Based on the most widely used ALINEA (asservissement linéaire d’entrée autoroutière) algorithm in the ramp metering field, this paper optimizes the algorithm by using a wavelet neural network algorithm to predict traffic flow and consider the problem of inflow reduction in multi-lane traffic. For the multi-ramp cooperative control problem, the redundancy time is taken as the main index. The classifier’s design is based on pattern recognition theory. The important nodes are identified by K-means algorithm. The improved ALINEA algorithm is used to implement ramp control for important nodes. By controlling the key nodes of the expressway, the traffic efficiency of the expressway system is improved.


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    Title :

    Research on Dynamic Ramp Selection Control of Urban Expressway Based on Improved ALINEA Algorithm


    Contributors:
    Ci, Yusheng (author) / Sun, Yichen (author) / Wu, Lina (author) / Rong, Yu (author)

    Conference:

    19th COTA International Conference of Transportation Professionals ; 2019 ; Nanjing, China


    Published in:

    CICTP 2019 ; 2623-2635


    Publication date :

    2019-07-02




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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