COVID-19, a respiratory virus violently spread worldwide, has deeply affected people’s daily life and travel behaviors. We adopted an autoregressive distributed lag model to analyze changes in travel patterns in Houston, Texas during COVID-19. The results indicated that visit patterns and changes in COVID-19 cases a week prior heavily influence the following week’s behaviors. Additionally, unemployment claims, median minimum dwell time, and workplace visit activity played a major role in predicting total foot traffic. Notably, transit systems have seen an overall decrease in usage but were not significant in estimating total foot traffic. This model showcased a unique method of quantifying and analyzing travel behaviors in Houston in response to COVID-19.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Measuring travel behavior in Houston, Texas with mobility data during the 2020 COVID-19 outbreak


    Beteiligte:
    Jiao, Junfeng (Autor:in) / Bhat, Mira (Autor:in) / Azimian, Amin (Autor:in)

    Erschienen in:

    Transportation Letters ; 13 , 5-6 ; 461-472


    Erscheinungsdatum :

    2021-05-28


    Format / Umfang :

    12 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Benefits of Real-Time Travel Information in Houston, Texas

    K. N. Balke / G. L. Ullman / W. R. McCasland et al. | NTIS | 1995


    Port of Houston, Texas

    Engineering Index Backfile | 1948


    Identifying Hospital Deserts in Texas Before and During the COVID-19 Outbreak

    Jiao, Junfeng / Degen, Nathaniel / Azimian, Amin | Transportation Research Record | 2022


    Port of Houston Texas

    Engineering Index Backfile | 1935