Intelligent Positioning in Cities using GNSS and Enhanced 3D Mapping

Poor positioning performance in dense urban areas is a major obstacle to the practical realisation of new technologies such as navigation for the visually impaired, tracking people with chronic medical conditions, augmented reality, advanced lane control systems for vehicles and advanced railway signalling systems.
The Global Positioning System (GPS) provides metres-level positioning in open environments. However in dense urban areas, buildings block, attenuate, reflect and diffract radio signals, limiting the real-time positioning accuracy to 10-50m when enough signals can be received to calculate a position. Other radio positioning technologies are typically no more accurate, while position obtained from dead reckoning degrades with time. Optical techniques developed by the robotics community are more suited to some applications than others and are still undergoing research to make them more reliable and efficient.
Using the new global navigation satellite systems (GNSS) constellations (i.e., GLONASS and, in future, Galileo and Compass) in addition to GPS improves the availability of satellite-based positioning in urban areas. However, to improve the accuracy, a new approach to positioning is needed and the increasing availability of 3D mapping provides an opportunity to achieve this.
The aim of this project is thus to improve the accuracy of real-time mobile positioning in urban areas to within a few metres by combining multi-constellation GNSS with 3D mapping, a concept known as intelligent urban positioning. By exploiting knowledge of the surroundings provided by 3D city models and rebuilding the positioning algorithms from the bottom up to make use of all available information, a step change in positioning performance can be achieved, unlocking the potential for a host of new positioning applications.
This research will build on UCL's track record of innovation in urban positioning, including the development of a brand new GNSS positioning method known as shadow matching. This project will investigate new ways of using 3D mapping to aid ranging-based GNSS positioning and then combine this with shadow matching to obtain the best overall position solution. Testing will be conducted under a wide range of scenarios to assess how the performance varies as a function of the urban environment, the class of GNSS user equipment used and the characteristics of the 3D mapping. Finally, context detection algorithms will be developed to determine when the positioning system is in an environment suitable for the algorithms developed under this project and when it is in an environment where conventional GNSS algorithms or an indoor positioning technique should be deployed instead.
By improving the accuracy and reliability of urban positioning, a successful outcome of this project would unlock the potential for many new applications that can both contribute to the economy and provide solutions to societal problems, while improving the reliability of many existing technologies. Positioning technology that can determine the correct side of the street and identify adjacent buildings is a key component of automated guidance for visually impaired pedestrians. More accurate emergency caller location and tracking of people with chronic medical conditions enables response teams to arrive more quickly. Augmented reality will benefit from a more efficient overlaying of information on the surrounding environment. Researchers mapping patterns of air pollution or wheelchair accessibility in cities will be able to quickly and cheaply geolocate information to within a few metres. More reliable identification of traffic lanes and railway tracks will support the development of advanced intelligent transport systems. Route guidance for visitors to cities, location of friends and business associates in complex or crowded urban environments, and location-based advertising will also benefit.

According to the European GNSS Agency (GSA) GNSS Market Report - Issue 2, dated May 2012, the worldwide global navigation satellite systems (GNSS) market size is expected to grow from £54bn in 2012 to £137bn in 2020. This will be dominated by the road and location-based services (i.e. mobile device) sectors, both of which are affected by the problem of poor real-time positioning in dense urban areas. The GNSS industry has an extensive presence in the UK, including CSR, Forsberg, Intel, QinetiQ, Spirent, ST Microelectronics, UBlox, Veripos and others. There are also many companies that use GNSS in their products. By improving the accuracy and reliability of urban positioning, a successful outcome of this project would unlock the potential for many new applications that can both contribute to the economy and provide solutions to societal problems, while improving the reliability of many existing technologies. ST Micro-electronics and Ordnance Survey will directly benefit as project partners.
Automated navigation and guidance for blind and visually impaired pedestrians will significantly improve their independence, boosting quality of life and enabling them to contribute more to the economy. Positioning technology to enable them to easily determine the correct side of the street and identify adjacent buildings, noting that many shops and cafés are only a few metres wide, is an important part of this. This is reflected in the participation of the Royal National Institute for Blind People (RNIB) as a project partner.
Emergency caller location and tracking of people with chronic medical conditions enables response teams to reach patients and other emergencies more quickly. If people can be located reliably to the correct building, response times will be shortened and lives potentially saved.
Many location-based services will benefit from better urban positioning, generating economic benefits. More reliable location and route guidance services for visitors to cities will improve the user experience, increasing their take up and making them more attractive to advertisers. It will also enable reliable location of friends and business associates in complex or crowded urban environments. Location-based advertising will benefit from reliable knowledge of which shop or business a potential customer is visiting. This will enable advertising to be better targeted, minimising intrusion from irrelevant adverts and thus making consumers more amenable to receiving advertising on mobile devices.
Reliable identification of traffic lanes is an important requirement for advanced intelligent transport systems that can direct individual vehicles to maximise traffic flow, prevent gridlock and prioritise emergency vehicles and buses, making best use of the available space in crowded cities. Similarly, advanced rail signalling systems require a system for identifying which track a train is on. By combining the new techniques developed under this project with dead reckoning and/or optical techniques, reliable real-time identification of traffic lanes and railway tracks should become a realistic prospect.
The potential for augmented reality to enhance the lives of both professionals and consumers is huge. However, the information must be correctly overlaid on the surrounding environment. A more accurate position initialisation will make the overlay process less reliant on image-matching, which can be confused by repeating features, improving both the robustness and the processing efficiency.
Other applications with economic benefit include high-value asset tracking, road-user charging, pay-as-you-drive insurance and identification of "white space" radio spectrum for short-range communication. Applications with social benefit include enforcement of exclusion zones and curfews and spatial data gathering in cities to produce maps of pollution or accessibility for the disabled.