Aiming at improving the efficiency and effectiveness of traffic information processing, the paper firstly studied how to mine the tremendous GPS historical traffic data to get a concise and typical data sample. Then, based on the principle of "Minimization of Coefficient of Variance" of selected typical samples, it is explored for the selection technique of "statistical cycle time" about traffic information processing. The approach has been applied successfully in the modeling parameter optimization of the project of "A Model Research of Traffic Congestion Based on GPS Real Time Data" and its implementation.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Optimization of Traffic Information Processing Based on Data Mining from GPS Historical Data


    Contributors:
    Liu, Nan (author) / Peng, Peng (author) / Shen, Zuzhi (author) / Han, Haihang (author) / Deng, Mingrong (author)

    Conference:

    Second International Conference on Transportation Engineering ; 2009 ; Southwest Jiaotong University, Chengdu, China



    Publication date :

    2009-07-29




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Optimization of Traffic Information Processing Based on Data Mining from GPS Historical Data

    Liu, N. / Peng, P. / Shen, Z. et al. | British Library Conference Proceedings | 2009


    Pattern mining from historical traffic big data

    Alam, Ishteaque / Ahmed, Mohammad Fuad / Alam, Mohaiminul et al. | IEEE | 2017


    Prioritized Traffic Information Delivery Based on Historical Data Analysis

    Jo, Hyunsung / Lee, Byungwoo / Na, Yong-chan et al. | IEEE | 2007


    A multimedia data mining framework: mining information from traffic video sequences

    Chen, Shu-Ching / Shyu, Mei-Ling / Zhang, Chengcui et al. | Tema Archive | 2002


    Short-time track prediction method based on air traffic management historical data mining

    SU ZHIGANG / HAO JINGTANG / WANG GUANGCHAO | European Patent Office | 2016

    Free access