01656817

Component

The presence of bicycle infrastructure has been shown to influence cycling levels and mode choice. To reach more potential users and increase ridership, much effort has been done to improve cycling facilities with recent emphasis on providing protected bicycle facilities separated from vehicular traffic. It has been hypothesized that less confident cyclists prefer protected or off-street facilities compared to traditional bicycle lanes that only separate motor vehicle traffic and cyclists with striping. It has also been documented through national design guidance that off-street shared-use paths do not substitute for the need for on-street bicycle facilities. This study uses one full year of global positioning system (GPS) route data from the Auburn University’s bike share program to model facility choice between an ideal on-street bicycle lane and off-street shared-use path. By selecting a site where both bicycle facility types are present, the analysis found that slightly more than half of the almost 900 trips were taken on the bicycle lane. A binary logic regression model was run using calculated user demographics, annual travel patterns and trip characteristics to determine what variables influence the facility choice. The modeling and analysis validates the difference in bicycle users where confident, regular cyclists overall prefer direct, on-street bicycle facilities while less confident and less experienced cyclists would rather ride on a protected facility away from traffic even if it requires sharing the path with pedestrians and is a slightly less direct route.

This paper was sponsored by TRB committee ANF00 Section - Pedestrians and Cycles. Alternate title: Cyclists' Preferences for Bike Lanes Versus Road-Adjacent Shared-Use Paths Using a Year-Long Bikeshare GPS Data Set

18-00826

English

5p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

References; Tables

Alternatives analysis; Bicycle lanes; Bicycles; Bikeways; Cyclists; Global Positioning System; Logistic regression analysis; Revealed preferences; Route choice; Vehicle sharing

Auburn University

Data and Information Technology; Pedestrians and Bicyclists; Planning and Forecasting; Terminals and Facilities

Transportation Research Board Annual Meeting 2018 Paper #18-00826

TRIS, TRB, ATRI

Jan 8 2018 10:12AM