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Assessing impacts of the built environment on mobility: A joint choice model of travel mode and duration

Author

Listed:
  • Yang Yang
  • Samitha Samaranayake
  • Timur Dogan

Abstract

This paper introduces a joint choice model for travel mode and duration to quantify the mobility impacts of urban design changes on the built environment. The model is formulated as a Random Forest classifier that predicts the mode-duration probabilities of a given trip. A novel series of predictor features are proposed which measure the urban form, demographics, and service densities on different scales of the transportation network. Through a sensitivity analysis and a proof-of-concept case study, we find that a dense, mixed-use environment with good coverage of a multi-modal mobility network can significantly promote active transportation and public transit use. However, we also find that ultra-dense, centralized developments can lead to increased travel time and increased vehicle use in the urban periphery. Our modeling and analysis method provides a simplified and effective way to assess urban design and planning scenarios from different mobility perspectives and facilitates data-driven, mobility-aware urban design and planning that can help identify better solutions more quickly.

Suggested Citation

  • Yang Yang & Samitha Samaranayake & Timur Dogan, 2023. "Assessing impacts of the built environment on mobility: A joint choice model of travel mode and duration," Environment and Planning B, , vol. 50(9), pages 2359-2375, November.
    • Handle: RePEc:sae:envirb:v:50:y:2023:i:9:p:2359-2375
    DOI: 10.1177/23998083231154263
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    References listed on IDEAS

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    Cited by:

    1. Minan Yang & Liyun Wang & Xin Li & Yongsheng Qian, 2025. "Study on Travel Characteristics and Satisfaction in Low-Density Areas Based on MNL and SEM Models—A Case of Lanzhou," Sustainability, MDPI, vol. 17(19), pages 1-27, September.
    2. Kim, Jaehwan & Jang, Kitae & Shim, Jisup, 2024. "Factors influencing bus-to-subway transfer duration at subway stations: Evidence from large-scale smart card data in Seoul," Journal of Transport Geography, Elsevier, vol. 120(C).

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