Reference Machine Vision for ADAS Functions

Studies have shown that fatalities due to unintentional roadway departures can be significantly reduced if Lane Departure Warning and Lane Keep Assist systems are used effectively. However, these systems have not been widely adopted due, in part, to the lack of suitable standards for pavement markings that enable reliable functionality of sensor systems. The objective of this project is to develop a reference lane detection system that will provide a benchmark for evaluating different lane markings and perception algorithms. The project will also validate the effectiveness of lane markings’ material characteristics as well as the vision algorithms through a systematic testing of lane detection algorithms in a robust test/vehicle environment.

• Dataset URL:
  https://doi.org/10.15787/VTT1/5FGGKD
• Record URL:
  https://safed.vtti.vt.edu/wp-content/uploads/2021/06/Safe-D_Report-04_115_Final-Report.pdf
• Summary URL:
  https://safed.vtti.vt.edu/projects/reference-machine-vision-for-adas-functions/
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/60228
• Dataset URL:
  https://rosap.ntl.bts.gov/view/dot/61535
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program. Supporting datasets available at: https://doi.org/10.15787/VTT1/5FGGKD; https://rosap.ntl.bts.gov/view/dot/61535
• Corporate Authors:

  Safety Through Disruption University Transportation Center (Safe-D)

  Texas A&M Transportation Institute
  College Station, TX  United States 

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Nayak, Abhishek
  • 0000-0003-0371-7747
  • Rathinam, Sivakumar
  • 0000-0002-9223-7456
  • Pike, Adam M
  • 0000-0002-5820-3084
• Publication Date: 2021-5

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Appendices; Figures; Maps; Photos; References; Tables;
• Pagination: 49p

Subject/Index Terms

• TRT Terms: Detection and identification systems; Driver support systems; Machine vision; Road markings; Traffic lanes
• Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01781912
• Record Type: Publication
• Report/Paper Numbers: 04-115
• Contract Numbers: 69A3551747115
• Files: UTC, NTL, TRIS, ATRI, USDOT
• Created Date: Sep 20 2021 2:52PM