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    Modeling the Capacity of Left-Turn and Through Movement Considering Left-Turn Blockage and Spillback at Signalized Intersection with Short Left-Turn Bay

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    Date
    2010-10-12
    Author
    Cho, Kyoung Min
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    Abstract
    This research presents more realistic models for left-turn and through volume capacity by taking into account the probabilistic nature of the left-turn bay blockages and spillbacks at a signalized intersection under the leading phasing scheme with a short left-turn bay. Generally, the left-turn bay spillback situation has been overlooked in the leading left-turn signal because much attention has been given to the more common problem of left-turn blockage under the leading left signal. The left-turn spillback situation, however, might happen because the ratio of left-turning vehicle tends to be relatively high in the traffic after the occurrence of left-turn bay blockage. That is, left-turn bay blockage, spillback situations, left-turn capacity, and through capacity are closely connected with one another. Hence, this research estimates more precisely the capacity for through and left-turn movement by considering the left-turn bay blockage and spillback situations associated with left-turn bay under leading left-turn signal operations. In order to find general agreement between the results from this proposed model and a real-world situation, the developed capacity model is validated with the results from CORSIM simulations of a real-world signalized intersection. The binomial distribution is applied as the arrival distribution for through movement considering the characteristics of expected arrivals under heavy flow conditions. Finally, since left-turn bay blockage and spillback situation seem to have adverse impacts on each other, this research investigates if there are any dependent relationships between left-turn bay blockage and spillback. Here, this study confirmed that close relationships between left-turn bay blockage and spillback situations obviously exists.
    URI
    http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-2944
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    • Texas A&M University at College Station

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