Data Fusion for Non-Motorized Safety Analysis

Data-driven approaches play a critical role in developing safety improvement investment decisions. However, for non-motorized travel, exposure to risk has often been the missing piece of the puzzle. Safety analysts have been struggling with the lack of availability of exposure data, making it difficult to discern a trend in crash rates and identify high-risk locations for pedestrians and bicyclists. While short-term counts cannot be considered policy relevant (until they are scaled to a long-term representative value), continuous monitoring of non-motorized traffic using automatic sensors are often not cost effective. Moreover, every sensor has some limitations in terms of coverage, accuracy, and reliability. In the era of big data, global positioning system (GPS) data, cell phone tracking apps, fitness tracking devices or bike sharing systems hold great potential to observe travel activity but they include a range of biases related to representation. Recognizing these limitations and benefiting from the advancements in technologies, this project aims to develop effective methodologies to fuse together different data sources to develop accurate and reliable exposure estimates for safety analysis. The proposed framework will bring together traditional and emerging data sources, and will be developed in such a way that it can be up- or down-scaled based on the available data sources of a study area. The exposure estimation output will then be used for crash assessment tailored to the needs of the study area. The proposed approach will increase the quality and representativeness of data and help safety analysts to effectively derive benefits from potential sources in their decision making.


  • English


  • Status: Active
  • Funding: $478437
  • Contract Numbers:


  • 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 (Safe-D)

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

    Glenn, Eric

  • Performing Organizations:

    Texas A&M Transportation Institute

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

    Sener, Ipek

  • Start Date: 20180601
  • Expected Completion Date: 20210731
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01658897
  • Record Type: Research project
  • Source Agency: Safety through Disruption University Transportation Center (Safe-D)
  • Contract Numbers: 69A3551747115
  • Files: UTC, RIP
  • Created Date: Feb 2 2018 5:33PM