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    Pedestrian Spatial Violation Analyses for Urban Roadways

    Source: Journal of Transportation Engineering, Part A: Systems:;2020:;Volume ( 146 ):;issue: 011
    Author:
    Ling Wang
    ,
    Hao Zhong
    ,
    Wangyue Huang
    ,
    Wanjing Ma
    DOI: 10.1061/JTEPBS.0000400
    Publisher: ASCE
    Abstract: This study presents an investigation regarding the critical contributing factors in pedestrian spatial violations based on field observation of 15,090 samples at 14 roadway segments in Shanghai, China. A violation prediction model was applied to predict the impacts of roadway geometry design and traffic on the number of violations, and a real-time pedestrian violation prediction model was used to predict whether a pedestrian would spatially violate. For the violation prediction model, a Bayesian Poisson-lognormal model was used, and for the real-time pedestrian violation prediction model, a Bayesian logistic regression model was adopted. Then, random forest was employed to rank the importance of factors that are significant in violation prediction. The results showed that the presence of median, land use type, and number of lanes are the most significant variables in spatial violation. The findings of this study can provide a basis for traffic practitioners, researchers, and authorities to analyze the reasons for pedestrians’ spatial violations and develop guidelines for crossings design.
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      Pedestrian Spatial Violation Analyses for Urban Roadways

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4268125
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    contributor authorLing Wang
    contributor authorHao Zhong
    contributor authorWangyue Huang
    contributor authorWanjing Ma
    date accessioned2022-01-30T21:23:46Z
    date available2022-01-30T21:23:46Z
    date issued11/1/2020 12:00:00 AM
    identifier otherJTEPBS.0000400.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4268125
    description abstractThis study presents an investigation regarding the critical contributing factors in pedestrian spatial violations based on field observation of 15,090 samples at 14 roadway segments in Shanghai, China. A violation prediction model was applied to predict the impacts of roadway geometry design and traffic on the number of violations, and a real-time pedestrian violation prediction model was used to predict whether a pedestrian would spatially violate. For the violation prediction model, a Bayesian Poisson-lognormal model was used, and for the real-time pedestrian violation prediction model, a Bayesian logistic regression model was adopted. Then, random forest was employed to rank the importance of factors that are significant in violation prediction. The results showed that the presence of median, land use type, and number of lanes are the most significant variables in spatial violation. The findings of this study can provide a basis for traffic practitioners, researchers, and authorities to analyze the reasons for pedestrians’ spatial violations and develop guidelines for crossings design.
    publisherASCE
    titlePedestrian Spatial Violation Analyses for Urban Roadways
    typeJournal Paper
    journal volume146
    journal issue11
    journal titleJournal of Transportation Engineering, Part A: Systems
    identifier doi10.1061/JTEPBS.0000400
    page6
    treeJournal of Transportation Engineering, Part A: Systems:;2020:;Volume ( 146 ):;issue: 011
    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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