Digital mapping

Abstract: Map-matching algorithms integrate positioning data with spatial road network data (roadway centrelines) to identify the correct link on which a vehicle is travelling and to determine the location of a vehicle on a link. A map-matching algorithm could be used as a key component to improve the performance of systems that support the navigation function of intelligent transport systems (ITS). The required horizontal positioning accuracy of such ITS applications is in the range of 1 m to 40 m (95%) with relatively stringent requirements placed on integrity (quality), continuity and system availability. A number of map-matching algorithms have been developed by researchers around the world using different techniques such as topological analysis of spatial road network data, probabilistic theory, Kalman filter, fuzzy logic, and belief theory. The performances of these algorithms have improved over the years due to the application of advanced techniques in the map matching processes and improvements in the quality of both positioning and spatial road network data. However, these algorithms are not always capable of supporting ITS applications with high required navigation performance, especially in difficult and complex environments such as dense urban areas. This suggests that research should be directed at identifying any constraints and limitations of existing map matching algorithms as a prerequisite for the formulation of algorithm improvements. The objectives of this paper are thus to uncover the constraints and limitations by an in-depth literature review and to recommend ideas to address them. This paper also highlights the potential impacts of the forthcoming European Galileo system and the European Geostationary Overlay Service (EGNOS) on the performance of map matching algorithms. Although not addressed in detail, the paper also presents some ideas for monitoring the integrity of map-matching algorithms. The map-matching algorithms considered in this paper are generic and do not assume knowledge of ‘future’ information (i.e. based on either cost or time). Clearly, such data would result in relatively simple map-matching algorithms.

Abstract: A method, system and apparatus for displaying points-of-interest (“POIs”) on a digital map are disclosed. One such method includes: presenting a digital map on a graphical display of an electronic device, wherein the digital map comprises map tiles and corresponds to a geographic region; receiving free-hand user input selecting a portion of the digital map; delimiting the portion of the digital map selected by the user; determining one or more of the POIs whose geographic coordinates are within the portion of the digital map selected by the user; and displaying a graphic for each of the determined POIs, wherein the displayed graphic is displayed on the digital map at the geographic coordinates of each of the determined one or more POIs.

Abstract: The HydroATLAS database provides a standardized compendium of descriptive hydro-environmental information for all watersheds and rivers of the world at high spatial resolution. Version 1.0 of HydroATLAS offers data for 56 variables, partitioned into 281 individual attributes and organized in six categories: hydrology; physiography; climate; land cover & use; soils & geology; and anthropogenic influences. HydroATLAS derives the hydro-environmental characteristics by aggregating and reformatting original data from well-established global digital maps, and by accumulating them along the drainage network from headwaters to ocean outlets. The attributes are linked to hierarchically nested sub-basins at multiple scales, as well as to individual river reaches, both extracted from the global HydroSHEDS database at 15 arc-second (~500 m) resolution. The sub-basin and river reach information is offered in two companion datasets: BasinATLAS and RiverATLAS. The standardized format of HydroATLAS ensures easy applicability while the inherent topological information supports basic network functionality such as identifying up- and downstream connections. HydroATLAS is fully compatible with other products of the overarching HydroSHEDS project enabling versatile hydro-ecological assessments for a broad user community.

Abstract: Accident avoidance system for a host vehicle includes a global positioning system residing on the host vehicle for determining the host vehicle's location as the host vehicle travels based on signals received from one or more satellites, a map database having digital maps corresponding to an area including the location of the host vehicle as determined by the global positioning system, a vehicle-to-vehicle communication system residing on the host vehicle operative for receiving signals including location information acquired by global positioning systems residing on other vehicles directly from the other vehicles indicating the locations of the other vehicles, and a navigation system including a display residing on the host vehicle for displaying images to an occupant of the host vehicle showing the digital maps and indications of the locations of the host vehicle and the other vehicles on the digital maps. The navigation system also updates the images shown on the navigation system display to reflect changes in the locations of the host vehicle and the other vehicles.