Abstract
This paper develops an approach that uses GIS and an unlabeled multinomial logit (MNL) model to estimate the impact bridge facility attributes have on bicycle travel behavior. The data used to estimate the model were collected from May to October 2011 in Austin, TX via a GPS-based smartphone application that allowed trips to be tracked in real time. Demographic (age, gender, and cycle frequency) and trip purpose information was also collected. Three attributes are analyzed in the model: bridge accessibility to the bicycle network, vehicular volume, and bicycle separation from traffic. Accessibility and bicycle separation significantly impacted bicyclists' behavior, especially for female and infrequent bicyclists as well as for trips where travel time is not a significant issue. Distance was also analyzed and found to be the most significant factor, particularly for time-constrained trips (trips during the peak period and commute trips). Distance was less important for recreational trips as well as for female bicyclists.
Published Version
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