Vehicle Automation and Transportability of Crash Modification Factors

Safety-based roadway design requires predicting a design's safety consequences, and the primary tools for making these predictions, compiled in the Highway Safety Manual, are based on regression-type statistical models and before/after studies fit to observational data. Like most empirical models these tools can give reasonable representations of the conditions in place when they were constructed, but extrapolating them to new conditions is problematic. In particular, these tools are functions of the driver and vehicle mix prevalent during the last 20 years or so, which are likely to change, possibly drastically, as vehicle automation becomes widespread. A major challenge facing safety researchers will then be to adapt, if possible, the extensive research that went into the Highway Safety Manual to these new and different conditions. Although a considerable and ongoing effort is being devoted to predicting the direct effects of vehicle automation (e.g. Rosen et al. 2010) to the researcher's knowledge no attention is being given to how vehicle automation will interact with existing road safety principles. This can be seen as a problem of determining the transportability (i.e. external validity) of estimated crash modification factors to these new conditions. Hauer et al (2012) and Persaud et al (2015) have initiated a discussion of this issue but to date the focus has been on geographical variability under the current driver/vehicle mix. Within the field of artificial intelligence however, Bareinboim and Pearl (2012, 2014) have developed analytic tools which could profitably be applied to this problem. This project will explore the usefulness of Bareinboim and Pearl's tools by looking at how vehicle automation could impact the crash reduction effects of two roadway-based countermeasures (1) installation of pedestrian hybrid beacons (PHB) at uncontrolled crosswalks and (2) offsetting opposing left-turn lanes at signalized intersections.

Language

  • English

Project

  • Status: Active
  • Funding: $63925
  • Contract Numbers:

    DTRT13-G-UTC35

    CTS-2018053

  • Sponsor Organizations:

    Research and Innovative Technology Administration

    University Transportation Centers Program
    1200 New Jersey Avenue
    Washington, DC  United States  20590

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Project Managers:

    Stearns, Amy

  • Performing Organizations:

    University of Minnesota Department of Civil, Environmental and Geo-Engineering

    500 Pillsbury Drive SE
    Minneapolis, MN  United States  55455
  • Principal Investigators:

    Davis, Gary

  • Start Date: 20180223
  • Expected Completion Date: 20190531
  • Actual Completion Date: 0

Subject/Index Terms

Filing Info

  • Accession Number: 01664794
  • Record Type: Research project
  • Source Agency: Roadway Safety Institute
  • Contract Numbers: DTRT13-G-UTC35, CTS-2018053
  • Files: UTC, RiP
  • Created Date: Mar 28 2018 1:01PM