Toward More Robust Spatial Sampling Strategies for Non-motorized Traffic

With the widespread promotion of New Urbanism and Smart Growth there is an assumption that levels of non-motorized traffic are increased. However, planners and analysts for non-motorized transportation modes still rely on very limited data resources and are therefore limited in identifying demand patterns and moving forward with more productive management and planning schemes. In this study, we utilized continuous non-motorized traffic counts collected along four share use paths in Chittenden County, Vermont and analyzed the association between hourly (volume percentages of daily total) distribution patterns at each count station and land uses in the adjacent areas. Our findings show the linkage is not as evident as expected between surrounding land use and the hourly patterns of the counts gathered, likely due to the insufficient diversity of the land use patterns around the count stations. Therefore, there is a dire need for a more robust sampling strategy to be developed to obtain counts efficiently that are able to extrapolate short period counts into region-wide travel estimates. In this study, we propose a spatial-based clustering analysis which identifies five land use categories to assist planning practitioners in selecting sampling locations that are representative for generating consistent non-motorized traffic counts for entire network.

Language

  • English

Media Info

  • Media Type: DVD
  • Features: Figures; References; Tables;
  • Pagination: 17p
  • Monograph Title: TRB 89th Annual Meeting Compendium of Papers DVD

Subject/Index Terms

Filing Info

  • Accession Number: 01150469
  • Record Type: Publication
  • Report/Paper Numbers: 10-3308
  • Files: BTRIS, TRIS, TRB
  • Created Date: Jan 25 2010 11:39AM