Methods for estimating bicycling and walking in Washington state.
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Methods for estimating bicycling and walking in Washington state.

  • 2014-05-01

Filetype[PDF-1.73 MB]


  • English

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      This report presents the work performed in the first and second phases in the process of creating a method to calculate Bicycle and Pedestrian Miles Traveled (BMT/PMT) for the state of Washington. First, we recommend improvements to the existing Washington State Bicycle and Pedestrian Documentation Program to provide data for BMT/PMT estimates, including expanding the program geographically and installing permanent automated bicycle and pedestrian counters to complement the short duration count program. The method to estimate BMT/PMT relies on the assumption of a stratified random sample drawn from the set of all roads and paths divided into 16 groups. These groups are based on three spatial attributes, which were gathered from a review of the literature: • Level of urbanism (2 categories): Urban and Rural • Facility type (2 categories): Highway/Arterial and Other • Geographic/climatic regions (4 regions): Coast Range, Puget Lowland, Cascades, Eastern Washington This report describes the first steps being taken toward the goal of computing this metric. Count data from Seattle, Olympia, and the State’s Count Program have been gathered. To account for temporal variation, seasonal, daily and hourly adjustment factors have been computed based on one year of count data collected from the Fremont Bridge in Seattle. The short duration count sites have been grouped by the attributes described above, though most fall into just two groups: Puget Lowland Urban Arterial/Highway and Puget Lowland Urban Local/Collector/Path. Little or no data are available in most of the other groups. The roads in the state have also been divided into these 16 groups in order to compute total centerline miles for each group. This report outlines a sample-based method that could be used to compute BMT/PMT for the state and identifies both the data available for such a computation as well as the data gaps. It also suggests other methods that could also be used to estimate BMT/PMT to compare to the count-based method.
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