Estimating walking and bicycling at the state level.

Details

• Creators:
  Nordback, Krista ; Sellinger, Michael ; Phillips, Taylor
• Corporate Creators:
  Portland State University
• Corporate Contributors:
  Portland State University. Transportation Research and Education Center (TREC) ; United States. Department of Transportation. University Transportation Centers (UTC) Program
• Subject/TRT Terms:
  • Bicycling
  • Walking
  • Pedestrian counts
  • Traffic counts
  • Travel surveys
  • Statistical sampling
  • Demographics
  • Data collection
  • Person miles of travel
  • Estimating
• Publication/ Report Number:
  NITC-RR-708
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States;Washington
• Edition:
  Final report
• Corporate Publisher:
  National Institute for Transportation and Communities (NITC)
• Abstract:
  Estimates of vehicle miles traveled (VMT) drive policy and planning decisions for surface transportation. No similar ; metric is computed for cycling and walking. What approaches could be used to compute such a metric on the state ; level? This report discusses three such approaches, identifies the advantages and disadvantages of each, and applies ; them to Washington State. The first approach employs travel survey data. The second approach is sample-based using ; pedestrian and bicycle count data. The third approach is an aggregate demand model approach using demographic data ; combined with count data. Due to data limitations, none of these methods could be properly implemented on the ; statewide level. Despite the data limits, the methods were implemented for one county (King County) in order to ; compare findings. The travel survey method estimated the lowest bicycle and pedestrian miles traveled (BMT and ; PMT), and the sample-based method estimated the highest. The travel survey method is useful for a statewide measure, ; but it does not provide the detail needed for facility-level estimates. For bicyclists, the sample-based method is ; appropriate if volumes are desired at the facility level. For pedestrians, the aggregate model might be more appropriate, ; because of the more dispersed nature of pedestrian travel. Each method has strengths and weaknesses, and each helps ; us understand bicycle and pedestrian travel in different ways. ; For this reason, the project team recommends improving both statewide travel survey data and pedestrian and cyclist ; traffic count data which feed these methods. Travel survey data should be collected statewide with oversampling for ; non-motorized travelers. Pedestrian and cyclist traffic counts should be expanded to include a continuous counting ; program in addition to the short-duration count program. After the continuous count program is in place, short-duration ; counts should be chosen using a stratified random sampling approach. For example, the sampling frame could consist ; of all road and path segments in the state divided by region (Coast Range, Puget Lowland, Cascades, Eastern ; Washington), by urbanity (rural, urban), by facility type (highways/arterials, local/collector roads, paths), and by ; whether the location is on a bridge or not. To increase sites sampled, the short-duration count program could also be ; rotated, with each location being counted every three years instead of every year. Better data will allow the state to ; quantify bicycling and walking at both the state level and facility level to inform decision-making, facility design and ; planning, and safety analysis.
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• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/32303/dot_32303_DS1.pdf
• File Type:
  [PDF - 3.17 MB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:c035b7596abcbccfd20628156dd19dcc7a1ebb9dfb4242ad2648f1b9b4e16bd17bded2811013272a2dd74e97c06ef127fbbe266d67f5572e6499dae163165f49