This study applies and updates a method which identifies and quantifies the extent of traffic congestion from recurring freeway bottlenecks. Additionally, the spatiotemporal stability of bottlenecks over an extended period was tested. Over time congestion at bottlenecks may increase, may decrease, or may migrate to other nearby locations. Analysis of stability is important since prioritizing and applying treatments at bottlenecks is a multiyear process. In addition, a robust method for selecting sensitivity based parameters to identify and quantify bottleneck effects is presented. Subsequently, a systematic framework is developed for tracking and archiving the spatiotemporal changes in the recurring bottlenecks. The proposed method is demonstrated on a case study on Interstate 40 in North Carolina using three years of probe data. A congestion speed ratio detection threshold of 0.7 and a probability of activation threshold of 33% for the study area were determined from a sensitivity test to ascertain their recurrence. The method identified 13 bottlenecks with their impacts ranging from 35 to 3,278 mi-hours of congestion per year. Eight bottlenecks either newly emerged or had their queues merged or shifted between successive years. Even spatially stable bottlenecks had significant variation in their activation frequency and queue length. Exploration of the changes in bottleneck severity and locations revealed the influence of a long-term work zone in the area and the effect of the rapid growth in traffic demand. Local agencies can use this method to shortlist recurring bottlenecks and track changes to plan mitigation strategies.


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    Titel :

    Characteristics and Temporal Stability of Recurring Bottlenecks


    Weitere Titelangaben:

    Transportation Research Record


    Beteiligte:
    Ahmed, Ishtiak (Autor:in) / Rouphail, Nagui M. (Autor:in) / Tanvir, Shams (Autor:in)


    Erscheinungsdatum :

    2018-10-10




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch