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Statistical and activity-based modeling of university student travel behavior

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  • Xueming Chen

Abstract

This paper conducts a statistical analysis of student travel behavior at Virginia Commonwealth University (VCU). The data source is the ‘University NHTS’ project launched by the Virginia Department of Transportation (VDOT) in 2009. Through this empirical study, it has been found that university student travel behavior is different from that of the general population; urban universities have lower percentages of nonmotorized trips than college-town universities; undergraduate students are likely to make more daily trips than graduate students -- similarly, on-campus students make more frequent trips than off-campus students; the most frequent student activities are home and academic activities; and student group categories have virtually no impact on daily activity profiles, though activity types do have a dramatic impact on daily activity profiles. Based on these research findings, the paper makes a series of recommendations regarding trip generation, trip distribution, mode choice, and activity-based modeling.

Suggested Citation

  • Xueming Chen, 2012. "Statistical and activity-based modeling of university student travel behavior," Transportation Planning and Technology, Taylor & Francis Journals, vol. 35(5), pages 591-610, March.
    • Handle: RePEc:taf:transp:v:35:y:2012:i:5:p:591-610
    DOI: 10.1080/03081060.2012.701818
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    References listed on IDEAS

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    1. Staffan Algers & Jonas Eliasson & Lars-Göran Mattsson, 2001. "Activity-based model development to support transport planning in the Stockholm region," ERSA conference papers ersa01p19, European Regional Science Association.
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    Cited by:

    1. Hamad, Khaled & Obaid, Lubna, 2022. "Tour-based travel demand forecasting model for a university campus," Transport Policy, Elsevier, vol. 117(C), pages 118-137.
    2. Bai, Yihang & Cao, Mengqiu & Wang, Ruoyu & Liu, Yuqi & Wang, Seunghyeon, 2022. "How street greenery facilitates active travel for university students," LSE Research Online Documents on Economics 115239, London School of Economics and Political Science, LSE Library.
    3. Zhou, Jiangping, 2014. "From better understandings to proactive actions: Housing location and commuting mode choices among university students," Transport Policy, Elsevier, vol. 33(C), pages 166-175.
    4. Ji, Shujuan & Wang, Xin & Lyu, Tao & Liu, Xiaojie & Wang, Yuanqing & Heinen, Eva & Sun, Zhenwei, 2022. "Understanding cycling distance according to the prediction of the XGBoost and the interpretation of SHAP: A non-linear and interaction effect analysis," Journal of Transport Geography, Elsevier, vol. 103(C).
    5. Jiangping Zhou & Yin Wang & Jiangyue Wu, 2018. "Mode Choice of Commuter Students in a College Town: An Exploratory Study from the United States," Sustainability, MDPI, vol. 10(9), pages 1-18, September.
    6. Hossain, Sanjana & Loa, Patrick & Ong, Felita & Habib, Khandker Nurul, 2022. "The determinants of commute mode usage frequency of post-secondary students in the Greater Toronto and Hamilton Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 164-185.
    7. Sottile, Eleonora & Tuveri, Giovanni & Piras, Francesco & Meloni, Italo, 2022. "Modelling commuting tours versus non-commuting tours for university students. A panel data analysis from different contexts," Transport Policy, Elsevier, vol. 118(C), pages 56-67.
    8. Bindong Sun & Rui Guo & Chun Yin, 2023. "Inequity on suburban campuses: University students disadvantaged in self‐improvement travel," Growth and Change, Wiley Blackwell, vol. 54(2), pages 404-420, June.
    9. Whalen, Kate E. & Páez, Antonio & Carrasco, Juan A., 2013. "Mode choice of university students commuting to school and the role of active travel," Journal of Transport Geography, Elsevier, vol. 31(C), pages 132-142.
    10. Zhan, Guangjun & Yan, Xuedong & Zhu, Shanjiang & Wang, Yun, 2016. "Using hierarchical tree-based regression model to examine university student travel frequency and mode choice patterns in China," Transport Policy, Elsevier, vol. 45(C), pages 55-65.

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