A vehicle includes: recognizing a forward vehicle in response to the processing of image data captured by an image sensor disposed at the vehicle so as to have a field of view of the outside of the vehicle; obtaining a distance from the forward vehicle in response to the processing of detecting data captured by a radar disposed at the vehicle so as to have a detecting area of the outside of the vehicle; obtaining a change amount of vertical movement of the forward vehicle in the image data in response to the distance from the forward vehicle that is equal to or less than a reference distance; obtaining a height of an obstacle on a road surface corresponding to the change amount; obtaining the height of the obstacle on the road surface in the image data in response to the distance from the forward vehicle that exceeds the reference distance; identifying a driving speed of the vehicle; identifying a reference height corresponding to the driving speed of the vehicle; and outputting deceleration guide information in response to the height of the obstacle on the road surface that is greater than or equal to the reference height.

This disclosure describes a radar system configured to estimate a yaw-rate and an over-the-ground (OTG) velocity of extended targets in real-time based on raw radar detections. This disclosure further describes techniques for determining instantaneous values of lateral velocity, longitudinal velocity, and yaw rate of points of a rigid body in a radar field-of-view (FOV) of the radar system.

The present invention provides a method of communicating vehicle positioning information, wherein signals are transmitted from at least one vehicle mounted antenna for indicating a position of the vehicle to another entity, the signals including information concerning at least one of an identity of the at least one antenna and information providing a displacement between the at least one antenna and a boundary of the vehicle.

A computer implemented method for determining the position of a vehicle, wherein the method comprises: determining at least one scan comprising a plurality of detection points, wherein each detection point is evaluated from a signal received at the at least one sensor and representing a location in the vehicle environment; determining, from a database, a predefined map, wherein the map comprises a plurality of elements in a map environment, each of the elements representing a respective one of a plurality of static landmarks in the vehicle environment, and the map environment representing the vehicle environment; matching the plurality of detection points and the plurality of elements of the map; determining the position of the vehicle based on the matching; wherein the predefined map further comprises a spatial assignment of a plurality of parts of the map environment to the plurality of elements, and wherein the spatial assignment is used for the matching.

Feedback for map information is based on an integrated navigation solution for a device within a moving platform using obtained motion sensor data from a sensor assembly of the device, obtained radar measurements for the platform and obtained map information for an environment encompassing the platform. An integrated navigation solution is generated based at least in part on the obtained motion sensor data using a nonlinear state estimation technique that uses a nonlinear measurement model for radar measurements. The map information is assessed based at least in part on the integrated navigation solution and radar measurements so that feedback for the map information can be provided.

According to one aspect, a system for robust localization may include a scan accumulator, a scan matcher, a transform maintainer, and a location fuser. The scan accumulator may receive a set of sensor data from a set of sensors mounted on a vehicle. The scan accumulator may generate a sensor scan point cloud output by transforming the set of sensor data from each sensor frame to a corresponding vehicle frame and calculate a fitness score, a transformation probability, and a mean elevation angle used to determine a scan confidence for the sensor data. The transform maintainer may receive GPS data, the scan confidence, and the matched sensor scan point cloud output and map tile point cloud data from the scan matcher, and determine whether the GPS data or the matched sensor scan point cloud output and map tile point cloud data is utilized for a map-to-odometer transformation output.

A computer implemented method for determining the position of a vehicle, wherein the method comprises: determining at least one scan comprising a plurality of detection points, wherein each detection point is evaluated from a signal received at the at least one sensor and representing a location in the vehicle environment; determining, from a database, a predefined map, wherein the map comprises a plurality of elements in a map environment, each of the elements representing a respective one of a plurality of static landmarks in the vehicle environment, and the map environment representing the vehicle environment; matching the plurality of detection points and the plurality of elements of the map; determining the position of the vehicle based on the matching; wherein the predefined map further comprises a spatial assignment of a plurality of parts of the map environment to the plurality of elements, and wherein the spatial assignment is used for the matching.

A system for virtual aperture array radar tracking includes a transmitter that transmits first and second probe signals; a receiver array including a first plurality of radar elements positioned along a first radar axis; and a signal processor that calculates a target range from first and second reflected probe signals, corresponds signal instances of the first reflected probe signal to physical receiver elements of the radar array, corresponds signal instances of the second reflected probe signal to virtual elements of the radar array, calculates a first target angle between a first reference vector and a first projected target vector from the first reflected probe signal, and calculates a position of the tracking target relative to the radar array from the target range and first target angle.

A driving control method is provided in which a processor configured to control driving of a vehicle acquires detection information around a vehicle on the basis of a detection condition that can be set for each point; extracts events which the vehicle encounters, on the basis of the detection information; creates a driving plan in which a driving action is defined for each of the events on the basis of the detection information acquired in the events; executes a driving control instruction for the vehicle in accordance with the driving plan; and determines the detection condition on the basis of the content of the driving action defined for each of the events.

A sensor system for a vehicle includes a central module and a plurality of sub modules mounted in a frame of the vehicle, the sub modules being independently removable. The sub modules include sensors configured to capture image data and distance data in a vicinity of the vehicle. The central module is connected to each of the plurality of sub modules through a first network including a switching hub. The sub modules are individually connected to an external processor through a second network. The central processor is configured to synchronize the sub modules based on absolute time information through the first network, and the sub modules are configured to output the captured image data and distance data appended with synchronized time information to the external processor by communicating through the second network.