Planned special events attract thousands of attendees from nearby cities or suburbia by car and transit. In most cases, the majority of attendees use personal automobiles, and a high parking demand results in a short time, with a consequent parking shortage. Parking guidance information systems can solve the problem by displaying information on parking lot availability to dynamically divert vehicles. This study focused on optimizing dynamic parking guidance information for automobile drivers at special events. An original multimode traffic network was converted to a novel network by considering parking lots as dummy links; therefore the shortest path and traffic assignment could be implemented in this extended network. A bilevel programming model based on quasi-dynamic route choice and linear programming was proposed to optimize the dynamic parking guidance information. On the basis of travelers' reaction to the guidance, stochastic dynamic user optimal route choice was employed within the lower-level model. The upper-level model was a linear program aimed at minimizing network total travel time. The solutions of the bilevel programming model were based on discrete particle swarm optimization and the method of successive average algorithms. Results of a case study implemented with a hypothetical network indicated that the optimization model could reduce the system total travel time by 4%.


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    Title :

    Optimization of Dynamic Parking Guidance Information for Special Events


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:
    Lv, Nengchao (author) / Yan, Xinping (author) / Ran, Bin (author) / Wu, Chaozhong (author) / Zhong, Ming (author)


    Publication date :

    2012-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English