Abstract: Parking lot (18, 20) locations and geometries are discerned from probe data (22) and integrated with a digital map (12) for use in navigation and other map-related activities. The steps of this invention include: identifying the positions in the probe data (22) where cars are probably parked, detecting the positions of parking lots (18, 20), determining the extension and shape of the detected parking lots (18, 20), and adjusting the parking lots (18, 20) into the road network (14). Optionally, the parking lot (18, 20) can be classified and additional attributes computed. Finally, a topological connection of the parking lot (18, 20) is made to the road network (14) during which entrances (34) and exits (36) are identified.

Abstract: A method for improving and extending an existing digital road network and generating new networks from statistically relevant amounts of probe data recorded by GPS-enabled navigation devices. New probe data is matched to the existing digital map, then the data merged into the existing network using a time-dependent weight and/or accuracy-dependent weight. A recalculation date is established, and the weight value of a line segment and/or trace is adjusted as a function of the time span relative to the recalculation. The function may include setting a maximal time period divided into bins each having a respective weight reduction factor, or applying decay function. Through this technique, digital maps can be updated and extended without undue influence exerted by old trace data.

Abstract: A method for improving and extending an existing road network and generating new networks from statistically relevant amounts of probe data recorded by GPS-enabled navigation devices. New probe data is matched to the existing digital vector map, then the data merged into the existing network using a weighted mean technique. When new roads are detected, appropriate junction points are made with the existing network elements. The updated network data is simplified to improve computing speed and reduce data storage requirements.

Abstract: A system and method for providing a digital map database wherein multiple instances of geocoded objects pertaining to points of interest (POI) and/or three-dimensional (3D) objects contained within one or more building blocks are compared to find undesirable duplicate geocoded objects. Cross-referencing information is stored and preference information about which geocoded object or object property/attribute should be used is assessed to determine priority for selection or presentation on the display screen of a navigation device or other suitable computing device. Cross-references can be pre-calculated at compile time or calculated on-the-fly by the navigation application at run time and may be persistently stored in dedicated data structures. When duplicate geocoded objects are found, only the most accurate information or a super set of (attribute) information is used by applications or presented to a user thereby preventing confusion.

Abstract: A system and method for providing a digital map database wherein multiple instances of geocoded objects pertaining to points of interest (POI) and/or three-dimensional (3D) objects contained within one or more building blocks are compared to find undesirable duplicate geocoded objects. Cross-referencing information is stored and preference information about which geocoded object or object property/attribute should be used is assessed to determine priority for selection or presentation on the display screen (12) of a navigation device (10) or other suitable computing device. Cross-references can be pre-calculated at compile time or calculated on-the-fly by the navigation application at run time and may be persistently stored in dedicated data structures. When duplicate geocoded objects are found, only the most accurate information or a super set of (attribute) information is used by applications or presented to a user thereby preventing confusion.

Abstract: A method comprises extracting a local identifier (130, 730a, 730b) from an image (100, 500, 700), the image (100, 500, 700) also having positional data (120) relating to the location at which the image (100, 500, 700) was captured; and associating the extracted local identifier (130, 730a, 730b) with the corresponding positional data (120) to allow for associating the extracted local identifier with a digital map (300, 600, 800).

Abstract: A method comprises extracting a local identifier (130, 730a, 730b) from an image (100, 500, 700), the image (100, 500, 700) also having positional data (120) relating to the location at which the image (100, 500, 700) was captured; and associating the extracted local identifier (130, 730a, 730b) with the corresponding positional data (120) to allow for associating the extracted local identifier with a digital map (300, 600, 800).