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    Modeling Mode Choice Behaviors for Public Transport Commuters in Beijing

    Source: Journal of Urban Planning and Development:;2018:;Volume ( 144 ):;issue: 003
    Author:
    Weng Jiancheng;Tu Qiang;Yuan Rongliang;Lin Pengfei;Chen Zhihong
    DOI: 10.1061/(ASCE)UP.1943-5444.0000459
    Publisher: American Society of Civil Engineers
    Abstract: Based on an analysis of the factors that influence the mode choice behaviors of commuters who use public transport (subways and buses), this study developed a questionnaire using a combination of revealed preference (RP) and stated preference (SP) techniques; both online and paper surveys were conducted to gather commuters’ travel choices between subways and buses. A binary logit (BL) specification was proposed to examine public transport commuters’ travel choices. The regression coefficients were estimated using maximum likelihood estimation. Finally, based on the data obtained from Beijing public transport smart cards, a support vector machine (SVM) classification model was established to identify commuters’ mode choices, and the accuracy was found to be as high as 94.24%. The estimated mode choice model was employed to predict the market shares of both subways and buses after a new fare scheme was implemented. The results showed that the model had high prediction accuracy: the average absolute error for predicting the market share of buses was 5.93%.
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      Modeling Mode Choice Behaviors for Public Transport Commuters in Beijing

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4249429
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    contributor authorWeng Jiancheng;Tu Qiang;Yuan Rongliang;Lin Pengfei;Chen Zhihong
    date accessioned2019-02-26T07:47:37Z
    date available2019-02-26T07:47:37Z
    date issued2018
    identifier other%28ASCE%29UP.1943-5444.0000459.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4249429
    description abstractBased on an analysis of the factors that influence the mode choice behaviors of commuters who use public transport (subways and buses), this study developed a questionnaire using a combination of revealed preference (RP) and stated preference (SP) techniques; both online and paper surveys were conducted to gather commuters’ travel choices between subways and buses. A binary logit (BL) specification was proposed to examine public transport commuters’ travel choices. The regression coefficients were estimated using maximum likelihood estimation. Finally, based on the data obtained from Beijing public transport smart cards, a support vector machine (SVM) classification model was established to identify commuters’ mode choices, and the accuracy was found to be as high as 94.24%. The estimated mode choice model was employed to predict the market shares of both subways and buses after a new fare scheme was implemented. The results showed that the model had high prediction accuracy: the average absolute error for predicting the market share of buses was 5.93%.
    publisherAmerican Society of Civil Engineers
    titleModeling Mode Choice Behaviors for Public Transport Commuters in Beijing
    typeJournal Paper
    journal volume144
    journal issue3
    journal titleJournal of Urban Planning and Development
    identifier doi10.1061/(ASCE)UP.1943-5444.0000459
    page5018013
    treeJournal of Urban Planning and Development:;2018:;Volume ( 144 ):;issue: 003
    contenttypeFulltext
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