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Estimating Travellers’ Trip Purposes using Public Transport Data and Land Use Information

Conference Paper


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Abstract


  • In public transport system, the equipped automated fare collection (AFC) system records travellers’

    spatial and temporal information and generates a mass of data daily with more than ever attraction of

    interest and attention from both academics and practitioners. Advances in data availability and data

    mining techniques provide great opportunity to investigate various researches in an efficient and

    effective manner. A comprehensive literature review on the application of public transport smart card

    data before 2011 can be referred to [1]. As some relevant studies in recent years, [2] proposed a data

    fusion method to infer passengers’ behavioral attributes of the trips based on the naive Bayes classifier

    model. The proposed method was applied to a single railway station in Osaka, with boarding/alighting

    information recorded by smart card and validation using trip survey data. [3] applied a unsupervised

    machine learning method, continuous hidden Markov model, to imputing the missing activities for

    each trip chain with integration of both clustering and transition models. [4] conducted a comparison

    on OD matrices between survey data and smart card data, and showed that both trip demands showed

    high correlation, which implied that the latter might provide a more efficient while less expensive way

    to construct the OD matrices.

    As is well known, traditional survey serves as the major method to gather useful trip

    information for a long time, but it often takes high expense of manpower, time and monetary

    resources. Moreover, the gap between real trips and survey results can never be ignored. This study

    aims to investigate various travel purposes of the public transit passengers and develop a data analysis

    framework to estimate the trip purposes, which can be considered as an alternative or a

    complementarity to the traditional survey method.

Publication Date


  • 2019

Citation


  • Du, B. (2019). Estimating Travellers’ Trip Purposes using Public Transport Data and Land Use Information. Tenth Triennial Symposium on Transportation Analysis (TRISTAN X) (pp. 1-4).

Ro Full-text Url


  • https://ro.uow.edu.au/cgi/viewcontent.cgi?article=1320&context=smartpapers

Ro Metadata Url


  • http://ro.uow.edu.au/smartpapers/293

Start Page


  • 1

End Page


  • 4

Abstract


  • In public transport system, the equipped automated fare collection (AFC) system records travellers’

    spatial and temporal information and generates a mass of data daily with more than ever attraction of

    interest and attention from both academics and practitioners. Advances in data availability and data

    mining techniques provide great opportunity to investigate various researches in an efficient and

    effective manner. A comprehensive literature review on the application of public transport smart card

    data before 2011 can be referred to [1]. As some relevant studies in recent years, [2] proposed a data

    fusion method to infer passengers’ behavioral attributes of the trips based on the naive Bayes classifier

    model. The proposed method was applied to a single railway station in Osaka, with boarding/alighting

    information recorded by smart card and validation using trip survey data. [3] applied a unsupervised

    machine learning method, continuous hidden Markov model, to imputing the missing activities for

    each trip chain with integration of both clustering and transition models. [4] conducted a comparison

    on OD matrices between survey data and smart card data, and showed that both trip demands showed

    high correlation, which implied that the latter might provide a more efficient while less expensive way

    to construct the OD matrices.

    As is well known, traditional survey serves as the major method to gather useful trip

    information for a long time, but it often takes high expense of manpower, time and monetary

    resources. Moreover, the gap between real trips and survey results can never be ignored. This study

    aims to investigate various travel purposes of the public transit passengers and develop a data analysis

    framework to estimate the trip purposes, which can be considered as an alternative or a

    complementarity to the traditional survey method.

Publication Date


  • 2019

Citation


  • Du, B. (2019). Estimating Travellers’ Trip Purposes using Public Transport Data and Land Use Information. Tenth Triennial Symposium on Transportation Analysis (TRISTAN X) (pp. 1-4).

Ro Full-text Url


  • https://ro.uow.edu.au/cgi/viewcontent.cgi?article=1320&context=smartpapers

Ro Metadata Url


  • http://ro.uow.edu.au/smartpapers/293

Start Page


  • 1

End Page


  • 4