A method for classification of ground conditions in the vicinity of a vehicle using a radar sensor, comprising: receiving reflected portions of a radar signal at a receiver unit of a radar system; calculating information derived from the received portions of the radar signal for discrete spatial regions by the radar system or a control unit connected thereto; assigning the information to data structure units associated with a geographical location and the assignment of the information taking into account movement of the vehicle; collecting pieces of information in the respective data structure units, the pieces of information being obtained from reflected portions of radar signals transmitted at different times; evaluating the information contained in the data structure using a classifier to obtain information regarding the ground condition; assigning ground condition types to the data structure units based on evaluation results obtained by the classifier.

Methods and systems are provided for generating an on-demand distributed aperture by mechanical articulation. In some aspects, a process can include steps for determining a location of an autonomous vehicle, determining whether a maneuver requires long range detections or medium range detections based on the location of the autonomous vehicle, positioning at least two articulated radars based on the determining of whether the maneuver requires long range detections or medium range detections, and enabling a mode of resolution based on the positioning of the at least two articulated radars and by utilizing a static radar. Systems and machine-readable media are also provided.

Examples disclosed herein relate to radar systems to coordinate detection of objects external to the vehicle and distractions within the vehicle. A method of environmental detection with a radar system includes detecting an object in an external environment of a vehicle with the radar system positioned on the vehicle. The method includes determining a distraction metric from measurements of user activity obtained within the vehicle with the radar system. The method includes adjusting one or more detection parameters of the radar system based at least on the detected object and the distraction metric. Other examples disclosed herein relate to a radar sensing unit for a vehicle that includes an internal distraction sensor, an external object detection sensor, a coordination sensor and a central controller for internal and external environmental detection.

An extraction unit (101) extracts as a stationary object-detection point, a detection point on a stationary object among a plurality of detection points around a vehicle (200), the plurality of detection points being detected by an outside-detection sensor (501) at a plurality of detection timings. A grouping unit (105) groups two or more stationary object-detection points deduced as detection points on a same stationary object, among a plurality of stationary object-detection points extracted by the extraction unit (101) at the plurality of detection timings.

A navigation system includes: a control circuit configured to: generate a video clip by parsing an interval of a sensor data stream for a region of travel; analyze the video clip submitted to a deep learning model, already trained, including identifying a traffic flow estimate; access a position coordinate for calculating a distance to intersection; generate a traffic flow state by fusing a corrected speed, the traffic flow estimate, and the distance to intersection; merge a vehicle maneuvering instruction into the traffic flow state for maneuvering through the region of travel; and a communication circuit, coupled to the control circuit, configured to: communicate the traffic flow state for displaying on a device.

A system comprises a computer having a processor and a memory, the memory storing instructions executable by the processor to access sensor data of a sensor of a vehicle while an adaptive cruise control feature of the vehicle is active, detect, based on the sensor data, an object located along a path of travel of the vehicle, determine that the object is a moveable object based on a radar return of a radar reflector of the object, and responsive to the determination that the object is the moveable object, adjust, by the adaptive cruise control feature, the speed of the vehicle.

The disclosure relates to a method of providing a current local environment status map for a motor vehicle, and to a motor vehicle and a system for carrying out the method. The method includes generating own driving situation data which describe a current, position-related vehicle parameter of the motor vehicle, and generating environment situation data which describe a current arrangement of a further motor vehicle located in a predefined environment of the motor vehicle. The method also includes generating, based on these data, a vehicle environment map which describes a current local traffic situation in the predefined environment. The further vehicle environment maps of the environment of the vehicle are received from at least one other the further motor vehicle and are combined with the generated vehicle environment map using a map data evaluation criterion in order to generate an improved current local environment status map for the motor vehicle.

An electronic device includes a plurality of sensors installed in predetermined orientations at different positions. Each of the plurality of sensors includes a transmission antenna that transmits a transmission wave, a reception antenna that receives a reflected wave that is the transmission wave having been reflected, and a control unit that detects an object that reflects the transmission wave, based on a transmission signal transmitted as the transmission wave and a reception signal received as the reflected wave. The electronic device further includes a determination unit that determines a shift in orientation of at least any of the plurality of sensors, based on detection results of an object obtained by the plurality of sensors.

A method for controlling a vehicle (100) includes reading-in measurement data about a surface (6) of a substrate (2) lying ahead of the vehicle (100) in its travel direction (F), where the surface contains a ground-level obstacle (4) and recognizing the ground-level obstacle (4) from the measurement data. The method also includes determining a movement vector (V4) of the recognized ground-level obstacle (4) in a vehicle-associated coordinate system on the basis of the measurement data read in and determining a movement vector (V1) of the vehicle (100) in a coordinate system superordinate relative to the vehicle-associated coordinate system. The method further includes checking whether the ground-level obstacle (4) is a dynamic ground-level obstacle (4) in the superordinate coordinate system and emitting a control signal for controlling an operational safety system (30) of the vehicle (100) as a function of the result of the check. Also disclosed is a control unit (200) for carrying out a method of that type and a vehicle (100) with a control unit (200) of that type.

A computer implemented method for object detection includes: determining a grid, the grid comprising a plurality of grid cells; determining, for a plurality of time steps, for each grid cell, a plurality of respective radar detection data, each radar detection data indicating a plurality of radar properties; determining, for each time step, a respective radar map indicating a pre-determined radar map property in each grid cell; converting the respective radar detection data of the plurality of grid cells for the plurality of time steps to a point representation of pre-determined first dimensions; converting the radar maps for the plurality of time steps to a map representation of pre-determined second dimensions, wherein the pre-determined first dimensions and the pre-determined second dimensions are at least partially identical; concatenating the point representation and the map representation to obtain concatenated data; and carrying out object detection based on the concatenated data.