Extreme weather conditions, strong gusts, and torrential rainfall threaten the safety of the general public and restrict people’s travel options. Most of the transportation modes are suspended because of safety reasons. Taxis are one of the only few available non-private transport modes to provide services to those who have urgent and unavoidable travel needs. This study uses global positioning system data collected from 460 Hong Kong urban taxis during nine ordinary and one tropical cyclone periods aiming to find out and explain the differences in relation to the percentage of taxis not in operation, the number of served passenger-trips, average time spent by vacant-taxi drivers finding a customer, and the percentage of taxi drivers in cross-district customer-search throughout the same 48 h duration. The findings show an inadequate level of taxi supply and a high passenger demand during the tropical-cyclone-affected period. Up to 80% of taxis were not in operation to serve the urgent and necessary trips. The average customer-search time for taxi drivers, which is anticipated inversely proportional to the demand for taxi rides, was very short (about 5 min). Policy measures are discussed and recommended to the government to improve the taxi services during extreme weather conditions.


    Zugriff

    Download

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Spatio-Temporal Influence of Extreme Weather on a Taxi Market


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Wong, R. C. P. (Autor:in) / Mak, P. L. (Autor:in) / Szeto, W. Y. (Autor:in) / Yang, W. H. (Autor:in)


    Erscheinungsdatum :

    03.03.2021




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Detecting Taxi Trajectory Anomaly Based on Spatio-Temporal Relations

    Qian, Shiyou / Cheng, Bin / Cao, Jian et al. | IEEE | 2022


    Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining

    Jindal, Ishan / Qin, Zhiwei / Chen, Xuewen et al. | ArXiv | 2018

    Freier Zugriff

    Mining urban taxi operation characteristics based on spatio-temporal trajectory data

    Kugan, Huang / Huan, Xiong / Chun, Bao et al. | SPIE | 2024


    Taxi scheduling visual analysis method and system based on multi-dimensional spatio-temporal data

    ZHANG HUIJIE / BAI JINGHAN / GONG WANFU et al. | Europäisches Patentamt | 2023

    Freier Zugriff