关键词: |
Assistive technology, Data collection, Digital maps, Intelligent transportation systems, Lane lines, Persons with disabilities, Retroreflectivity, Sensors, Traffic signs, Vegetation, Data and information technology, Highways, Maintenance and preservation, Operations and traffic management, Safety and human factors, Society, Carnegie Mellon University |
摘要: |
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. |