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Guidebook on Pedestrian and Bicycle Volume Data Collection

Author

Listed:
  • Ryus, Paul
  • Ferguson, Erin
  • Laustsen, Kelly M.
  • Schneider, Robert J.
  • Proulx, Frank R.
  • Hull, Tony
  • Miranda-Moreno, Luis

Abstract

NCHRP Report 797: Guidebook on Pedestrian and Bicycle Volume Data Collection is directed to practitioners involved in collecting non-motorized count data. The Guidebook (1) describes methods and technologies for counting pedestrians and bicyclists, (2) offers guidance on developing a non-motorized count program, (3) gives suggestions on selecting appropriate counting methods and technologies, and (4) provides examples of how organizations have used non-motorized count data to better fulfill their missions. The research behind the Guidebook can be found on the TRB website as NCHRP Web-Only Document 205: Methods and Technologies for Pedestrian and Bicycle Volume Data Collection (NWOD 205). NWOD 205 includes the results of the testing and evaluation of a range of automated count technologies that capture pedestrian and bicycle volume data.

Suggested Citation

  • Ryus, Paul & Ferguson, Erin & Laustsen, Kelly M. & Schneider, Robert J. & Proulx, Frank R. & Hull, Tony & Miranda-Moreno, Luis, 2014. "Guidebook on Pedestrian and Bicycle Volume Data Collection," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt11q5p33w, Institute of Transportation Studies, UC Berkeley.
    • Handle: RePEc:cdl:itsrrp:qt11q5p33w
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    References listed on IDEAS

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    1. Schneider, Robert J. & Arnold, Lindsay S. & Ragland, David R., 2009. "A Pilot Model for Estimating Pedestrian Intersection Crossing Volumes," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3nr8h66j, Institute of Transportation Studies, UC Berkeley.
    2. Schneider, Robert J. & Diogenes, Mara Chagas & Arnold, Lindsay S. & Attaset, Vanvisa & Griswold, Julia & Ragland, David R, 2010. "Association between Roadway Intersection Characteristics and Pedestrian Crash Risk in Alameda County, California," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0d48w4gz, Institute of Transportation Studies, UC Berkeley.
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    Cited by:

    1. Md Mintu Miah & Kate Kyung Hyun & Stephen P. Mattingly & Hannan Khan, 2023. "Estimation of daily bicycle traffic using machine and deep learning techniques," Transportation, Springer, vol. 50(5), pages 1631-1684, October.
    2. Clifton, Kelly J. & Singleton, Patrick A. & Muhs, Christopher D. & Schneider, Robert J., 2016. "Representing pedestrian activity in travel demand models: Framework and application," Journal of Transport Geography, Elsevier, vol. 52(C), pages 111-122.
    3. Hwachyi Wang & S. K. Jason Chang & Hans De Backer & Dirk Lauwers & Philippe De Maeyer, 2019. "Integrating Spatial and Temporal Approaches for Explaining Bicycle Crashes in High-Risk Areas in Antwerp (Belgium)," Sustainability, MDPI, vol. 11(13), pages 1-28, July.
    4. Jestico, Ben & Nelson, Trisalyn & Winters, Meghan, 2016. "Mapping ridership using crowdsourced cycling data," Journal of Transport Geography, Elsevier, vol. 52(C), pages 90-97.
    5. Wang, Hwachyi & De Backer, Hans & Lauwers, Dirk & Chang, S.K.Jason, 2019. "A spatio-temporal mapping to assess bicycle collision risks on high-risk areas (Bridges) - A case study from Taipei (Taiwan)," Journal of Transport Geography, Elsevier, vol. 75(C), pages 94-109.
    6. Mohammad Anwar Alattar & Caitlin Cottrill & Mark Beecroft, 2021. "Sources and Applications of Emerging Active Travel Data: A Review of the Literature," Sustainability, MDPI, vol. 13(13), pages 1-17, June.
    7. Munira, Sirajum & Sener, Ipek N., 2020. "A geographically weighted regression model to examine the spatial variation of the socioeconomic and land-use factors associated with Strava bike activity in Austin, Texas," Journal of Transport Geography, Elsevier, vol. 88(C).

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    Keywords

    Engineering; NCHRP; pedestrian; bicycle; safeTREC;
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