United States Department of Transportation
i
Investigating Tools for Evaluating Service and Improvement Opportunities on Bicycle Routes in Ohio
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2019-08-01
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[PDF-4.79 MB]
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Alternative Title:Investigating Tools for Evaluating Service and Improvement Opportunities on Bicycle Routes on Ohio’s Local System [Alternate Title from Title Page]
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Edition:Final Report
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Abstract:Over the past two decades, transportation engineers and urban planners have become increasingly interested in using performance measures to capture roadway infrastructure effects on bicyclists’ comfort levels. This study develops a useful tool to evaluate current service levels and identify improvement opportunities on Ohio’s local roadway network. The research team begins by assessing the available data sources required to develop a customized model for Ohio. Stakeholder interviews and data assessment outcomes indicate that most local jurisdictions do not have access to all relevant data for a complete bicycle LTS analysis. Therefore, the team extends the original bicycle LTS framework by formulating effective methods to deal with missing data. The designed methods are based on Ohio’s functional classification system, and existing data on speed limits, traffic volumes, and bicycle facility widths. Although this approach enables agencies to conduct bicycle LTS analysis when critical data elements are missing (such as posted speed limits, traffic volumes, and bicycle facility widths), it may produce partially incorrect assignments. For instance, analyses based on Mid-Ohio region data show that in cases where road traffic volumes are missing, the research team’s approach replicates the results with an 18.6% mismatch in bicycle LTS score assignments overall. The mismatch percentage breaks down to 10.0% in urban areas and 27.5% in rural areas. Given this outcome, the research team recommends that local communities collect all necessary data before conducting a bicycle LTS analysis. The team’s approach to handling missing data can help when collecting accurate data is not feasible due to time and cost considerations, and in cases where interim and temporary results may prove useful while acquiring these data.
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