As a significant part of intelligent traffic systems, the short-term traffic forecasting system undertakes the important task of providing basic data for traffic control and route guidance. In view of the real-time requirements and accuracy of short-term traffic forecasting systems, this study designs a data-driven, short-term traffic forecasting system based on a non-parametric regression model. First, this paper adopts distributed architecture, which assigns forecasting tasks of different roads to several host computers. Second, a short-term traffic forecasting algorithm based on non-parametric regression is improved in terms of feature of application, promoting search efficiency, and continuously self-adaptive. Finally, according to the characteristics of different databases, it optimizes storage structure, raises I/O efficiency, and improves the system performance. The experiment results show that this system has higher prediction speed and reliability and can handle the prediction tasks of large-scale transportation network systems. At the same time, this system can optimize and adjust itself in the process. It also has low dependence of initial setting and better adaptation.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Distributed Short-Term Traffic Forecasting System Based on Non-Parametric Regression Approach


    Contributors:
    Ling, Shuai (author) / Wu, Gang (author) / Ma, Shou-feng (author) / Jia, Ning (author)

    Conference:

    14th COTA International Conference of Transportation Professionals ; 2014 ; Changsha, China


    Published in:

    CICTP 2014 ; 233-246


    Publication date :

    2014-06-24




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





    The Combined Short-Term Forecasting Approach to Traffic Flow Based on Non-Parametric Regression

    Zhang, X.-l. / He, G.-g. / China Communications and Transportation Association; Transportation & Development Institute (American Society of Civil Engineers) | British Library Conference Proceedings | 2007


    Short-Term Traffic Flow Forecasting Based on the Improved Non-Parametric Regression

    Li, Ying-hong / Hao, Xiao-qing / Liu, Le-min | ASCE | 2013



    Use of Local Linear Regression Model for Short-Term Traffic Forecasting

    Sun, Hongyu / Liu, Henry X. / Xiao, Heng et al. | Transportation Research Record | 2003