Public transportation (PT) often fails to provide door-to-door service. Passengers often have to walk a distance to reach their destination after getting off the public transportation station. Therefore, the walking accessibility of the station area directly affects the attractiveness of the PT. For walking, accurate calculation or prediction of accessibility should consider not only the objective distance, but also the environment and psychological perception factors of pedestrians. This paper aims to map the pedestrian perceived cost to the transportation environment to evaluate the walking accessibility of the public transportation station area accurately. From the perspective of psychological perception of walking environment, four key impedance factors are selected and a pedestrian perceived impedance model is established. Then an evaluation model of station area accessibility is set employing POIs (Point of Interests) based on the accumulative opportunity method. Finally, the case is given to show the application of the model. The results show that the number of crosswalks with signal lights, mixed use of sidewalk and non-motorized lane, the obstacle quantity and the vehicle entrance quantity on sidewalks can increase perceived impedance significantly. For example, pedestrians are willing to spend 4.21 extra minutes to adopt routes with one fewer obstacle per 100 meters. Within 10 minutes of walking time, walking perception has a greater impact on station area accessibility. The perceived walking time thresholds for evaluating bus and rail transit station area accessibility are recommended to be 15 minutes and 20 minutes, respectively. The evaluation results can provide a reliable basis for improving the walking network around public transportation station.


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    Titel :

    Evaluation of public transportation station area accessibility based on walking perception


    Beteiligte:
    Linbo Li (Autor:in) / Tianshuang Gao (Autor:in) / Yanli Wang (Autor:in) / Yuning Jin (Autor:in)


    Erscheinungsdatum :

    2023




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt