Geospatial Analysis of Bicycle Network "Level of Traffic Stress", Bicycle Mode Choice Behavior, and Bicycle Crashes for Risk Factor Identifcation

Abstract

Small and medium-sized cities need publicly acceptable criteria for bicycle infrastructure improvements. This report explores the effectiveness of one proposed system of bicycle infrastructure criteria using data from a state-of-the-art travel survey, the Oregon Household Activity Survey (OHAS), and census journey-to-work data for the Salem-Keizer metropolitan area. In addition, this report also attempts to explore the geospatial correlation between bicycle level of traffic stress and where bicycle crashes happen. Results show that commuters ( i.e., employees and students) with low-stress connectivity to work and school are more likely to commute by bicycle, but also show that some demographic variables like race and income correlate with households’ low stress connectivity. The count model of household bicycle trip production in the Salem-Keizer region produced in this report illustrates that the size of a household’s adjacent “island” of low-stress bicycle connectivity correlates positively with bicycle trip production. In contrast, modeling with census data fails to show any correlation between bicycle commute mode share at the “is -land” scale and low-stress network connectivity. The mixed results suggest the range of a commuters’ low-stress bicycle network alone may not be a primary factor in the decision to bike. In combination with existing literature, we consider how the effect of low-stress connectivity on cycling to destinations relies on travelers’ awareness of low stress connections between origins and destin ations. Further research should identify level of service criteria that can predict cycling rates yet remain cost effective for small communities to map.