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Modeling the Impact of Weather and Context Data on Transport Mode Choices: A Case Study of GPS Trajectories from Beijing

Author

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  • Timothy Otim

    (Institute of Communications and Navigation, German Aerospace Center, 82234 Oberpfaffenhofen, Germany
    These authors contributed equally to this work.)

  • Leandro Dörfer

    (Institute of Communications and Navigation, German Aerospace Center, 82234 Oberpfaffenhofen, Germany
    These authors contributed equally to this work.)

  • Dina Bousdar Ahmed

    (Institute of Communications and Navigation, German Aerospace Center, 82234 Oberpfaffenhofen, Germany
    These authors contributed equally to this work.)

  • Estefania Munoz Diaz

    (Institute of Communications and Navigation, German Aerospace Center, 82234 Oberpfaffenhofen, Germany
    These authors contributed equally to this work.)

Abstract

Over the years, researchers have been studying the effects of weather and context data on transport mode choices. Existing research studies are predominantly designed around travel surveys, but the accuracy of their findings relies on how travelers give accurate and honest answers. The proliferation of smartphones, however, now offers the possibility of utilizing GPS positioning data as an alternative information source, opening the potential to accurately model and better understand factors which influence transport mode choices, compared to travel surveys. The objective of this work is to develop a model to predict the transport mode choices based on GPS trajectories, weather and context data. We use 2671 GPS trajectories from the Geolife GPS trajectories dataset, weather data, such as temperature and air quality, and context data, such as rush hour, day/night time and onetime events, such as the Olympics. In the statistical analysis, we apply both descriptive and statistical models, such as the multinomial logit and probit models. We find that temperature has the most prominent effect among weather conditions. For instance, for temperatures greater than 25 °C, the walking share increases by 27%, and the bike share reduces by 21%, which is line with the results from several survey-based studies. In addition, the evidence of government policy on transport regulation is revealed when the air quality becomes hazardous, as people are encouraged to use environmentally friendly transport mode choices, such as the bike instead of the bus or car, which are known CO 2 emitters. Our conclusion is that GPS trajectories can be used as a means to model passenger behavior, e.g. the choice of transport mode, in a quantitative way, which will support transport mode operators and policy makers in their efforts to design and plan the transport mode infrastructure to best suit the passengers’ needs.

Suggested Citation

  • Timothy Otim & Leandro Dörfer & Dina Bousdar Ahmed & Estefania Munoz Diaz, 2022. "Modeling the Impact of Weather and Context Data on Transport Mode Choices: A Case Study of GPS Trajectories from Beijing," Sustainability, MDPI, vol. 14(10), pages 1-18, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6042-:d:816771
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    as
    1. Guzman, Luis A. & Oviedo, Daniel & Rivera, Carlos, 2017. "Assessing equity in transport accessibility to work and study: The Bogotá region," Journal of Transport Geography, Elsevier, vol. 58(C), pages 236-246.
    2. Böcker, Lars & Prillwitz, Jan & Dijst, Martin, 2013. "Climate change impacts on mode choices and travelled distances: a comparison of present with 2050 weather conditions for the Randstad Holland," Journal of Transport Geography, Elsevier, vol. 28(C), pages 176-185.
    3. Böcker, Lars & Dijst, Martin & Faber, Jan, 2016. "Weather, transport mode choices and emotional travel experiences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 360-373.
    4. Hainan Huang & Yi Lin & Jiancheng Weng & Jian Rong & Xiaoming Liu, 2018. "Identification of Inelastic Subway Trips Based on Weekly Station Sequence Data: An Example from the Beijing Subway," Sustainability, MDPI, vol. 10(12), pages 1-15, December.
    5. Susan Handy & Bert van Wee & Maarten Kroesen, 2014. "Promoting Cycling for Transport: Research Needs and Challenges," Transport Reviews, Taylor & Francis Journals, vol. 34(1), pages 4-24, January.
    6. Kaniz Fatima & Sara Moridpour & Tayebeh Saghapour, 2021. "Spatial and Temporal Distribution of Elderly Public Transport Mode Preference," Sustainability, MDPI, vol. 13(9), pages 1-15, April.
    7. Kyle Gebhart & Robert Noland, 2014. "The impact of weather conditions on bikeshare trips in Washington, DC," Transportation, Springer, vol. 41(6), pages 1205-1225, November.
    8. Singhal, Abhishek & Kamga, Camille & Yazici, Anil, 2014. "Impact of weather on urban transit ridership," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 379-391.
    9. Tom Thomas & Rinus Jaarsma & Bas Tutert, 2013. "Exploring temporal fluctuations of daily cycling demand on Dutch cycle paths: the influence of weather on cycling," Transportation, Springer, vol. 40(1), pages 1-22, January.
    10. Lars Böcker & Martin Dijst & Jan Prillwitz, 2013. "Impact of Everyday Weather on Individual Daily Travel Behaviours in Perspective: A Literature Review," Transport Reviews, Taylor & Francis Journals, vol. 33(1), pages 71-91, January.
    11. Arana, P. & Cabezudo, S. & Peñalba, M., 2014. "Influence of weather conditions on transit ridership: A statistical study using data from Smartcards," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 1-12.
    12. Şimşekoğlu, Özlem & Nordfjærn, Trond & Rundmo, Torbjørn, 2015. "The role of attitudes, transport priorities, and car use habit for travel mode use and intentions to use public transportation in an urban Norwegian public," Transport Policy, Elsevier, vol. 42(C), pages 113-120.
    13. Yang, Jun & Liu, Ying & Qin, Ping & Liu, Antung A., 2014. "A review of Beijing׳s vehicle registration lottery: Short-term effects on vehicle growth and fuel consumption," Energy Policy, Elsevier, vol. 75(C), pages 157-166.
    14. Ton, Danique & Duives, Dorine C. & Cats, Oded & Hoogendoorn-Lanser, Sascha & Hoogendoorn, Serge P., 2019. "Cycling or walking? Determinants of mode choice in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 123(C), pages 7-23.
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