A driver assistance system and method are disclosed. The driver assistance system includes a first sensor installed at a vehicle and configured to have a field of view directed forward from the vehicle to acquire front image data, a second sensor selected from a group of radar and LIDAR sensors, installed at the vehicle, and configured to have a field of view directed forward from the vehicle to acquire front detection data, and a controller having a processor configured to process the front image data and the front detection data, wherein the controller is configured to detect a lane, in which the vehicle is traveling, or detect a front object located in front of the vehicle, in response to the processing of the image data and the front detection data, output a braking signal to a braking system of the vehicle when a collision between the vehicle and the front object is expected, and output a steering signal to a steering system of the vehicle when a collision between the vehicle and the front object is expected even with braking control.

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 sensor signal processing unit (100) arranged to detect a configuration of parking slots (1a,1b,1c,1d) based on radar detections received from a radar-based sensor system (120). The unit includes a histogram unit arranged to generate a representation of a spatial distribution of a set of radar detection coordinates, and a detection unit arranged to detect the configuration of parking slots. The detection unit is arranged to detect the configuration of parking slots based on a Fourier transform of the representation of spatial distribution.

A method for synchronizing devices in a vehicle may make use of the Controller Area Network (CAN) communication bus. A bus interface of each of two or more devices coupled to the bus may be configured to accept a same message broadcast via the communication bus, in which the message has a specific message identification (ID) header. A message may be received from the communication bus that has the specific message ID simultaneously by each of the two or more devices. Operation of the two or more devices may be synchronized by triggering a task on each of the two or more devices in response to receiving the message having the specific message ID.

A vehicle may include: a camera configured to obtain a surrounding image of the vehicle; and a controller configured to derive spatial recognition data by learning the surrounding image of the vehicle as an input value, derive object recognition data including wheel area data of surrounding vehicles by learning the surrounding image of the vehicle as an input value, determine a ground clearance between a bottom surface of a vehicle body of the surrounding vehicle and a ground by use of the spatial recognition data and the wheel area data, and control the vehicle to park the vehicle by reflecting the ground clearance.

A method for radar-based monitoring of a rearward area of a truck. The truck comprises a radar device and at least one semitrailer. The method comprises the steps of ascertaining various objects and their position using the radar device, determining an alignment of the trailer relative to the radar device, determining the objects that, based on their position, are concealed for the radar device as a result of the alignment of the semitrailer, and ascertaining, on the basis of the alignment of the semitrailer and an ascertained reflection of the radar waves on the semitrailer, the true position of the objects ascertained as concealed.

Disclosed is a control assistance device that includes a radar system that detects surrounding objects, and generates radar tracking information tracking a position of the surrounding object relative to a vehicle, and a camera system, that includes cameras, and generates image information, and camera tracking information tracking the position of the surrounding object. The control assistance device also includes processors that determine whether the radar tracking information is generated in real time when the surrounding object approaches within a preset distance from the vehicle based on generated tracking information that includes the radar tracking information or the camera tracking information, determine whether the camera tracking information is generated in real time, when the radar tracking information is determined as generated in real time, and control a braking system of the vehicle based on the generated tracking information, when the camera tracking information is determined as generated in real time.

Methods, systems, and devices for wireless communications are described. A user equipment (UE), such as a vehicle that is enabled with radar detection and ranging, may include multiple radars or radar components and may receive, at a first radar, a first radar waveform in a field of view (FOV) associated with the first radar. The UE may determine a trajectory of the target object which may indicate the target object entering a FOV of a second radar. The UE may receive, at the second radar, a second radar waveform in the FOV of the second radar and may associate the second radar waveform with the target object based on the trajectory of the target object and the second radar waveform being in the FOV of the second radar.

Systems and methods for generating simulated LiDAR data using RADAR and image data are provided. An algorithm is trained using deep-learning techniques such as loss functions to generate simulated LiDAR data using RADAR and image data. Once trained, the algorithm can be implemented in a system, such as a vehicle, equipped with RADAR and image sensors in order to generate simulated LiDAR data describing the system's environment. The simulated LiDAR data may be used by a vehicle control system to determine, generate, and implement modified driving operations.

Image recording device provided with a fixed part for at least partial inclusion in and/or on the body of a motor vehicle, and a movable part which comprises at least one optical element, the optical element comprising at least one optical sensor and/or a lens unit, and an adjustment device provided with a power source, for adjusting the movable part between a first position and a second position, wherein during use in the first position the movable part is wholly or partly included in the body, and in the second position the movable part extends at an angle with respect to the body, such that at least the optical element carried by the movable part extends at least partly outside the body, wherein the movable part pivots from the second position about a, preferably substantially vertical, axis to the first position and vice versa.