This research develops 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 or a few departure times -- for the evaluation of transit systems. These accessibility calculations are accomplished using only publicly-available data sources. Multiple time thresholds for a cumulative opportunities measure of accessibility are evaluated for their usefulness in modeling transit mode share. A binomial logit 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 model achieves a pseudo-R-sqaure 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. It may be possible to apply these techniques to existing models of transit ridership and mode share to improve their performance and cost-effectiveness.
University of Minnesota M.S. thesis. September 2013. Major: Civil Engineering. Advisor: David M. David. 1 computer file (PDF). iv, 37 pages.
Modeling the commute mode share of transit using continuous accessibility to jobs.
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