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A transportation system to move students, faculty and staff on a university campus and its surrounding community continues to be an unmet need for most North American universities. A very important reason behind this problem is that effective methodologies to model travel demand in a university setting are not available, nor are analysis tools to compare the existing mobility with the projected mobility where major transportation improvement is planned for a university setting. In this study, a multi-modal travel demand model was developed to model the travel demand of students, faculty and staff in various transportation scenarios on a university campus and its surrounding community. The modeling methodology has several innovative characteristics, which adapt the model to a university setting and differentiate it from traditional travel demand models, including: (1) Individual trip generation and trip distribution information, such as class schedule, residence addresses, office addresses, etc., were used to construct student, faculty and staff trip tables; (2) A multi-modal transportation network was constructed that reflects the necessary interaction among motor vehicles, pedestrians, parking facilities and public transit facilities; and (3) A time-of-day model that uses probability distribution functions to simulate temporal distribution of trips was developed to realize the incremental trip assignment. The model was used to evaluate an existing transportation system and two alternatives, each with a Personal Rapid Transit (PRT) system assumed constructed on the Kansas State University main campus. A multi-measure evaluation approach was developed to evaluate the mobility impact of the transportation alternatives examined. The evaluation results indicate that an appropriately designed PRT system could improve the mobility on a university campus, by saving travel time, increasing predictability of travel time throughout a weekday, relieving traffic congestion, and making distant parking lots as accessible as those close to or within the core campus area. The model performed well and generated reasonable results. The study methodology developed should be usable, without significant change, to other universities that have similar size and travel characteristics.
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