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    Research on Parking-Space Occupancy Recognition Based on MobileNet and Intelligent Parking Guidance Strategy

    Source: Journal of Highway and Transportation Research and Development (English Edition):;2022:;Volume ( 016 ):;issue: 003::page 78-84
    Author:
    Si-si Gu
    ,
    Xiao-fei Sun
    ,
    Miao Wang
    ,
    Jia-qing Yu
    DOI: 10.1061/JHTRCQ.0000835
    Publisher: ASCE
    Abstract: In order to solve the problem that parking spaces are hard to find in expressway service areas and to provide accurate parking space information and effective parking guidance, a strategy of parking-space occupancy recognition based on MobileNet and intelligent parking guidance is proposed. Based on detailed analysis of parking status and existing problems in expressway service areas, this paper puts forward the classification strategy of intelligent parking guidance in service areas and builds the technical route of parking space recognition based on AI vision. First, taking high-grade video and low-grade video in the service area as the detection data sources, the lightweight MobileNet classification model is used to analyze the parking-space occupancy in real time, to provide accurate and reliable information of the spare and occupied parking spaces in the parking area. Second, through the three-grade guidance screen, the three-grade parking guidance consisting of main line preview guidance, entrance total capacity guidance, and parking space guidance by vehicle type is realized, so that travelers can have a comprehensive understanding of parking-space occupancy in the service area in advance. To verify the effectiveness of an intelligent parking guidance classification strategy, a highway service area in north China is selected for field verification. The results show that the recognition accuracy of parking-space occupancy recognition model based on MobileNet is 98.0% under sufficient illumination during the day and 90.0% at night. During peak holidays, the total travel time of vehicles due to congestion and waiting in service areas is reduced by about 7%, which can save 20%∼30% of the time for finding parking spaces compared with the time for finding parking spaces in traditional service areas. Therefore, the proposed parking-space occupancy recognition based on MobileNet and intelligent parking guidance strategy can significantly improve the practical problems in the service area, meet the parking demand of the public to the maximum extent, relieve the parking pressure during peak hours, and improve the traffic capacity of the service area.
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      Research on Parking-Space Occupancy Recognition Based on MobileNet and Intelligent Parking Guidance Strategy

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4289476
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    • Journal of Highway and Transportation Research and Development (English Edition)

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    contributor authorSi-si Gu
    contributor authorXiao-fei Sun
    contributor authorMiao Wang
    contributor authorJia-qing Yu
    date accessioned2023-04-07T00:39:13Z
    date available2023-04-07T00:39:13Z
    date issued2022/09/01
    identifier otherJHTRCQ.0000835.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4289476
    description abstractIn order to solve the problem that parking spaces are hard to find in expressway service areas and to provide accurate parking space information and effective parking guidance, a strategy of parking-space occupancy recognition based on MobileNet and intelligent parking guidance is proposed. Based on detailed analysis of parking status and existing problems in expressway service areas, this paper puts forward the classification strategy of intelligent parking guidance in service areas and builds the technical route of parking space recognition based on AI vision. First, taking high-grade video and low-grade video in the service area as the detection data sources, the lightweight MobileNet classification model is used to analyze the parking-space occupancy in real time, to provide accurate and reliable information of the spare and occupied parking spaces in the parking area. Second, through the three-grade guidance screen, the three-grade parking guidance consisting of main line preview guidance, entrance total capacity guidance, and parking space guidance by vehicle type is realized, so that travelers can have a comprehensive understanding of parking-space occupancy in the service area in advance. To verify the effectiveness of an intelligent parking guidance classification strategy, a highway service area in north China is selected for field verification. The results show that the recognition accuracy of parking-space occupancy recognition model based on MobileNet is 98.0% under sufficient illumination during the day and 90.0% at night. During peak holidays, the total travel time of vehicles due to congestion and waiting in service areas is reduced by about 7%, which can save 20%∼30% of the time for finding parking spaces compared with the time for finding parking spaces in traditional service areas. Therefore, the proposed parking-space occupancy recognition based on MobileNet and intelligent parking guidance strategy can significantly improve the practical problems in the service area, meet the parking demand of the public to the maximum extent, relieve the parking pressure during peak hours, and improve the traffic capacity of the service area.
    publisherASCE
    titleResearch on Parking-Space Occupancy Recognition Based on MobileNet and Intelligent Parking Guidance Strategy
    typeJournal Article
    journal volume16
    journal issue3
    journal titleJournal of Highway and Transportation Research and Development (English Edition)
    identifier doi10.1061/JHTRCQ.0000835
    journal fristpage78-84
    journal lastpage78_84_7
    page7
    treeJournal of Highway and Transportation Research and Development (English Edition):;2022:;Volume ( 016 ):;issue: 003
    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
    yabeshDSpacePersian