A direct-demand model for bicycle counts: the impacts of level of service and other factors. (January 2016)

• Record Type: Journal Article
• Authors: Fagnant, Daniel J; Kockelman, Kara
• Is Part Of: Environment and planning. Volume 43:Number 1(2016)
• Page Start: 93
• Page End: 107
• Publication Date: 2016-01
• Subjects: transportation planning -- bicycle -- cycling -- bike lanes -- traffic counts -- level of service; Architecture -- Research -- Periodicals; Building -- Research -- Periodicals; Land use -- Planning -- Periodicals; Architecture -- Research; Building -- Research; Land use -- Planning; Periodicals; 720.5
• DOI: 10.1177/0265813515602568
• Languages: English
• ISSNs: 0265-8135

Abstract

Transportation planning in the US has traditionally focused on automotive traffic but is increasingly turning towards a multimodal approach in order to accommodate all users. This shift in focus is particularly crucial for cyclists, as 630 were killed and 51 000 injured on America's roadways in 2009 alone. Unfortunately, most municipalities do not conduct comprehensive bicycle counts to determine where cyclists are riding, though some do seek a scatter of spot counts. This investigation uses Seattle metropolitan area cyclist-count data from 251 locations to develop a direct-demand model for estimating peak-period cyclist counts based on trip-generation and attraction factors (such as site-based population and employment densities), as well as cycling-relevant roadway conditions. Roadway-condition variables were chosen from the 2010 Highway Capacity Manual (Chapter 17, Transport Research Board, Washington, DC) on urban street segments (including factors like traffic volumes and bike-lane width), as well as other physical features, like bridge presence and access to bicycle trails. Model results show greatest practical significance for intersections within the City of Seattle and curb-lane width (both of which are associated with higher counts) and roadway speed (which is associated with lower counts). The model was implemented in the community of Shoreline, Washington, just north of Seattle, to demonstrate its applicability. We examined both segment-based levels of service for cyclists and expected intersection-based counts. Model application findings indicate that segment-based levels of service show little correlation with expected counts, though such information still serves a valuable purpose in terms of evaluating cyclists' comfort levels (which may also have potential correlation with cyclist safety), a worthwhile goal in itself. As such, these two models may be used in combination when targeting new cycling infrastructure and improvements.