Technology and Enhancements to Improve Pre-Crash Safety

This project focuses on technology improvements that can be implemented in intelligent and autonomous vehicles toward the goal of improving pre-crash safety. First, with autonomous vehicles being on the verge of deployment as part of city infrastructure, the need for autonomous vehicles to be capable of anticipating human driver intent is inescapable. Newer technologies and potentially controversial sensing options, such as gaze direction, driver body language/weight shifting, and even electroencephalogram (EEG) sensors, are available for exploration. Recent research has shown the crucial importance of gaze monitoring. For example, on the approach to curves, driver gaze direction can predict speed at the apex and crashes. Drivers' gaze duration on external signs can predict their ability to keep in their lane. The project proposes to explore technologies for sensing driver attention and their impact in pre-crash scenarios. In conjunction with Project 1, the project will design and test biomonitors and their value in improving crash safety. The project will also predict, using behavior models, the extent to which monitoring information can be effective in improving pre-crash safety. Second, the project will study the value of vehicle to infrastructure (V2I) and vehicle to vehicle (V2V) communications for improving pre-crash safety. Using simulator studies--and later, field tests for promising approaches--the project will study scenarios in which location and heading information for nearby vehicles is used, and will test its value in averting crashes or minimizing crash injury. An important element of this understanding is how the (in)accuracy of this information impacts safety performance. V2V hardware testing facilities in Ohio State University's (OSU's) Control and Intelligent Transportations Research (CITR) Laboratory will be used to quantify location accuracy in realistic scenarios. The project will also study information accuracy as it impacts information trust in the corresponding behavioral models being developed in Project 3. Third, the project will study the impact of both intra-vehicle and inter-vehicle communication cybersecurity on pre-crash scenarios. A number of issues are of concern: external "snooping"; injection of false information externally; and "hacking" the vehicular software. Several countermeasures are being developed, including key generation and filtering. The focus in the Crash Imminent Safety University Transportation Center (CrIS UTC) will be on the implications of cyber-threats on pre-crash safety. For example, cybersecurity countermeasures result in data latency; the project will investigate how this latency degrades safety margins. As a second example, inaccurate information, including false warning indicators that may result from either compromised security or communication noise reduce driver trust in the data, and result in a change of driver behavior in response to these indicators. The project will study these changes using the behavior models in Projects 2, 3, and 5, and assess the safety impact.

Language

  • English

Project

  • Status: Active
  • Funding: $302665.00
  • Sponsor Organizations:

    Research and Innovative Technology Administration

    University Transportation Centers Program
    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Performing Organizations:

    Ohio State University, Columbus

    410 West Tenth Avenue
    Columbus, OH  United States  43210
  • Principal Investigators:

    Ozguner, Fusun

    Homaifar, Abdollah

    Chen, Yaobin

    Ozguner, Umit

  • Start Date: 20130930
  • Expected Completion Date: 0
  • Actual Completion Date: 0
  • Source Data: RiP Project 35924

Subject/Index Terms

Filing Info

  • Accession Number: 01503180
  • Record Type: Research project
  • Source Agency: Crash Imminent Safety University Transportation Center
  • Files: UTC, RiP
  • Created Date: Jan 4 2014 1:00AM