An unlabeled multinomial logit model is developed to estimate the impact bridge facility attributes have on bicycle travel behavior. Data were collected in Austin, Texas, via a GPS-based smartphone application. Three attributes are analyzed and interacted with varied demographic and trip purpose information: bridge accessibility, vehicular volume, and traffic separation. Due to the significant investment in bicycle facilities at the local, state, and federal levels and the increase in urban bicycle use, it is imperative that agencies fully understand the behavioral elements underlying bicycle travel patterns. Transportation planners cannot assume bicyclists are solely focused on minimizing travel time or distance—standard practice assumptions for vehicular modes. This paper focuses on the analysis of bridge characteristics that are attractive to bicyclists. While several others have looked at bicycle facility preferences, this is the first paper to focus exclusively on bridges. Bridge facilities are fundamentally different from the res
