Up-to-Date City Maps for Modeling, Planning, and Assistive Technologies

Digital maps are important for many different aspects of intelligent transportation. They are needed to model traffic patterns, to plan infrastructure upkeep, or for navigation for different traffic participants. These maps not only need to contain roads and all the transportation relevant objects like lane markings and traffic signs, but also their state of repair, compliance with regulations, and suitability for various users. The last point is particularly important for people who use wheelchairs, they not only need to know if there is a sidewalk but also if the sidewalk is wide enough and well maintained. Traditional methods to create such maps are manual surveying or surveying vehicles that make use of specialty sensors. These methods are cost prohibitive to keep maps up-to-date. The project team's proposed approach is to use inexpensive sensors on a fleet of vehicles that drive on the road for other purposes. The team will build on their experience with creating maps of road damage and stop signs. They want to expand their detection to all regulatory traffic signs and lane markings and measure retro-reflectivity of signs and lane markings. The project team also wants to detect damage, vandalism and vegetation overgrowth. They want to pay particular attention to information that is relevant to people with physical or cognitive limitations or disabilities, like state of repair of sidewalks or size and retro-reflectivity of traffic signs that is important for older driver.

Language

• English

Project

• Status: Active
• Funding: $127500
• Sponsor Organizations:

  Technologies for Safe and Efficient Transportation University Transportation Center

  Carnegie Mellon University
  Pittsburgh, PA  United States  15213

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Carnegie Mellon University

  Pittsburgh, PA  United States 
• Project Managers:

  Ehrlichman, Courtney

• Performing Organizations:

  Carnegie Mellon University

  Pittsburgh, PA  United States 
• Principal Investigators:

  Mertz, Christoph

• Start Date: 20170101
• Expected Completion Date: 20170730
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program
• Subprogram: DTRT-13G-UTC-26

Subject/Index Terms

• TRT Terms: Assistive technology; Data collection; Digital maps; Intelligent transportation systems; Lane lines; Persons with disabilities; Retroreflectivity; Sensors; Traffic signs; Vegetation
• Subject Areas: Data and Information Technology; Highways; Maintenance and Preservation; Operations and Traffic Management; Safety and Human Factors; Society;

Filing Info

• Accession Number: 01645845
• Record Type: Research project
• Source Agency: Technologies for Safe and Efficient Transportation University Transportation Center
• Files: UTC, RiP
• Created Date: Sep 6 2017 7:14PM