Examination of Backing Crashes and Potential IVHS Countermeasures

Details

• Creators:
  Tijerina, Louis ; Hendricks, Donald ; Pierowicz, John ; Everson, Jeff ; Kiger, Steve
• Subject/TRT Terms:
  • Crash avoidance systems
  • Crash causes
  • Backing (Driving)
  • Human factors engineering
  • INTELLIGENT VEHICLE INITIATIVE OR IVI
• Publication/ Report Number:
  DOT HS 808 016 ; DOT-VNTSC-NHTSA-93-1
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Corporate Publisher:
  United States. Joint Program Office for Intelligent Transportation Systems
• Abstract:
  This report examines the potential for Intelligent Vehicle Highway System (IVHS) technology to improve the crash avoidance capability of drivers and vehicles for backing crashes. IVHS has the potential to greatly enhance highway traffic safety. This report attempts to determine the safety implications of IVHS by using analytical methods to model the backing crash type and potential IVHS crash avoidance countermeasures. The causal assessments show that approximately 87.0 percent of the cases occurred because drivers were unaware of (did not see or did not check for the struck vehicle, object, or pedestrian. Of the causal factors which appear to be amenable to IVHS countermeasures in the near term, the main causal factor appeared to be that the backing vehicle's driver was unaware of an obstacle. This suggested that a vehicle-based IVHS countermeasure that warns drivers of obstacles in the backing path might be helpful. The suggested countermeasure was a rear-zone object detection system. It is estimated that the functional rear-zone object detection system would be approximately 70 percent effective in avoiding the parallel path, curved path, and pedestrian/pedalcyclist crash subtypes. In terms of all backing crash subtypes, the system would be approximately 28 percent effective.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/2933/dot_2933_DS1.pdf
• File Type:
  [PDF - 903.72 KB]
• Collection(s):
  ITSJPO Digital Library
• Main Document Checksum:
  urn:sha256:a7b2c1289eeaf969440110b4564486e85735025378a5b3b9b3b13e335fdc5621