Examining the Effects of the Built Environment on Travel Mode Choice across Different Age Groups in Seoul using a Random Forest Method

It is important to analyze factors that influence travel mode choice and to predict individual mode choice because this shapes people’s movement and determines their level of mobility. While there have been studies investigating how built-environment elements are associated with travel mode choice, most efforts have neglected evaluating the heterogeneity of effects that the built environment has on travel mode choice across different age groups. This study aims to examine the effects of the built environment in influencing travel mode choice across age groups in Seoul, South Korea, using a random forest approach. Our random forest model demonstrates what factors are important and how they are associated with the effects on travel mode choice. As a result, the built environment has a greater impact on the subway selection for older adults than other age groups and the random forest approach captures non-linear relationships between certain predictors and travel mode choices. Applying this approach to the travel mode choice analysis, we can examine the heterogeneous effects of the built environment on travel mode choice across different age groups.

• Record URL:
  https://doi.org/10.1177/03611981211000750
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/03611981
• Supplemental Notes:
  • The data that support the findings of this study were obtained from the 2016 Household Travel Survey at Korea Transport Database (http://www.ktdb.go.kr). As these data are available to anyone publicly via this portal, the data sharing is not applicable to this article as no new data were created or analyzed in this study. © National Academy of Sciences: Transportation Research Board 2021.
• Authors:
  • Kim, Kyusik
  • Kwon, Kyusang
  • Horner, Mark W
• Publication Date: 2021-8

Language

• English

Media Info

• Media Type: Digital/other
• Features: Appendices; Figures; Maps; References; Tables;
• Pagination: pp 670-683
• Serial:
  • Transportation Research Record: Journal of the Transportation Research Board
  • Volume: 2675
  • Issue Number: 8
  • Publisher: Sage Publications, Incorporated
  • ISSN: 0361-1981
  • EISSN: 2169-4052
  • Serial URL: http://journals.sagepub.com/home/trr

Subject/Index Terms

• TRT Terms: Age groups; Automobile ownership; Built environment; Machine learning; Mode choice; Predictive models; Public transit; Travel demand
• Geographic Terms: Seoul (Korea)
• Subject Areas: Highways; Passenger Transportation; Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01764326
• Record Type: Publication
• Report/Paper Numbers: TRBAM-21-00164
• Files: TRIS, TRB, ATRI
• Created Date: Feb 4 2021 11:00AM