Safety Enhancement by Detecting Driver Impairment Through Analysis of Real-Time Volatilities [Research Brief]

Details

• Creators:
  Khattak, Asad J.
• Corporate Creators:
  Collaborative Sciences Center for Road Safety ; University of Tennessee, Knoxville
• Corporate Contributors:
  United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology ; United States. Department of Transportation. University Transportation Centers (UTC) Program
• Subject/TRT Terms:
  • Biometrics
  • Detection and identification systems
  • Distraction
  • Driver support systems
  • Environment
  • Impaired drivers
  • Mathematical models
  • Simulation
  • Telemetry
  • Traffic safety
  More +
• Resource Type:
  Brief
• Geographical Coverage:
  United States
• Corporate Publisher:
  Collaborative Sciences Center for Road Safety
• Abstract:
  Distracted driving can lead to driving instability and result in crashes causing injuries and the loss of valuable lives. Early detection of driver distraction is critical to alert drivers by providing feedback and warning messages. This project develops a framework to detect driver impairment using extensive real-time driver biometric information and data related to vehicle kinematics and the roadway environment. Data from multiple sources, including driver gaze data, vehicle kinematics indicators, and external factors like interaction with surrounding traffic, are collected and analyzed.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/77716/dot_77716_DS1.pdf
• File Type:
  [PDF - 592.97 KB]
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:b954eae5ed03070d273bad1fd586c5b24b7a1aa6eb16e85bc7ce216973215f1e48750c782e8991a8c4d46639b0c327595e663da51a941676fc44f4ddc2142985