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    Federal Highway Administration Vehicle Classification from Video Data and a Disaggregation Model

    Source: Journal of Transportation Engineering, Part A: Systems:;2005:;Volume ( 131 ):;issue: 009
    Author:
    Andrew J. Graettinger
    ,
    Ramgiridhar R. Kilim
    ,
    Meghavardhan R. Govindu
    ,
    Philip W. Johnson
    ,
    S. Rocky Durrans
    DOI: 10.1061/(ASCE)0733-947X(2005)131:9(689)
    Publisher: American Society of Civil Engineers
    Abstract: To assess highway system performance, states are required to submit compositional traffic count reports to the Federal Highway Administration (FHWA). A methodology was developed for obtaining compositional vehicle counts from low-cost portable video technology. Autoscope, an advanced video camera with machine vision processing, was used to capture, process, and store compositional counts based on vehicle length. A maximum of five length-based vehicle classes can be differentiated from video; therefore a methodology was developed that generates the FHWA 13-category vehicle classes. A disaggregation process, typically used in stochastic hydrology, is employed. Results from the disaggregation model are compared with actual FHWA classification data obtained from axle counters. It was observed that less than 1% of the vehicles were not included in the model output and 3.43% were misclassified. In addition, 95 and 99% confidence intervals calculated by the disaggregation model included 92.3 and 100% of the actual axle counter data.
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      Federal Highway Administration Vehicle Classification from Video Data and a Disaggregation Model

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/37795
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    • Journal of Transportation Engineering, Part A: Systems

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    contributor authorAndrew J. Graettinger
    contributor authorRamgiridhar R. Kilim
    contributor authorMeghavardhan R. Govindu
    contributor authorPhilip W. Johnson
    contributor authorS. Rocky Durrans
    date accessioned2017-05-08T21:04:41Z
    date available2017-05-08T21:04:41Z
    date copyrightSeptember 2005
    date issued2005
    identifier other%28asce%290733-947x%282005%29131%3A9%28689%29.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/37795
    description abstractTo assess highway system performance, states are required to submit compositional traffic count reports to the Federal Highway Administration (FHWA). A methodology was developed for obtaining compositional vehicle counts from low-cost portable video technology. Autoscope, an advanced video camera with machine vision processing, was used to capture, process, and store compositional counts based on vehicle length. A maximum of five length-based vehicle classes can be differentiated from video; therefore a methodology was developed that generates the FHWA 13-category vehicle classes. A disaggregation process, typically used in stochastic hydrology, is employed. Results from the disaggregation model are compared with actual FHWA classification data obtained from axle counters. It was observed that less than 1% of the vehicles were not included in the model output and 3.43% were misclassified. In addition, 95 and 99% confidence intervals calculated by the disaggregation model included 92.3 and 100% of the actual axle counter data.
    publisherAmerican Society of Civil Engineers
    titleFederal Highway Administration Vehicle Classification from Video Data and a Disaggregation Model
    typeJournal Paper
    journal volume131
    journal issue9
    journal titleJournal of Transportation Engineering, Part A: Systems
    identifier doi10.1061/(ASCE)0733-947X(2005)131:9(689)
    treeJournal of Transportation Engineering, Part A: Systems:;2005:;Volume ( 131 ):;issue: 009
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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