Urban road flooding is increasingly becoming an interesting topic, which results in traffic congestion and secondary incidents, severely affects people's daily travelling. The paper proposes a method to generate a traffic assignment scheme for urgent dispersion in order to minimize the impact of congested traffic induced by flooded roads. In the method, Shunt Paths Search and Adaptive Dynamic Assignment algorithms are developed to determine an urgent dispersion area and its traffic assignment to implement the traffic assignment scheme in the area. Shunt Paths Search algorithm follows the least nodes principle to find the feasible paths from the entrance to the exit of the incident area, and these shunt paths compose the dispersion area. Adaptive Dynamic Assignment algorithm attempts to transfer the overflow traffic to the feasible paths as much as possible so that both the incident area and the shunt paths keep unblocked. Once the dispersion area can't deal with the traffic congestion of the incident area, some of the traffic flow from the outside crossing will be redirected to make sure the incident area keeping from congestion. The proposed methodology is applied to Panyu District of Guangzhou, China, with traffic-volume data in 18 intersections collected by a traffic survey in morning and evening peak/non-peak periods. The traffic assignment schemes of urgent dispersion are generated according to different depth of water spots of two incident area, due to the reduction of road capacity caused by the water spots. In order to evaluate the feasibility of the schemes in the study area, they are implemented in VISSIM. As expected, the average delay has contributed to an almost 50% reduction in urgent dispersion area after using the traffic assignment schemes in case study. It proves that the method can be utilized to solve the problem of urban road flooding effectively.


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    Title :

    A traffic assignment method of urgent dispersion under road flooding


    Contributors:
    Hu, Jihua (author) / Liang, Jiaxian (author) / Li, Guoyuan (author) / Gao, Lixiao (author)


    Publication date :

    2015-06-01


    Size :

    833942 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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