Non-motorized travel modes, and cycling in particular, are experiencing a resurgence in many U.S. states as well as in other countries. Still, most studies usually focus on bicyclists’ behaviors in areas with strong bicycling cultures. As part of two separate projects, a survey was deployed in areas without a strong bicycling culture (N=1188, N=1335), with the intent to measure the preferences for cycling infrastructure among current and potential cyclists. Separate analyses have been conducted on each of these datasets independently. This project calls for the combination of these two datasets to allow for a more statistically robust analyses and a more general description of variations between different sites. Initial regression models will be used to describe stated preferences for bicycle infrastructure using explanatory variables such as the presence of parking, number of lanes, and the type of bicycle facility. Further models will then be developed, including the addition of sociodemographic and attitudinal data, as well as the investigation of other model structures, such as segmented models and multinomial logit models.
This project will also have access to data from an ongoing follow-up survey with which models from the first wave will be re-estimated and analyzed. Mode choice data will also be analyzed from the two survey waves, with a special interest in exploring any shifts in mode choice throughout the panel and how these mode shifts can influence the general system and their impacts on energy and emissions. Results from this study provide useful insights into ways to promote sustainability, maximize the return of investments, and design bike infrastructure that can attract patronage and be most successful in areas lacking a substantial bicycling population.