YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • ASCE
    • Journal of Transportation Engineering, Part A: Systems
    • View Item
    •   YE&T Library
    • ASCE
    • Journal of Transportation Engineering, Part A: Systems
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    Vehicle-Type Dependent Car-Following Model for Heterogeneous Traffic Conditions

    Source: Journal of Transportation Engineering, Part A: Systems:;2011:;Volume ( 137 ):;issue: 011
    Author:
    K. V. R. Ravishankar
    ,
    Tom V. Mathew
    DOI: 10.1061/(ASCE)TE.1943-5436.0000273
    Publisher: American Society of Civil Engineers
    Abstract: Car-following behavior forms the kernel of traffic microsimulation models and is extensively studied for similar vehicle types. However, in heterogeneous traffic having a diverse mix of vehicles, following behavior also depends on the type of both the leader and following vehicles. This paper is an attempt to modify the widely used Gipps’s car-following model to incorporate vehicle-type dependent parameters. Performance of the model is studied at microscopic and macroscopic levels using data collected from both homogeneous and heterogeneous traffic conditions. The results indicate that the proposed modifications enhance the prediction of follower behavior and suggest the need of incorporating vehicle-type combination specific parameters into traffic simulation models.
    • Download: (288.4Kb)
    • Show Full MetaData Hide Full MetaData
    • Get RIS
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      Vehicle-Type Dependent Car-Following Model for Heterogeneous Traffic Conditions

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/69277
    Collections
    • Journal of Transportation Engineering, Part A: Systems

    Show full item record

    contributor authorK. V. R. Ravishankar
    contributor authorTom V. Mathew
    date accessioned2017-05-08T22:01:56Z
    date available2017-05-08T22:01:56Z
    date copyrightNovember 2011
    date issued2011
    identifier other%28asce%29te%2E1943-5436%2E0000317.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/69277
    description abstractCar-following behavior forms the kernel of traffic microsimulation models and is extensively studied for similar vehicle types. However, in heterogeneous traffic having a diverse mix of vehicles, following behavior also depends on the type of both the leader and following vehicles. This paper is an attempt to modify the widely used Gipps’s car-following model to incorporate vehicle-type dependent parameters. Performance of the model is studied at microscopic and macroscopic levels using data collected from both homogeneous and heterogeneous traffic conditions. The results indicate that the proposed modifications enhance the prediction of follower behavior and suggest the need of incorporating vehicle-type combination specific parameters into traffic simulation models.
    publisherAmerican Society of Civil Engineers
    titleVehicle-Type Dependent Car-Following Model for Heterogeneous Traffic Conditions
    typeJournal Paper
    journal volume137
    journal issue11
    journal titleJournal of Transportation Engineering, Part A: Systems
    identifier doi10.1061/(ASCE)TE.1943-5436.0000273
    treeJournal of Transportation Engineering, Part A: Systems:;2011:;Volume ( 137 ):;issue: 011
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian