Thesis (Ed. D.)--University of Missouri-Columbia, 1998. / Typescript. Vita. Includes bibliographical references (leaves 70-73). Also available on the Internet.

Thesis (Ed. D.)--University of Missouri-Columbia, 1998. / Typescript. Vita. Includes bibliographical references (leaves 70-73). Also available on the Internet.

Thesis (Ph.D.)--University of Texas at Austin, 2008. / Includes vita. Includes bibliographical references (p. 200-216). Also available online.

No description available.

This research studies travelers' route choice behavior in a driving simulator with real-time information en-route. We investigate whether travelers plan strategically for real-time information en-route or simply select a fixed path from origin to destination at the beginning of a trip, and whether network complexity and a parallel driving task affect subjects' strategic thinking ability. In this study, strategic thinking refers to a traveler's route choice decision taking into account future diversion possibilities downstream enabled by information at the diversion node. All of the subjects in this study participated in driving-simulator-based tests while half of the subjects participated in additional PC-based tests. Three types of maps were used. The first type required a one-time choice at the beginning of a trip to test the traveler's risk attitude. The other two types offered route choices both at the beginning of and during a trip to test the traveler's strategic thinking. The study shows that a significant portion of route choice decisions are strategic in a realistic driving simulator environment. Furthermore, different network complexities impose different cognitive demands on a subject and affect his/her strategic thinking ability. A subject tends to be more strategic in a simple network. Lastly, a parallel driving task does not significantly affect a subject's strategic thinking ability. This seemingly counterintuitive conclusion might be caused by the simplicity of the tested network.

The events of September 11,2001 followed by the oil price hike and the economic crisis of 2008, have lead to a drop in the demand for air travel. Airlines have attempted to return to profitability by cutting service in certain unattractive routes and airports. Simultaneously, delays and excess demand at a few major hubs have lead to airline introducing service at reliever airports. This dissertation attempts to capture the changes in the airline network by utilizing a supply-demand framework. / Ph. D.

The rise of micromobility, most notably electric standing scooters (e-scooters), has resulted in new challenges for traffic planning and road safety. One such issue is the fact that in most European countries, e-scooter users are obliged to ride their vehicle on cycling infrastructure and thereby share this infrastructure with bicyclists. This increases the use of and, subsequently, demand for bicycle lanes, which is an obvious challenge for transport planning. However, for adequate planning and construction of cycling infrastructure, information on route choice behavior of bicyclists and e-scooter users and its influencing factors is necessary. While research on bicyclists' route choice is well advanced, research on e-scooter riders is still in its infancy. For bicyclists, the presence of bicycle facilities, traffic volume, and travel time are among others particularly important for route choice. However, the question arises whether this also applies to e-scooter riders as vehicle dynamics are different and riders are, at least for now, less skilled due to lack of training and exposition. In order to fill this research gap, we aimed to analyze the determinants for route choice of e-scooter users in comparison to bicyclists in a field study. [from Introduction]

No description available.

Driver heterogeneity in travel behavior has repeatedly been cited in the literature as a limitation that needs to be addressed. In this work, driver heterogeneity is addressed from four different perspectives. First, driver heterogeneity is addressed by models of driver perceptions of travel conditions: travel distance, time, and speed. Second, it is addressed from the perspective of driver learning trends and models of driver-types. Driver type is not commonly used in the vernacular of transportation engineering. It is a term that was developed in this work to reflect driver aggressiveness in route switching behavior. It may be interpreted as analogous to the commonly known personality-types, but applied to driver behavior. Third, driver heterogeneity is addressed via latent class choice models. Last, personality traits were found significant in all estimated models. The first three adopted perspectives were modeled as functions of variables of driver demographics, personality traits, and choice situation characteristics. The work is based on three datasets: a driving simulator experiment, an in situ driving experiment in real-world conditions, and a naturalistic real-life driving experiment. In total, the results are based on three experiments, 109 drivers, 74 route choice situations, and 8,644 route choices. It is assuring that results from all three experiments were found to be highly consistent. Discrepancies between predictions of network-oriented traffic assignment models and observed route choice percentages were identified and incorporating variables of driver heterogeneity were found to improve route choice model performance. Variables from all three groups: driver demographics, personality traits, and choice situation characteristics, were found significant in all considered models for driver heterogeneity. However, it is extremely interesting that all five variables of driver personality traits were found to be, in general, as significant as, and frequently more significant than, variables of trip characteristics — such as travel time. Neuroticism, extraversion and conscientiousness were found to increase route switching behavior, and openness to experience and agreeable were found to decrease route switching behavior. In addition, as expected, travel time was found to be highly significant in the models that were developed. However, unexpectedly, travel speed was also found to be highly significant, and travel distance was not as significant as expected. Results of this work are highly promising for the future of understanding and modeling of heterogeneity of human travel behavior, as well as for identifying target markets and the future of intelligent transportation systems. / Ph. D.

Commuter rail is increasingly popular as a means to introduce rail transportation to metropolitan transportation systems. The long-term benefits of commuter rail include the addition of capacity to the transportation system, providing a quality commute alternative, and shifting land use toward transit-oriented development patterns. The success of a commuter rail system depends upon cultivating a ridership base upon which to expand and improve the system. Cultivating this ridership is dependent upon offering a quality transportation option to commuters. Characteristics of commuter rail systems in the United States present challenges to offering quality service that must be overcome. Commuter rail has been implemented only on existing rail right-of-way (ROW) and infrastructure (depending upon condition) in the United States. Existing rail ROW does not often coincide with current commercial and residential demand centers and necessitates the use of a circulator system to expand the service boundary of commuter rail to reach these demand centers. The commuter rail circulator network design problem (CRCNDP) addresses a particular aspect of the commuter rail trip, seeking to improve the performance of the entire system through accurately modeling the portion of the trip from rail station to the final destination. This final leg includes both the trip on the circulator vehicle and the walking trip from the circulator stop to the final destination. This dissertation seeks to provide an innovative mathematical programming formulation and solution methodology for the CRCNDP and apply this method to a case study.