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    Lane Selection Model Based on Phase-Field Coupling and Set Pair Logic

    Source: Journal of Transportation Engineering, Part A: Systems:;2022:;Volume ( 148 ):;issue: 011::page 04022097
    Author:
    Shijie Liu
    ,
    Xiaoyuan Wang
    ,
    Yaqi Liu
    ,
    Longfei Chen
    ,
    Hao Li
    ,
    Gang Wang
    ,
    Qingyin Li
    DOI: 10.1061/JTEPBS.0000756
    Publisher: ASCE
    Abstract: Intelligent and connected driving (ICD) is an effective method of the vehicle’s active safety and traffic efficiency. Lane-changing is the critical part of ICD behavior and the basic content of traffic flow theory. Lane selection is the most important during lane-changing, which has a critical influence on traffic safety and efficiency. Focusing on the development of ICD technology, a lane selection model based on phase-field coupling and set pair logic is proposed. In this model, the method of phased-field coupling is used to comprehensively analyze the full information of lanes with the interaction between cluster vehicles considering driving propensity. The certain and uncertain human-vehicle-environment information is fully explored using the method of set pair logic. In the lane selection model, the lane utility and utility gains of lane-changing are calculated to select the candidate target lane. And the overall satisfaction is analyzed to determine the target lane as the final strategy. The proposed lane selection model constructed in this research fully considers the development of ICD technology and adapts to the requirement of an Intelligent and Connected Vehicle. This research could provide a theoretical basis for vehicle autonomous behavior decision-making and ICD.
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      Lane Selection Model Based on Phase-Field Coupling and Set Pair Logic

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4289511
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    • Journal of Transportation Engineering, Part A: Systems

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    contributor authorShijie Liu
    contributor authorXiaoyuan Wang
    contributor authorYaqi Liu
    contributor authorLongfei Chen
    contributor authorHao Li
    contributor authorGang Wang
    contributor authorQingyin Li
    date accessioned2023-04-07T00:40:14Z
    date available2023-04-07T00:40:14Z
    date issued2022/11/01
    identifier otherJTEPBS.0000756.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4289511
    description abstractIntelligent and connected driving (ICD) is an effective method of the vehicle’s active safety and traffic efficiency. Lane-changing is the critical part of ICD behavior and the basic content of traffic flow theory. Lane selection is the most important during lane-changing, which has a critical influence on traffic safety and efficiency. Focusing on the development of ICD technology, a lane selection model based on phase-field coupling and set pair logic is proposed. In this model, the method of phased-field coupling is used to comprehensively analyze the full information of lanes with the interaction between cluster vehicles considering driving propensity. The certain and uncertain human-vehicle-environment information is fully explored using the method of set pair logic. In the lane selection model, the lane utility and utility gains of lane-changing are calculated to select the candidate target lane. And the overall satisfaction is analyzed to determine the target lane as the final strategy. The proposed lane selection model constructed in this research fully considers the development of ICD technology and adapts to the requirement of an Intelligent and Connected Vehicle. This research could provide a theoretical basis for vehicle autonomous behavior decision-making and ICD.
    publisherASCE
    titleLane Selection Model Based on Phase-Field Coupling and Set Pair Logic
    typeJournal Article
    journal volume148
    journal issue11
    journal titleJournal of Transportation Engineering, Part A: Systems
    identifier doi10.1061/JTEPBS.0000756
    journal fristpage04022097
    journal lastpage04022097_11
    page11
    treeJournal of Transportation Engineering, Part A: Systems:;2022:;Volume ( 148 ):;issue: 011
    contenttypeFulltext
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