Abstract: A method of determination of the alignment angles of two or more road vehicle (1) borne radar sensors (4) for a road vehicle radar auto-alignment controller (3) starting from initially available rough estimates of alignment angles. From at least two radar sensors (4) are obtained signals related to range, azimuth and range rate to detections. The detections are screened (5) to determine detections from stationary targets. From the determined detections from stationary targets is derived a linearized signal processing model involving alignment angles, longitudinal and lateral velocity and yaw-rate of the road vehicle (1). A filter algorithm is applied to estimate the alignment angles. Based on the estimated alignment angles are produced signals suitable for causing a road vehicle (1) radar auto-alignment controller (3) to perform radar offset compensation.

Abstract: Described herein is a method and arrangement (11) for sourcing of location information, generating and updating maps (16) representing the location. From at least two road vehicle (12) passages at the location is obtained (1, 2) vehicle registered data on the surrounding environment from environment sensors and positioning data from consumer-grade satellite positioning arrangements and from at least one of an inertial measurement unit and a wheel speed sensor. The positioning data is smoothed (3) to establish continuous trajectories for the respective vehicles (12). Individual surrounding environment maps are created using the data from each respective vehicle (12) passage at the location. From the individual surrounding environment maps are identified submaps (15) sharing area segments. Pairs of submaps (15) sharing area segments are cross-correlated (6).

Abstract: A method of determination of the alignment angles of two or more road vehicle (1) borne radar sensors (4) for a road vehicle radar auto-alignment controller (3) starting from initially available rough estimates of alignment angles. From at least two radar sensors (4) are obtained signals related to range, azimuth and range rate to detections. The detections are screened (5) to determine detections from stationary targets. From the determined detections from stationary targets is derived a linearized signal processing model involving alignment angles, longitudinal and lateral velocity and yaw-rate of the road vehicle (1). A filter algorithm is applied to estimate the alignment angles. Based on the estimated alignment angles are produced signals suitable for causing a road vehicle (1) radar auto-alignment controller (3) to perform radar offset compensation.

Abstract: Described herein is a method and arrangement (11) for sourcing of location information, generating and updating maps (16) representing the location. From at least two road vehicle (12) passages at the location is obtained (1, 2) vehicle registered data on the surrounding environment from environment sensors and positioning data from consumer-grade satellite positioning arrangements and from at least one of an inertial measurement unit and a wheel speed sensor. The positioning data is smoothed (3) to establish continuous trajectories for the respective vehicles (12). Individual surrounding environment maps are created using the data from each respective vehicle (12) passage at the location. From the individual surrounding environment maps are identified submaps (15) sharing area segments. Pairs of submaps (15) sharing area segments are cross-correlated (6).

Abstract: The present disclosure relates to estimated road geometries used in vehicles, and in particular to a method and a control unit in a vehicle for determining a confidence level of an estimated road geometry. A method for determining a confidence level of an estimated road geometry is disclosed, the road geometry being estimated at least partly based on a position of a road object. The method comprises obtaining a reference position of the road object relative to the vehicle, updating a reach of a confidence zone of the vehicle, wherein a part of the estimated road geometry comprised within the confidence zone is associated with one or more reference confidence levels, and determining the confidence level of the estimated road geometry based on whether the reference position is comprised in the confidence zone.

Abstract: A method performed by an object size mapping system is described for enabling improved positioning of a vehicle. The object size mapping system includes a first reference camera adapted to be arranged on-board a reference vehicle. The object size mapping system determines a current reference position of the reference vehicle. The system captures by the first reference camera, at the current reference position of the reference vehicle, a current reference image of a stationary physical reference object situated in the surroundings of the reference vehicle. The object size mapping system then determines a current reference size value of at least a portion of the stationary physical reference object, in the current reference image. The object size mapping system stores the current reference size value to be associated with the current reference position of the reference vehicle and a mapped digital reference object corresponding to the stationary physical reference object.

Abstract: A method performed by a positioning system of a vehicle is disclosed for determining a position of the vehicle along a road including one or several road markings arranged on a surface of the road. The positioning system detects road markings, matches detected road markings with mapped road markings of stored map data based on comparing characteristics of the detected road markings with mapped characteristics of the mapped road markings. The positioning system furthermore identifies a mapped identified road marking determined to correspond with a detected identified road marking, and determines a positioning estimate of the vehicle along the road based on a mapped road marking position associated with the mapped identified road marking. A positioning system, a vehicle including such a positioning system, and a mapping unit and a mapping method performed therein for creating map data to be utilized by the above mentioned positioning system are also disclosed.

Abstract: A method performed by an object size mapping system is described for enabling improved positioning of a vehicle. The object size mapping system includes a first reference camera adapted to be arranged on-board a reference vehicle. The object size mapping system determines a current reference position of the reference vehicle. The system captures by the first reference camera, at the current reference position of the reference vehicle, a current reference image of a stationary physical reference object situated in the surroundings of the reference vehicle. The object size mapping system then determines a current reference size value of at least a portion of the stationary physical reference object, in the current reference image. The object size mapping system stores the current reference size value to be associated with the current reference position of the reference vehicle and a mapped digital reference object corresponding to the stationary physical reference object.

Abstract: The present disclosure relates to estimated road geometries used in vehicles, and in particular to a method and a control unit in a vehicle for determining a confidence level of an estimated road geometry. A method for determining a confidence level of an estimated road geometry is disclosed, the road geometry being estimated at least partly based on a position of a road object. The method comprises obtaining a reference position of the road object relative to the vehicle, updating a reach of a confidence zone of the vehicle, wherein a part of the estimated road geometry comprised within the confidence zone is associated with one or more reference confidence levels, and determining the confidence level of the estimated road geometry based on whether the reference position is comprised in the confidence zone.

Abstract: A method performed by a positioning system of a vehicle is disclosed for determining a position of the vehicle along a road including one or several road markings arranged on a surface of the road. The positioning system detects road markings, matches detected road markings with mapped road markings of stored map data based on comparing characteristics of the detected road markings with mapped characteristics of the mapped road markings. The positioning system furthermore identifies a mapped identified road marking determined to correspond with a detected identified road marking, and determines a positioning estimate of the vehicle along the road based on a mapped road marking position associated with the mapped identified road marking. A positioning system, a vehicle including such a positioning system, and a mapping unit and a mapping method performed therein for creating map data to be utilized by the above mentioned positioning system are also disclosed.