Tomtom Global Content B.v.

Tom Tom International B.v.

Tomtom Polska Sp. Z O.o

Rafal Jan Gliszczynski

Krzysztof Miksa

Blazej Kubiak

Krzysztof Kudrynski

Marcin Michal Kmiecik

Lukasz Piotr Taborowski

Arkadiusz Wysocki

Hubert Nowak

Krysztof Miksa

Methods and systems for improved positioning accuracy relative to a digital map are disclosed, and which are preferably used for highly and fully automated driving applications, and which may use localisation reference data associated with a digital map. The invention further extends to methods and systems for the generation of localisation reference data associated with a digital map.

Methods and systems for generating and using localization reference data

ABSTRACT METHODS AND SYSTEMS FOR GENERATING AND USING LOCALISATION REFERENCE DATAMethods and systems for improved positioning accuracy relative to a digital map are disclosed, and which are preferably used for highly and fully automated driving applications, and which may use localisation reference data associated with a digital map. The invention further extends to methods and systems for the generation of localisation reference data associated with a digital map.

Methods and systems for classifying data points of a point cloud indicative of the environment around a vehicle by using features of a digital map relating to a deemed current position of the vehicle. Such methods and systems can be used to detect road actors, such as other vehicles, around a vehicle capable of sensing its environment as a point cloud; preferably used by highly and fully automated driving applications.

Methods and systems for generating and using localisation reference data

Methods and systems for improved positioning accuracy relative to a digital map are disclosed, and which are preferably used for highly and fully automated driving applications, and which may use localisation reference data associated with a digital map. A vehicle localization is obtained by comparing real time depth map acquired by a sensor associated to the vehicle to a depth map associated to a digital map. The depth maps are indicative of an environment around the vehicle. Longitudinal and lateral offsets of the vehicle with respect to the digital map are determined. The invention further extends to methods and systems for the generation of localisation reference data associated with a digital map.

A method of determining a longitudinal position of a vehicle () relative to a digital map is disclosed in which real time scan data () is determined by scanning a lateral environment around the vehicle using at least one range-finder sensor, said real time scan data comprising one or more depth maps, each depth map representing the measured lateral distance to surfaces in the lateral environment for a plurality of longitudinal positions and elevations. Localization reference data associated with the digital map for a deemed current longitudinal position of the vehicle () in relation to the digital map is retrieved, and compared to the real time scan data () by calculating a cross-correlation to determine a longitudinal offset. The deemed current longitudinal position is adjusted based on said longitudinal offset to determine the longitudinal position of the vehicle () relative to the digital map.

Method and system for determining a position relative to a digital map

A method is disclosed involving receiving GPS data from a personal portable training device. A smoothing operation is performed on the GPS data to generate a more accurate representation of the route travelled for display to a user (). In the smoothing operation, a cubic spine algorithm is used to obtain an initial estimate of the route representation (). The estimate is then subjected to a refinement using at least received user motion data recorded by the personal training device (). In addition one or more of: data indicative of the GPS accuracy; historical route data; and digital map data, such as building footprints and bodies of water, may be used in refining the estimate.

Route smoothing

A method of and arrangement for mapping first range sensor data from a first range sensor to image data from a camera are disclosed. In at least one embodiment, the method includes: receiving time and position data from a position determination device on board a mobile system, as well as the first range sensor data from the first range sensor on board the mobile system and the image data from the camera on board the mobile system; identifying a first points cloud within the first range sensor data, relating to at least one object; producing a mask relating to the object based on the first points cloud; mapping the mask on object image data relating to the same object as present in the image data from the at least one camera; and performing a predetermined image processing technique on at least a portion of the object image data.

Method of and arrangement for mapping range sensor data on image sensor data

A computerised method of creating map data from a plurality of trips where each trip comprises position data derived from the positions of at least one navigation deviceover a period of time, the method comprising using a processing circuitry to perform the following steps: i. processing the position data; ii. determining from the processing the believed accuracy of the position data constituting a trip; iii. reducing the weight applied to and/or removing position data in which the belief is below a predetermined threshold to generate filtered position data; iv. deriving information about the roadbased upon the filtered position data; and v. generating further map data.

Method of creating map data

A computer arrangement is disclosed, including a processor that can communicate with a memory. The memory stores a computer program that can be run by the processor, and stores a set of laser scan samples including a sub-set of laser scan samples relating to a fa&#xe7;ade of a building and stores location data as to each laser scan sample. The memory also stores a picture of the same fa&#xe7;ade including location data as to pixels of the picture. The picture includes data as to a wall of the fa&#xe7;ade and data as to texture elements in the wall. In at least one embodiment, the processor automatically identifies the wall and the texture elements in the picture while using the laser scan samples.

System for and method of processing laser scan samples and digital photographic images relating to building facades

A method of detecting objects from terrestrial based mobile mapping data is disclosed, wherein the terrestrial based mobile mapping data has been captured by way of a terrestrial based mobile mapping vehicle driving on a road having a driving direction, the mobile mapping data including laser scanner data, source images obtained by at least one camera and position and orientation data of the vehicle, wherein the laser scanner data includes laser points, each laser point having associated position and orientation data, and each source image comprises associated position and orientation data. In at least one embodiment, the method includes: retrieving a position and orientation of the vehicle; filtering the laser scanner data in dependence of the position and orientation of the vehicle to obtain laser points corresponding to regions of interest; retrieving a source image associated with the position and orientation of the vehicle; mapping the laser points corresponding to regions of interest to image coordinates of the source image to generate a recognition mask; combining the recognition mask and the source image to obtain candidate 3D images representative of possible objects within the regions of interest; and, detecting a group of objects from the candidate 3D images. By combining image recognition and laser scanner recognition the detection rate can be increased to a very high percentage, thereby substantially reducing human effort. Furthermore, the generating of regions of interest in the laser data, enables a significant reduction of the processing power and/or the processing time needed to detect the objects in the images.

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Lodz, Poland

Rafal Jan Gliszczynski