Computational Imaging for Improving Vehicle Safety

Details

• Creators:
  Sankaranarayanan, Aswin ; Bhagavatula, VIjayakumar
• Corporate Creators:
  Carnegie Mellon University ; Carnegie Mellon University. Traffic21 Institute. Safety21 University Transportation Center (UTC)
• 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:
  • Depth perception
  • Weather conditions
  • Fluid dynamics
  • Photons
  • Fog
  • Algorithms
  • Driver support systems
  • Image analysis
  • Pedestrian safety
  • Sensors
  More +
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report (July 1, 2023-June 30, 2024)
• Corporate Publisher:
  Carnegie Mellon University. Traffic21 Institute. Safety21 University Transportation Center (UTC)
• Abstract:
  This project investigates the design and deployment of sensors and associated algorithms for handling harsh imaging conditions. We are interested in depth perception in rain, snow and fog. By expanding the depth range at which objects can be reliably detected, especially in dense fog, the project will facilitate a higher level of safety for vulnerable road users.
• Format:
  PDF
• Funding:
  69A35523244811
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/77499/dot_77499_DS1.pdf
• File Type:
  [PDF - 7.73 MB]
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:053d684d497d3aca76f90ad726de7e3482a8c50e3a9084ee1a899a76cc0781f55eceac8639aeb838a4c52278acfd305ad9008eae71a249ae714ae593dda443bf