The traffic detecting result is always short of accuracy by different kinds of individual sensors in urban China. To solve the issue, a new data fusion approach is raised. The algorithm combines fuzzy and rough set theory based on evidence theory. The method is improved to concise attribute rules and to measure fuzzy likelihood. Furthermore, a new combination rule is given to dissolve the confliction among the traffic evidence data collected by different individual sensors. Finally, the experiment to fuse the traffic data from an intersection in urban Hangzhou City showed that the proposed approach could obtain a high accuracy.


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    Titel :

    Traffic Data Fusion Method Based on Evidence Theory Combining with Fuzzy Rough Sets


    Beteiligte:
    Ning, Chen (Autor:in) / Yuan, Bin (Autor:in) / Wu, Jian (Autor:in)

    Kongress:

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



    Erscheinungsdatum :

    2009-07-29




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch