With the increasing concerns about environmental effects and the sustainability of roadway capacity expansion, transportation agencies are seeking alternative solutions to mitigate congestion. Managed lanes (MLs) promote person throughput on freeways and manage congestion through improving efficiency. The ML concept therefore has been gaining popularity in past decades. However, the lack of guidance on evaluating the performance of the ML facility poses challenges for agencies wanting to design and implement the strategy effectively. Many MLs are designed to be left-lane concurrent; vehicles entering the freeway from general purpose (GP) lane on-ramps need to cross weave over multiple GP lanes to access the ML. These weaving vehicles will have a negative effect on the operating performance of the parallel GP lanes. This paper investigates this cross-weaving effect as a function of different roadway geometric configurations as well as traffic conditions. A microscopic simulation model was built and calibrated on the basis of video data collected along I-635 in Dallas, Texas. Multiple scenarios were tested to explore the effect of the following parameters: number of GP lanes, cross-weave demand, and cross-weaving length. A set of capacity adjustment factors was determined to account for this effect as a function of those parameters. Results showed that the capacity-reducing effect was higher with a reduction in cross-weaving length, an increase in the number of GP lanes, or a rise in cross-weave demand volumes. The results are important in evaluating the operational performance of freeway segments in the presence of concurrent GP lanes and MLs in a Highway Capacity Manual context.


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    Titel :

    Quantifying Cross-Weave Impact on Capacity Reduction for Freeway Facilities with Managed Lanes


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:


    Erscheinungsdatum :

    01.01.2012




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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