A hybrid electric vehicle and a method of controlling the same are provided to avoid a collision thereof attributable to erroneous operation of an accelerator pedal. The method includes determining whether an accelerator pedal is erroneously operated in the situation in which an obstacle is detected to be present in the traveling path. In response to determining that the accelerator pedal is erroneously operated, the method includes switching the driving mode to a mode in which an engine is disconnected from a driving shaft and a motor generates driving force. The number of revolutions per minute (RPM) of the engine is then adjusted based on the extent to which the accelerator pedal is operated and the torque of the motor is adjusted based on a first vehicle speed and the distance to the obstacle.

Systems and methods for operating radar systems. The methods comprise, by a processor: receiving point cloud information generated by at least one radar device and a spatial description for an object; generating a plurality of point cloud segments by grouping data points of the point cloud information based on the spatial description; arranging the point cloud segments in a temporal order to define a radar tentative track; performing dealiasing operations using the radar tentative track to generate tracker initialization information; and using the tracker initialization information to generate a track for the object.

The present disclosure is directed to a modular radar apparatus and to methods for using a modular radar apparatus. Two or more modules of the radar apparatus may each include a reference signal antenna where a synchronization signal generated at a first module may be sent to a second module via a pair of respective reference signal antenna. When the synchronization signal is received by the second module, that signal may be provided to a phase locked loop (PLL) to synchronize timing of the second module with the first module. The PLL or a multiplier circuit could then generate signals with timing synchronized to the synchronization signal yet at frequencies higher than the synchronization signal. This synchronized timing may allow transmitted radar signals to be synchronized in time with received reflected radar signals more accurately because effects of transmitting synchronization signals via wired interconnects between modules is eliminated.

Ground truth data may be too sparse to supervise training of a machine-learned (ML) model enough to achieve an ML model with sufficient accuracy/recall. For example, in some cases, ground truth data may only be available for every third, tenth, or hundredth frame of raw data. Training an ML model to detect a velocity of an object when ground truth data for training is sparse may comprise training the ML model to predict a future position of the object based at least in part on image, radar, and/or lidar data (e.g., for which no ground truth may be available). The ML model may be altered based at least in part on a difference between ground truth data associated with a future time and the future position.

The present disclosure relates to a target following method, device, apparatus and system. The method includes: acquiring first orientation data sent by a UWB base station arranged on a target following apparatus and a following mode sent by a UWB beacon arranged on a target to be followed; processing, based on the following mode, the first orientation data to obtain second orientation data including a current distance between a target position and the UWB base station, and a second azimuth angle of a line where the target position and the UWB base station are located with respect to a current direction of a movement of the target following apparatus; and comparing the second orientation data with preset orientation data to obtain a comparison result, and controlling the target following apparatus to perform target following according to the comparison result.

Disclosed is a collision avoidance assisting apparatus which can execute an automatic braking process and an automatic steering process for avoiding collision with an obstacle. When the magnitude of a steering angle exceeds a predetermined threshold, the collision avoidance assisting apparatus determines that a driver has an intention of avoiding the collision by a steering operation and stops the automatic braking process and the automatic steering process. However, in such a case, the automatic braking process and the automatic steering process may be stopped when the steering angle exceeds the threshold as a result of execution of the automatic steering process. In view of this, when both the automatic braking process and the automatic steering process are being executed, the collision avoidance assisting apparatus continues the automatic braking process and the automatic steering process even when the magnitude of the steering angle is greater than the predetermined threshold.

An autonomous driving system includes a target object position recognition unit configured to recognize a target object position detected by a vehicle-mounted sensor based on map information in a map database, a vehicle position recognition unit configured to recognize a vehicle position, a relative-relationship-on-map acquisition unit configured to acquire a relative-relationship-on-map between the target object and the vehicle based on the target object position and the vehicle position on the map, a detected-relative-relationship acquisition unit configured to acquire a detected-relative-relationship between the target object detected by the sensor and the vehicle based on a result of detection performed by the sensor, a map accuracy evaluation unit configured to evaluate map accuracy of the map information based on the relative-relationship-on-map and the detected-relative-relationship, and an autonomous driving permission unit configured to permit an autonomous driving control using the map information based on the result of evaluation of the map accuracy.

A method for checking the plausibility of an initially known transverse movement of an object. The method includes: emission of a radar signal having constant signal frequency, and reception by a radar device of reflections of the radar signal having constant signal frequency; and checking the plausibility of the transverse movement of the object by analyzing frequency ranges corresponding to the transverse movement in a spectrum of the reflected radar signal having constant signal frequency.

A computer is programmed to determine a localization of a first vehicle, including location coordinates and an orientation of the first vehicle, based on first vehicle sensor data, and to wirelessly receive localizations of respective second vehicles, wherein a first vehicle field of view at least partially overlaps respective fields of view of each of the second vehicles. The computer is programmed to determine pair-wise localizations for respective pairs of the first vehicle and one of the second vehicles, wherein each of the pair-wise localizations defines a localization of the first vehicle relative to a global coordinate system based on a (a) relative localization of the first vehicle with reference to the respective second vehicle and (b) a second vehicle localization relative to the global coordinate system, and to determine an adjusted localization for the first vehicle that has a minimized sum of distances to the pair-wise localizations.

A vehicle includes a communicator that is mounted on the vehicle to perform wireless communication with a server and a controller operates the communicator to transmit an accident reception request signal and image data acquired by another vehicle to the server when the vehicle has an accident with an accident target vehicle. The controller operates the communicator to receive a fault ratio from the server when the server generates fault ratio data between the vehicle and the accident target vehicle based on the image data.