Modeling the commute mode share of transit using continuous accessibility to jobs |
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| Institution: | 1. School of Urban Planning, McGill University, Suite 400, 815 Sherbrooke St. W., Montréal, Québec H3A 2K6, Canada;2. Department of Geography, University of Toronto at Mississauga, 3359 Mississauga Road N., Mississauga, ON, L5L 1C6, Canada;1. Department of Industrial Engineering, Ghent University, Valentin Vaerwyckweg 1, 9000 Ghent, Belgium;2. Department of Geography, Ghent University, Krijgslaan 281 S8, 9000 Ghent, Belgium;3. Department of Human Geography, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON, Canada;1. Goergen Institute for Data Science, University of Rochester, Rochester, NY 14627, United States;2. Facebook, Inc., 1 Hacker Way, Menlo Park, CA 94025, United States;3. Department of Mathematics and Statistics, Williams College, Williamstown, MA 01267, United States;1. Department of Civil Engineering, McGill University, Room 492, 817 Sherbrooke St.W., Montreal, Quebec H3A 0C3, Canada;2. Département des génies civil, géologique et des mines, École Polytechnique de Montréal, C.P. 6079, succ. Centre-Ville, Montréal, Québec H3C 3A7, Canada;3. School of Urban Planning, McGill University, Suite 400, 815 Sherbrooke St. W., Montréal, Québec H3A 2K6, Canada;4. School of Civil Engineering, University of Sydney, Room 418, Building J05, 225 Shepherd St., Darlington, NSW 2006, Australia |
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| Abstract: | This paper presents the results of an accessibility-based model of aggregate commute mode share, focusing on the share of transit relative to auto. It demonstrates the use of continuous accessibility – calculated continuously in time, rather than at a single of a few departure times – for the evaluation of transit systems. These accessibility calculations are accomplished using only publicly-available data sources. A binomial logic model is estimated which predicts the likelihood that a commuter will choose transit rather than auto for a commute trip based on aggregate characteristics of the surrounding area. Variables in this model include demographic factors as well as detailed accessibility calculations for both transit and auto. The mode achieves a ρ2 value of 0.597, and analysis of the results suggests that continuous accessibility of transit systems may be a valuable tool for use in modeling and forecasting. |
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| Keywords: | Public transit Accessibility Modeling Mode share Mode choice |
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