Transit route choice models play a crucial role in determining how passengers interact with the transportation system. The resulting route choice parameters are used to calibrate demand forecasting models to determine how system alterations and modifications affect transit ridership on a route-level basis. Despite the importance of route choice calibration, no known model is available that is more recent than 2004. In order to understand current passengers' interaction with the modern-day transit system, a new method for transit route choice estimation is proposed in which a forward label-setting schedule-based multi-criterion shortest path algorithm is combined with an iterative trip elimination methodology. This new methodology yields high quality transit path choice sets with detailed temporal information on all types of network links (in-vehicle, walking, and waiting). This increased specificity, in turn, heightens the validity and accuracy of the route choice model. Passenger information is sampled from a transit on-board survey containing origin-destination locations, demographic details, and trip-specific attributes. A multinomial logit model with stop-level path size correction term is estimated yielding a 67\% match rate between the path with the highest estimated likelihood and the surveyed (taken) transit path. Furthermore, a transfer penalty of 28.8 minutes was estimated and coefficients' marginal rates of substitution are in close alignment to similar values in the literature for both walking and waiting time. Express routes were found to have a statistically significant negative impact on path utility for the lowest income thresholds while transitways (light rail, bus rapid transit, or commuter rail) had a positive associated perception for the highest household income class. Thus, support is found for the claim that transitways can potentially attract higher-income ``choice'' riders to the transit network. The merits and potential future applications of the new route choice model are analyzed through a case study investigating the impact of the A Line arterial bus rapid transit route on surrounding system ridership. The results of this research can be used to improve ridership projections and highlight areas for policy improvements that could have the largest impact on retaining and attracting new passengers to the transit system.
University of Minnesota M.S. thesis. December 2019. Major: Civil Engineering. Advisor: Alireza Khani. 1 computer file (PDF); vi, 61 pages.
Refined Choice Set Generation and The Investigation of Multi-Criterion Transit Route Choice Behavior.
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