Development of a Sensor Platform for Roadway Mapping: Part B – Mapping the Road Fog Lines

The authors' objective is the development and evaluation of a low-cost, vehicle-mounted sensor suite capable of generating map data with lane and road boundary information accurate to the 10 cm (4 in.) level. Such a map could be used for a number of different applications including Global National Satellite System/Global Positioning System (GNSS/GPS) based lane departure avoidance systems, smart phone based dynamic curve speed warning systems, base map improvements, among others. The sensor suite used consists of a high accuracy GNSS receiver, a side-facing video camera, and a computer. Including cabling and mounting hardware, the equipment costs were roughly $30,000. Here, the side-facing camera is used to record video of the ground adjacent to the passenger side of the vehicle. The video is processed using a computer vision algorithm that locates the fog line within the video frame. Using vehicle position data (provided by GNSS) and previously collected video calibration data, the fog line is located in real-world coordinates. The system was tested on two roads (primarily two-lane, undivided highway) for which high accuracy (<10 cm) maps were available. This offset between the reference data and the computed fog line position was generally better than 7.5 cm (3 in.). The results of this work demonstrate that it is feasible to use a camera to detect the position of a road’s fog lines, or more broadly any other lane markings, which when integrated into a larger mobile data collection system, can provide accurate lane and road boundary information about road geometry.

• Record URL:
  • https://hdl.handle.net/11299/172721
• Record URL:
  • https://hdl.handle.net/20.500.14153/mndot.3001
• Record URL:
  • http://www.roadwaysafety.umn.edu/publications/researchreports/pdfdownload.pl?id=2578
• 
• Summary URL:
  • http://www.dot.state.mn.us/research/TS/2015/201511TS.pdf
• Summary URL:
  • http://www.roadwaysafety.umn.edu/publications/researchreports/reportdetail.html?id=2412
• Record URL:
  • https://rosap.ntl.bts.gov/view/dot/32166
• Corporate Authors:

  University of Minnesota, Minneapolis

  Department of Mechanical Engineering
  111 Church Street, SE
  Minneapolis, MN  United States  55455

  Minnesota Department of Transportation

  Research Services and Library
  395 John Ireland Boulevard
  St Paul, MN  United States  55155
• Authors:
  • Davis, Brian
  • Donath, Max
• Publication Date: 2015-4

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; Maps; Photos; References; Tables;
• Pagination: 44p

Subject/Index Terms

• TRT Terms: Algorithms; Computer vision; Driver support systems; Mapping; Ran off road crashes; Video cameras
• Identifier Terms: Global Navigation Satellite System
• Uncontrolled Terms: Lane departure warning systems
• Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment; I91: Vehicle Design and Safety;

Filing Info

• Accession Number: 01560682
• Record Type: Publication
• Report/Paper Numbers: MN/RC 2015-11, CTS Project #2014019
• Contract Numbers: 99008 (wo) 115
• Files: NTL, TRIS, ATRI, STATEDOT
• Created Date: Apr 21 2015 9:01PM