SPR-2326: Automated Vehicle and Pavement Marking Evaluation in Connecticut

The objectives of this study are to determine areas or instances where advanced driver assistance systems (ADAS) have success as well as difficulties maintaining a “visual” on road markings. Furthermore, to identify if there are differences across makes, models, and technologies used to identify lane markings while a vehicle is operating under machine vision. The main objectives of this study can be summarized as below: (1) Evaluate the effect that various pavement marking characteristics such as color, condition, contrast, retroreflectivity, design, materials, etc. have on machine vision detection through an evaluation of consumer test vehicle performance operating on public roadway under various conditions as well as a pre- and post-improvement lane marking study design. (2) Explore the machine vision lane marking detection accuracy under various daytime and nighttime lighting conditions. (3) Explore the machine vision lane marking detection accuracy under mostly dry weather conditions, and potentially some wet weather conditions. (4) Explore the differences, if any, across different makes, models, and machine vision technologies used to detect lane marking and maintain safe operation under automated driving operation.

Language

• English

Project

• Status: Active
• Funding: $234,236
• Contract Numbers:

  SPR-2326

• Sponsor Organizations:

  Connecticut Department of Transportation

  2800 Berlin Turnpike
  P. O. Box 317546
  Newington, CT  United States  06131-7546
• Managing Organizations:

  Connecticut Department of Transportation

  2800 Berlin Turnpike
  P. O. Box 317546
  Newington, CT  United States  06131-7546
• Project Managers:

  Zimyeski, Melanie

• Performing Organizations:

  University of Connecticut, Storrs

  Connecticut Transportation Institute
  270 Middle Turnpike, Unit 5202
  Storrs, CT  United States  06269-5202
• Principal Investigators:

  Shaon, Mohammad Razaur Rahman

• Start Date: 20211228
• Expected Completion Date: 20230228
• Actual Completion Date: 0

Subject/Index Terms

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

Filing Info

• Accession Number: 01853902
• Record Type: Research project
• Source Agency: Connecticut Department of Transportation
• Contract Numbers: SPR-2326
• Files: RIP, STATEDOT
• Created Date: Aug 4 2022 1:35AM