The smartphone has become nearly indispensable in people’s daily lives. Prevalent smartphone usage can be observed on various occasions, even during walking. However, pedestrians’ perception of their surroundings may decline because they are absorbed by using the smartphone. The behavior of pedestrians using smartphones while walking at transit stations can be viewed as disturbance to pedestrian flows, thereby reducing the efficiency of station operation or even creating safety problems. This study seeks to describe such behavioral features mathematically and provide relevant implications for transit station design. Based on the social force model, the parameters reflecting the effect of smartphone usage on the perceived driving and repulsive forces are added and calibrated. By extracting trajectory data from the videos filmed in the field, the genetic algorithm is employed for the calibration process to minimize the gaps between the actual and projected trajectories. Two sets of parameter settings, for pedestrians with and without using smartphones, are determined and further applied to microscopic pedestrian simulation for a transfer station of the metro system in Taipei, Taiwan. The results indicate that pedestrians using smartphones are more prone to being affected by other pedestrians, revealing that their velocities are relatively unstable, while they need longer relaxation time to attain their desired walking statuses. The simulation results also visualize the potential bottlenecks in the station, where smartphone users may become obstacles to other pedestrians and increase the congestion level, highlighting the importance of incorporating the behavior modeling of pedestrians using smartphones into transit station design.


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    Titel :

    Research on Features of Pedestrians Using Smartphones at Transit Stations Based on Social Force Model


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Shen, Chung-Wei (Autor:in) / Mao, Mei-Neng (Autor:in) / Hsu, Yu-Ting (Autor:in) / Miralinaghi, Mohammad (Autor:in)


    Erscheinungsdatum :

    08.08.2022




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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