New and Unique Aspects of University Campus Transportation Data to Improve Planning Methods

Abstract

University campuses have unique characteristics that influence travel demand. They benefit from controlled planning frameworks, can influence almost all aspects of pricing and on-campus transportation infrastructure, benefit from simplified many-to-one travel patterns, and maintain extensive data on nearly the entire campus community. Campuses represent millions of trips daily, yet little research has been conducted that focuses on developing tailored frameworks to assess transportation demand, target travel demand management strategies, or to assess environmental or other impacts. This paper describes how two sets of commonly collected data can be leveraged to provide new insights into travel behavior, incentives, and environmental policy. Specifically, we illustrate the fusion of standard travel demand survey data with disaggregate and precise household address data to provide new inferences into appropriate strategies to improve transportation sustainability. We applied three use-cases—carpool potential, walk and bike incentives, and mode shift to reduce greenhouse gas emissions—to the data from three universities, University of Tennessee, Cal Poly San Luis Obispo, and San Diego State University, respectively. We found that the richer dataset provided substantially better data resolution that allowed for transportation strategies to be more precisely targeted and expansion of the potential impact of transportation demand management strategies.

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