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    Development of a behaviorally induced system optimal travel demand management system

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    Name:
    Development_of_Behaviorally_In ...
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    1.010Mb
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    Description:
    Final Accepted Manuscript
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    Author
    Hu, Xianbiao
    Chiu, Yi-Chang
    Shelton, Jeff
    Affiliation
    Department of Civil Engineering and Engineering Mechanics, University of Arizona
    Issue Date
    2016-03-30
    Keywords
    active traffic and demand management (ATDM)
    behaviorally induced system optimal
    dynamic traffic assignment
    system optimal
    travel behaviour
    travel demand management (TDM)
    
    Metadata
    Show full item record
    Publisher
    TAYLOR & FRANCIS INC
    Citation
    Development of a behaviorally induced system optimal travel demand management system 2016, 21 (1):12 Journal of Intelligent Transportation Systems
    Journal
    Journal of Intelligent Transportation Systems
    Rights
    Copyright © 2017 Taylor & Francis.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    The basic design concept of most advanced traveler information systems (ATIS) is to present generic information to travelers, leaving travelers to react to the information in their own way. This passive way of managing traffic by providing generic traffic information makes it difficult to predict the outcome and may even incur an adverse effect, such as overreaction (also referred to as the herding effect). Active traffic and demand management (ATDM) is another approach that has received continual attention from both academic research and real-world practice, aiming to effectively influence people's travel demand, provide more travel options, coordinate between travelers, and reduce the need for travel. The research discussed in this article deals with how to provide users with a travel option that aims to minimize the marginal system impact that results from this routing. The goal of this research is to take better advantage of the available real-time traffic information provided by ATIS, to further improve the system level traffic condition from User Equilibrium (UE), or a real-world traffic system that is worse than UE, toward System Optimal (SO), and avoid passively managing traffic. A behaviorally induced, system optimal travel demand management model is presented to achieve this goal through incremental routing. Both analytical derivation and numerical analysis have been conducted on Tucson network in Arizona, as well as on the Capital Area Metropolitan Planning Organization (CAMPO) network in Austin, TX. The outcomes of both studies show that our proposed modeling framework is promising for improving network traffic conditions toward SO, and results in substantial economic savings.
    Note
    12 month embargo; Published online: 30 Mar 2016
    ISSN
    1547-2450
    1547-2442
    DOI
    10.1080/15472450.2016.1171151
    Version
    Final accepted manuscript
    Additional Links
    https://www.tandfonline.com/doi/full/10.1080/15472450.2016.1171151
    ae974a485f413a2113503eed53cd6c53
    10.1080/15472450.2016.1171151
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