Automatic Recognition and Understanding of the Driving Environment for Driver Feedback

Details

• Creators:
  Zhou, Jifu ; Navarro-Serment, Luis E. ; Hebert, Martial
• Corporate Creators:
  Carnegie-Mellon University. Robotics Institute
• Corporate Contributors:
  University Transportation Centers Program (U.S.)
• Subject/TRT Terms:
  • Intelligent vehicles
  • Advanced driver information systems
  • Driver information systems
  • Smart driving
  • Research Hub
  • Data and Information Technology
  • Highways
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• TRIS Online Accession Number:
  01666089
• Corporate Publisher:
  Technologies for Safe and Efficient Transportation. University Transportation Center
• Description:
  A smart driving system must consider two key elements to be able to generate recommendations and make driving decisions that are effective and accurate: The environment of the car and the behavior of the driver. The long-term goal of this project is to develop techniques for building internal models of the vehicle’s static environment (objects, features, terrain) and of the vehicle’s dynamic environment (people and vehicle moving in the vehicle’s environment) from sensor data, which can operate online and can be used to provide the information necessary to make recommendations, to generate alarms, or to take emergency action. The overall approach is to combine recent progress in machine perception with the rapid advent of onboard sensors, and the availability of external data sources, such as maps.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/36114/dot_36114_DS1.pdf
• File Type:
  [PDF - 2.80 MB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha256:b4c9abb1d59ae52a5e40bceae8001df92dc9288022e3fe942104227d5ecf79df