Modeling the Impacts of Facility Type, Trip Characteristics, and Trip Stressors on Cyclists’ Comfort Levels Utilizing Crowdsourced Data

Abstract

Transportation agencies are striving to increase the comfort of their bicycle networks in an effort to improve the experience of existing cyclists and to attract new cyclists. To increase bicycle mode share is challenging and has motivated research to understand where and what types of bicycle improvements yield the maximum net benefit in terms of increased ridership, comfort, and safety. Data sets related to cyclists’ comfort levels as a function of bicycle infrastructure are nonexistent at the state or local level. To fill this data gap, the Oregon Department of Transportation sponsored the development of ORcycle, a smartphone application designed to collect cyclist travel, comfort, and safety information. The research reported in this paper utilized ORcycle data to model cyclists’ comfort levels as a function of bicycle facility types, sources of stress along the trip, and trip characteristics (e.g., purpose, length, frequency, and day of the week). Ordinal logistic regression models were estimated, and the results indicated that facility types such as bicycle boulevards and separated paths did have a significant positive impact on cyclists’ comfort levels. Other variables (e.g., sources of stress along the trip, trip purpose, and trip distance) also were found to have significant impacts on comfort levels. A sensitivity analysis and a policy discussion highlight how important it is to reduce sources of stress along bicycle routes to increase bicycle ridership and attract new cyclists.