 Assessing impacts of the built environment on mobility: A joint choice model of travel mode and durationYang Yang, Samitha Samaranayake and Timur Dogan Environment and Planning B, 2023, vol. 50, issue 9, 2359-2375 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. Keywords: urban mobility; planning; urban design; machine learning; travel behavior (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:50:y:2023:i:9:p:2359-2375 DOI: 10.1177/23998083231154263 Access Statistics for this article More articles in Environment and Planning B |
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