Browsing by Subject "Route Choice"

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    Refined Choice Set Generation and The Investigation of Multi-Criterion Transit Route Choice Behavior
    (2019-12) Tomhave, Benjamin
    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.
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    The roads taken: theory and evidence on route choice in the wake of the I-35W Mississippi River bridge collapse and reconstruction.
    (2010-09) Zhu, Shanjiang
    Route choice analysis investigates the path travelers follow to implement their travel plan. It is the most frequent, and thus arguably the most important decision travelers make on a daily basis. Long established efforts have been dedicated to a normative model of the route choice decision, while investigations of route choice from a descriptive perspective have been limited. Wardrop's first principle, or the shortest path assumption, is still widely used in route choice models. Most recent route choice models, following either the random utility maximization or rule-based paradigm, require explicit enumeration of feasible routes. The quality of model estimation and prediction is sensitive to the appropriateness of the consideration set. However, few empirical studies of revealed route characteristics have been reported in the literature. Moreover, factors beyond travel time, such as preferences for travel time reliability, inertia in changing routes, and travel experience that could also have significant impacts on route choice, have not been fully explored and incorporated in route choice modeling. The phenomenon that people use more than one route between the same origin and destination during a period of time is not addressed by conventional route choice models either. To bridge these gaps, this dissertation systematically evaluates people's route choice behavior using data collected in the Minneapolis - St. Paul metropolitan area after the I-35W Bridge Collapse. Both aggregate traffic data and individual survey data show gaps between models based on shortest travel time assumption and traffic conditions observed in the field. This study then employs the individual GPS trajectory and GIS maps to systematically evaluate the characteristics of routes people actually use. Merits of route choice set generation algorithms widely used in practice are assessed. The phenomenon of route diversity is clearly revealed through analysis of field data. A route portfolio model is proposed to explain the rationale of choosing a portfolio of routes under uncertainty about network conditions. It is posited that a rule-based model, comprehensively considering travelers' characteristics, additional network metrics, and previous travel experience will better replicate observed route choices than the traditional assumption of simply minimizing travel time or travel cost. Findings from this dissertation could also inform other parts of travel demand modeling.