filter Model for Short-Term Traffic Flow Prediction


    Contributors:
    Zhang, Liyan (author) / Ma, Jian (author) / Sun, Jian (author)

    Conference:

    The Twelfth COTA International Conference of Transportation Professionals ; 2012 ; Beijing, China


    Published in:

    CICTP 2012 ; 912-922


    Publication date :

    2012-07-23




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





    Research of Short-Term Traffic Flow Forecast Method Based on the Kalman Filter

    Chen, Feng / Jia, Yuanhua / An, Wenjuan et al. | ASCE | 2011


    Hybrid dual Kalman filtering model for short-term traffic flow forecasting

    Zhou, Teng / Jiang, Dazhi / Lin, Zhizhe et al. | IET | 2019

    Free access

    Hybrid dual Kalman filtering model for short‐term traffic flow forecasting

    Zhou, Teng / Jiang, Dazhi / Lin, Zhizhe et al. | Wiley | 2019

    Free access

    A Short-Term Traffic Flow Combination Prediction Model with Adaptive Weights

    Sun, Chuanxia / Sun, Xiaoliang / Yin, Peixuan et al. | ASCE | 2020