Abstract: A system for providing traffic information to a driver of an ego vehicle includes at least one sensor that provides image data of detected objects, including other vehicles, in a surrounding area of the ego vehicle; a position detection device that detects a position of the ego vehicle; a display unit that renders visual information relating to an environmental model of the surrounding area of the ego vehicle, the position, and corresponding digital map data; and an image analysis unit configured to determine a vehicle characteristic of at least one other vehicle in the surrounding area of the ego vehicle from a vehicle image of the at least one other vehicle generated based on the image data from the at least one sensor and to display information on the display unit based on the determined vehicle characteristic.

Abstract: A method for localizing a vehicle comprises transmitting first position data related to a first position of the vehicle at a first point in time from the vehicle to a server. The server computes second position data related to the first position of the vehicle at the first point in time based on the received first position data. The server transmits the second position data from the server to the vehicle. The vehicle computes third position data related to a second position of the vehicle at a second point in time based on the received second position data. The second point in time is later than the first point in time.

Abstract: A computing device may identify a plurality of equally sized data blocks of a first navigation file and may identify a plurality of equally sized data blocks of a second navigation file. The computing device may perform binary difference operations between the data blocks of the first navigation file to corresponding data blocks of the second navigation file The result of the binary difference operations is stored in a plurality of navigation patch files. At least two of the plurality of navigation patch files are merged into a merged navigation patch file.

Abstract: A method for providing vehicle information includes: receiving first vehicle data encoded according to a first protocol and corresponding to an environment external to a vehicle; receiving high definition mapping data corresponding to objects in the environment external to the vehicle; generating position information for objects indicated in the high definition mapping data by correlating locations of objects indicated by the high definition mapping data with objects in the environment external to the vehicle detected by at least one sensor; generating second vehicle data by correlating the high definition mapping data, the position information, and the first vehicle data; and encoding the second vehicle data according to a second protocol.

Abstract: A method for a vehicle includes determining a region of interest based on environment sensor data corresponding an environment of the vehicle and a machine-learned predictor configured to identify, within the environment sensor data, a region as the region of interest that at least statistically coincides with a line of sight of an occupant of the vehicle. The method also includes classifying a detected object within the determined region of interest using an object detection algorithm. The method also includes operating the vehicle in based on at least one of the detected object and the determined region of interest.

Abstract: A navigation data source is provided that includes an object data set including object data indicating a spatial vacancy and/or occupancy of sub-regions of a spatial region by one or more structural objects in the spatial region. The object data references the sub-regions based on a linear order of the sub-regions in the spatial region. The object data may include interval information about an at least partially occupied interval, such as a lower interval border and/or an upper interval border. The at least partially occupied interval indicates a group of, according to the linear order, one or more successional sub-regions, at least a part of which are spatially occupied. The object data includes an occupancy sequence indicating a spatial vacancy and/or occupancy of the successional sub-regions of the at least partially occupied interval.

Abstract: A method for vehicle lane assignment includes identifying lane boundaries for one or more lanes of a road being traversed by the vehicle. The method also includes determining a center-line on a per lane basis for the one or more lanes. For a lane, the method uses the respective lane boundaries to determine the respective center-line of the lane. The method also includes determining a lane width on a per lane basis for the one or more lanes. For a lane, the method uses the respective lane boundaries to determine the respective lane width of the lane. The method also includes calculating a first probability that the vehicle is within a first lane of the one or more lanes using the center-line and the lane width corresponding to the first lane. The method also includes determining whether the first probability is greater than a threshold. The method also includes, in response to a determination that the first probability is greater than the threshold, assigning the vehicle to the first lane.

Abstract: A method and apparatus are provided for creating a navigation data source for use with a navigation system configured for route determination based on associated costs. The navigation data source comprises a cost data set associated with a navigation data set that represents a map of a geographic region and defines at least a plurality of gateways. Each of the gateways of the plurality of gateways may be associated with a position located within the geographic region and associated with a gateway of a further navigation data set representing a map of another geographic region. The cost data set comprises cost data that defines, for at least some of the possible gateway pairs of the plurality of gateways, at least a cost value with each cost value indicating a cost for a route between gateways of a respective gateway pair.

Abstract: A navigation data source is presented, which comprises: a first navigation data set (111) of a first type, wherein said first navigation data set (111) represents a map (M111) of a first geographic region (R111), wherein said first navigation data set (111) further defines a first gateway (G1), wherein said first gateway (G1) is associated with a position within said first geographic region (R111) and spaced from a border of said first geographic region (R1), and wherein said first gateway (G1) is associable with a gateway (G1) defined by a second navigation data set of a second type (121).

Abstract: A method for determining a driving route of a vehicle includes accessing a map database describing a road network of intersecting roads, the map database having a structure including of a plurality of road section data of at least a single road. The method also includes assigning attributes corresponding to an automated driving mode of the vehicle to the road section data associated with the map database. The method also includes determining an automated driving route for the vehicle from a predetermined position to a predetermined destination based on the attributes relating to the automated driving mode of the vehicle.

Abstract: A method for a vehicle includes determining a region of interest based on environment sensor data corresponding an environment of the vehicle and a machine-learned predictor configured to identify, within the environment sensor data, a region as the region of interest that at least statistically coincides with a line of sight of an occupant of the vehicle. The method also includes classifying a detected object within the determined region of interest using an object detection algorithm. The method also includes operating the vehicle in based on at least one of the detected object and the determined region of interest.

Abstract: A method includes identifying, in or after a second process of compiling data that yields a second navigation database, a navigation data item having a changed position in a list of the second navigation database. The changed position is different to a previous position of the navigation data item in a list of a first navigation database which is yield from a first process of compiling data performed before the second process of compiling data. The method also includes generating first update data for updating the first navigation database to an intermediate navigation database in a first updating step. The first update data represents generic update instructions and/or information for changing a data reference pointing to the previous position of the identified navigation data item to a data reference pointing to the changed position of the identified navigation data item. Corresponding apparatuses and computer readable storage mediums are also provided.

Abstract: A method for controlling a trajectory of an ego vehicle (EV) comprises a step of obtaining map data describing connectivity of lanes at an intersection, a step of obtaining first turn probabilities for each connection of lanes at the, and a step of planning a trajectory of the ego vehicle (EV) at the intersection in accordance with the first turn probabilities.

Abstract: A method for localizing a vehicle comprises transmitting first position data related to a first position of the vehicle at a first point in time from the vehicle to a server. The server computes second position data related to the first position of the vehicle at the first point in time based on the received first position data. The server transmits the second position data from the server to the vehicle. The vehicle computes third position data related to a second position of the vehicle at a second point in time based on the received second position data. The second point in time is later than the first point in time.

Abstract: A system for correlating sensor data in a vehicle includes a first sensor disposed on the vehicle to detect a plurality of first objects. A first object identification controller analyzes the first data stream, identifies the first objects, and determines first characteristics associated therewith. A second sensor disposed on the vehicle detects a plurality of second objects. A second object identification controller analyzes the second data stream, identifies the second objects, and determines second characteristics associated therewith. A model generator includes a plausibility voter to generate an environmental model of the objects existing in space around the vehicle. The model generator may use ASIL decomposition to provide a higher ASIL level than that of any of the sensors or object identification controllers alone. Matchings between uncertain objects are accommodated using matching distance probability functions and a distance-probability voter. A method of operation is also provided.

Abstract: A method for position lane leveling includes: determining vehicle position information for a vehicle; determining lane position information for the vehicle based on output of a convolutional neural network; determining at least one of a road, a link, and a lane of the vehicle based on the vehicle position information and the lane position information; and controlling the vehicle based on the determined at least one of the road, the link, and the lane of the vehicle.

Abstract: A method for determining a current state vector describing location and heading of an ego-vehicle with respect to a lane boundary of a road comprises a step of obtaining road sensor data from at least one road sensor of the ego-vehicle detecting the lane boundaries of the road. In another step, a measured state vector of the ego-vehicle is calculated from the road sensor data. Furthermore, motion state data related to current heading and velocity of the ego-vehicle is obtained and a predicted state vector of the ego-vehicle is calculated based on the motion state data of the ego-vehicle and a previous state vector of the ego-vehicle. Finally a current state vector is determined by calculating a weighted average of the measured state vector and the predicted state vector of the ego-vehicle. The weights are determined based on characteristics of an upcoming section of the road.

Abstract: A method for producing an update package for a navigational database comprises: —providing a first update region of the navigational database, and —providing a first gateway table of the first update region such that the first gateway table associates each gateway of the first update region with said first update region and with at least one other update region.

Abstract: A computing device may identify a series of bits representative of a first binary large object (BLOB) for navigation data including road segments and road attributes. The computing device duplicates each bit of the series of bits a predetermined number of times to form a first bit string. The first bit string is larger than the series of bits by a factor of the predetermined number. The computing device performs a binary difference of the first bit string to a second bit string representative of a second BLOB. A result of the binary difference is stored in a navigation patch file.

Abstract: A system for providing traffic information to a driver of an ego vehicle includes at least one sensor that provides image data of detected objects, including other vehicles, in a surrounding area of the ego vehicle; a position detection device that detects a position of the ego vehicle; a display unit that renders visual information relating to an environmental model of the surrounding area of the ego vehicle, the position, and corresponding digital map data; and an image analysis unit configured to determine a vehicle characteristic of at least one other vehicle in the surrounding area of the ego vehicle from a vehicle image of the at least one other vehicle generated based on the image data from the at least one sensor and to display information on the display unit based on the determined vehicle characteristic.