Roadway and Driver Factors Associated with Vulnerable Road User Detection During Naturalistic Driving

Details

• Creators:
  Shirani, Niloufar ; Tice, Patricia ; Orlova, Elena ; Rothermel, Noah
• Corporate Creators:
  New England University Transportation Center ; University of Connecticut ; ProFound Insights, Inc.
• Corporate Contributors:
  United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  • Vulnerable road users
  • Driving behavior
  • Eye movements
  • Attention
  • Traffic safety
  • Automatic data collection systems
  • Datasets
  • Pedestrians
  • Cyclists
  • Urban areas
  More +
• Publication/ Report Number:
  161549
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report
• Corporate Publisher:
  New England University Transportation Center
• Abstract:
  Although physical visibility is often assumed to ensure driver awareness, relatively little naturalistic evidence describes how drivers perceive vulnerable road users (VRUs) across real-world driving contexts. This study examined roadway and driver factors associated with detection of pedestrians, cyclists, and motorcyclists using synchronized multimodal data. Twenty-four participants completed two naturalistic drives over a fixed route representing rural, suburban, campus, and urban environments. Driver gaze was recorded using Tobii Pro Glasses 3, vehicle data using a CANbus/GNSS-IMU logger, and heart rate using a Polar H10 sensor. The synchronized dataset contained 3,526 annotated VRU encounters. Mixed-effects logistic regression identified factors associated with successful detection. Vehicle speed was the strongest factor, with each 1-mph increase associated with an approximately 5% reduction in detection odds (OR = 0.95, p < 0.001). VRUs on the right side of the roadway were twice as likely to be detected as those on the left (OR = 2.00, p < 0.001), and detection was higher in rural than urban environments (OR = 4.55, p = 0.019). Findings support speed management, context-sensitive roadway design, and driver-assistance systems to improve VRU safety.
• Format:
  PDF
• Funding:
  69A35523483
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/93394/dot_93394_DS1.pdf
• File Type:
  [PDF - 341.40 KB]
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:4ffe103c19a384a5b1225280b2ac3d4ee5fd7aa86166acb47427bd05d426302a7648edf48d1a48b4ee7233a8b147df6f873a7cb9606154391c8714f8038e9199