Data Mining to Improve Planning for Pedestrian and Bicyclist Safety

Technological advancement in transportation has been creating new opportunities to explore and investigate new sources of data for the purpose of improving safety planning. The proposed project will investigate data from multiple sources, including automated pedestrian and bicycle counters, video cameras, crash databases, and global positioning system (GPS)/mobile applications (both active and passive monitoring), to inform bicycle and pedestrian safety improvements. The project goal is to combine/integrate and use the strength of these data sources to produce useful insights in transportation safety planning. While it may not be possible to use all these data sources due to data unavailability, data ownership, and other unforeseen issues, the research team will do their best to obtain and use data from as many sources as feasible. To estimate pedestrian and bicyclist counts at intersections, exposure models will be developed incorporating explanatory variables from a broad spectrum of data sources. Intersection related crashes and estimated exposure will then be used to build risk models that identify high risk intersections.

• Record URL:
  http://www.vtti.vt.edu/utc/safe-d/index.php/projects/data-mining-to-improve-planning-for-pedestrian-and-bicyclist-safety/

Language

• English

Project

• Status: Active
• Funding: $289793
• Contract Numbers:

  69A3551747115

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Safety through Disruption University Transportation Center

  Virginia Tech Transportation Institute
  Blacksburg, VA  United States  24060
• Project Managers:

  Harwood, Leslie

• Performing Organizations:

  San Diego State University

  5500 Campanile Dr
  San Diego, CA  United States  92182

  Texas A&M Transportation Institute

  Texas A&M University System
  3135 TAMU
  College Station, TX  United States  77843-3135

  Virginia Tech Transportation Institute

  3500 Transportation Research Plaza
  Blacksburg, Virginia  United States  24061
• Principal Investigators:

  Jahangiri, Arash

• Start Date: 20170401
• Expected Completion Date: 20181230
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Bicycles; Crash data; Data mining; Global Positioning System; High risk locations; Intersections; Mobile applications; Pedestrian safety
• Subject Areas: Data and Information Technology; Pedestrians and Bicyclists; Safety and Human Factors;

Filing Info

• Accession Number: 01632141
• Record Type: Research project
• Source Agency: Safety through Disruption University Transportation Center
• Contract Numbers: 69A3551747115
• Files: UTC, RiP
• Created Date: Apr 4 2017 12:18PM