In this paper, we focus on traffic flow analysis in a visualization way. Classical methods visualize the traffic states by mapping the road section speed values into different colors. These classical methods have two defects need to be improved. Firstly, the traffic states computation process does not concern the effects arisen by different road types and time periods. Secondly, as these classical methods take the road sections as research objects, it can not evaluate the traffic states of areas with larger space scale. Thus, traffic index is adopted to evaluate the traffic states, which is a comprehensive criterion that it can both consider the effects arisen by different road types and time periods. A new traffic states visualization method, traffic index cloud maps, is proposed to visualize the traffic states for large road network areas. Real applications in Shanghai indicate that our method can present the traffic states of road network areas accurately and intuitively. Also, it can analyze the macroscopic traffic flow effectively and flexibly.


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    Titel :

    Traffic Index Cloud Maps for Traffic Flow Analysis with Big Traffic Data


    Beteiligte:
    Xiao, Jianli (Autor:in) / Wang, Hongyu (Autor:in)


    Erscheinungsdatum :

    01.05.2020


    Format / Umfang :

    125735 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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