Using Predicted Bicyclist and Pedestrian Route Choice to Enhance Mode Choice Models

Abstract

Recent advances in bicyclist and pedestrian route choice modeling have shown that a variety of attributes affect the paths chosen for cycling and walking. They also allow one to estimate the effect on route choice of specific network changes, such as new bicycle facilities or pedestrian crossings. Route choices do not, however, tell one anything explicit about changes in decisions to walk or cycle in the first place. Cyclists might go out of their way to use a bike lane or to avoid a busy street, but how do those same features along a potential route influence the choice to cycle instead of using another travel mode? Route choice models are applied to predict the cycling and walking routes considered for a given trip, and the resulting route-level attributes are used to predict trip mode choice. In general, existing route preferences do carry over to mode choice, but with important differences, especially for bicycle facility types and female cyclists. The results show that available off-street paths and low-traffic on-street routes not only draw cyclists from other facilities but also make prospective riders more likely to cycle on a given trip. Gender differences are found for decisions to bicycle, with women showing a lower propensity than men to cycle on a similar trip and also stronger sensitivity to the availability of routes with lower traffic stress. Traffic-calmed streets, such as bicycle boulevards, may be particularly important in reducing the observed bicycling gender gap for everyday travel.