To determine the control strategy at intersections adjacent to the expressway on-ramp, a route identification method based on empirical mode decomposition (EMD) and dynamic time warping (DTW) is established. First, the de-noise function of EMD method is applied to eliminate disturbances and extract features and trends of traffic data. Then, DTW is used to measure the similarity of traffic volume time series between intersection approaches and expressway on-ramp. Next, a three-dimensional feature vector is built for every intersection approach traffic flow, including DTW distance, space distance between on-ramp and intersection approach, and intersection traffic volume. Fuzzy C-means clustering method is employed to cluster intersection approaches into classifications and identify critical routes carrying the most traffic to the on-ramp. The traffic data are collected by inductive loops at Xujiahui on-ramp of North and South Viaduct Expressway and surrounding intersections in Shanghai, China. The result shows that the proposed method can achieve route classification among intersections for different time periods in one day, and the clustering result is significantly influenced by three dimensions of traffic flow feature vector. As an illustrative example, micro-simulation models are built with different control strategies. The simulation shows that the coordinated control of critical routes identified by the proposed method has a better performance than coordinated control of arterial roads. Conclusions demonstrated that the proposed route identification method could provide a theoretical basis for the coordinated control of traffic signals among intersections and on-ramp.


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    Titel :

    Route Identification Method for On-Ramp Traffic at Adjacent Intersections of Expressway Entrance


    Beteiligte:
    Wenxuan Wang (Autor:in) / Xiaodong Zhu (Autor:in) / Yanli Wang (Autor:in) / Bing Wu (Autor:in)


    Erscheinungsdatum :

    2019




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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