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- W2291574596 abstract "Transportation planning in the US has traditionally focused on automotive traffic but is increasingly turning towards a multi-modal approach in order to accommodate all users. This shift in focus is particularly crucial for cyclists, as 630 were killed and 51 thousand 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’s Chapter 17 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 the City of Seattle indicator variable and curb lane width (both of which are correlated with higher counts) and roadway speed (which shows quadratic impacts, with expected counts highest around 35 mph and decreasing as speed becomes higher or lower). The model is implemented in the community of Shoreline, Washington, just north of Seattle, to demonstrate its applicability. As such, the evaluation examines both segment-based bicycle level of service and expected intersection-based counts. Model application findings indicate that segment-based bicycle level of service shows little correlation with expected counts, though such information may be used to target new cycling infrastructure improvements." @default.
- W2291574596 created "2016-06-24" @default.
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- W2291574596 date "2014-01-01" @default.
- W2291574596 modified "2023-09-23" @default.
- W2291574596 title "A Direct-Demand Model for Bicycle Counts: The Impacts of Level of Service and Other Factors" @default.
- W2291574596 hasPublicationYear "2014" @default.
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