In transportation networks, traffic sensors are used to monitor the operation of transportation systems. A multi-objective detector location optimization is proposed. Four components are included in the objective function:(1) to cover more origin-demand pairs; (2) to obtain the maximum traffic data; (3) to maximize the gain of travel time error, and (4) to maximize the gain of travel time predication. This problem is solved by applying a distance-based, multi-objective, evolution algorithm. Numerical experiments are conducted on a small simulated network and Sioux-Falls network, respectively. An analysis about the obtained Pareto frontier is done. The results demonstrate the feasibility and effectiveness of the approach.


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    Title :

    A Multi-Objective Detector Location Optimization Approach


    Contributors:
    Liu, Yang (author) / Zhu, Ning (author)

    Conference:

    14th COTA International Conference of Transportation Professionals ; 2014 ; Changsha, China


    Published in:

    CICTP 2014 ; 1788-1800


    Publication date :

    2014-06-24




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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