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    A Multiclass Link Transmission Model for a Class-Varying Capacity and Congested Wave Speed

    Source: Journal of Transportation Engineering, Part A: Systems:;2023:;Volume ( 149 ):;issue: 010::page 04023096-1
    Author:
    Michael W. Levin
    ,
    Di Kang
    DOI: 10.1061/JTEPBS.TEENG-7940
    Publisher: ASCE
    Abstract: Varying implementations and availability of vehicle automation result in vehicles using significantly different driving behaviors. Adaptive cruise control implementations vary by manufacturer and also differ from human driving. Due to the prevalence of partial automation on new vehicles, researchers and practitioners interested in forecasting future traffic conditions are considering mixed or multiclass flow scenarios. Prior work on automated vehicles proposed a multiclass kinematic wave theory where the flow-density relationship changes in space and time in response to local variations in class proportions, They solved this theory using a Godunov approximation (cell transmission model). Capacity and congested wave speed are assumed to vary with respect to class proportions, and a triangular flow-density relationship is used. This problem is challenging because the flow-density relationship varies endogenously with the movement of vehicles, resulting in two unknowns that must be solved together: vehicle movements (cumulative counts) and boundaries defining changes in the flow-density relationship. This paper derives a multiclass link transmission model to solve the multiclass kinematic wave theory for any finite number of classes. In the process, we derive a multiclass Newell’s method to find exact solutions as a linear program. A simplified iterative algorithm is obtained to more quickly solve the multiclass link transmission model to be useful for large networks.
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      A Multiclass Link Transmission Model for a Class-Varying Capacity and Congested Wave Speed

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4293178
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    • Journal of Transportation Engineering, Part A: Systems

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    contributor authorMichael W. Levin
    contributor authorDi Kang
    date accessioned2023-11-27T22:58:00Z
    date available2023-11-27T22:58:00Z
    date issued7/18/2023 12:00:00 AM
    date issued2023-07-18
    identifier otherJTEPBS.TEENG-7940.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4293178
    description abstractVarying implementations and availability of vehicle automation result in vehicles using significantly different driving behaviors. Adaptive cruise control implementations vary by manufacturer and also differ from human driving. Due to the prevalence of partial automation on new vehicles, researchers and practitioners interested in forecasting future traffic conditions are considering mixed or multiclass flow scenarios. Prior work on automated vehicles proposed a multiclass kinematic wave theory where the flow-density relationship changes in space and time in response to local variations in class proportions, They solved this theory using a Godunov approximation (cell transmission model). Capacity and congested wave speed are assumed to vary with respect to class proportions, and a triangular flow-density relationship is used. This problem is challenging because the flow-density relationship varies endogenously with the movement of vehicles, resulting in two unknowns that must be solved together: vehicle movements (cumulative counts) and boundaries defining changes in the flow-density relationship. This paper derives a multiclass link transmission model to solve the multiclass kinematic wave theory for any finite number of classes. In the process, we derive a multiclass Newell’s method to find exact solutions as a linear program. A simplified iterative algorithm is obtained to more quickly solve the multiclass link transmission model to be useful for large networks.
    publisherASCE
    titleA Multiclass Link Transmission Model for a Class-Varying Capacity and Congested Wave Speed
    typeJournal Article
    journal volume149
    journal issue10
    journal titleJournal of Transportation Engineering, Part A: Systems
    identifier doi10.1061/JTEPBS.TEENG-7940
    journal fristpage04023096-1
    journal lastpage04023096-15
    page15
    treeJournal of Transportation Engineering, Part A: Systems:;2023:;Volume ( 149 ):;issue: 010
    contenttypeFulltext
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