Implementing a well-designed detour plan to minimize the impact of nonrecurrent congestion has long been adopted by responsible highway agencies, mainly on the basis of estimated incident duration or number of blocked lanes. Because an effective detour operation necessitates rigorous plans in advance and a vast amount of resources during implementation, a convincing justification for taking such actions becomes increasingly essential in practice, especially in view of diminishing resources for traffic management. This paper presents a multicriterion decision support system to assist traffic managers in effectively making such decisions in real-time operations by taking into account (a) associated costs and benefits from various perspectives, including the operational cost, and (b) the resultant benefits from reduced delay, fuel consumption, and emissions, as well as (c) the likelihood of incurring secondary incidents. The impact of potential driver compliance in response to the detour strategy and of the local traffic condition on the effectiveness of detour operations can be included in the decision process. The proposed system, with its embedded analytical hierarchy process structure and optimal corridor detour model, allows potential users to rank by priority all essential decision criteria (on the basis of either resource constraints or the demand of the general public) and to make the critical decision that can best manage any nonrecurrent congestion and maximize the total resultant socioeconomic benefits.


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    Title :

    Advanced Traffic Management System


    Subtitle :

    Integrated Multicriterion System for Assessing Detour Decisions during Nonrecurrent Freeway Congestion


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:
    Kim, Woon (author) / Liu, Yue (author) / Chang, Gang-Len (author)


    Publication date :

    2012-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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