A method for evaluating an angular position of an object recognized on the basis of radar data, the radar data being ascertained by a radar device. The method includes: ascertaining of an intrinsic speed of the radar device; ascertaining a relative speed of the recognized object in relation to the radar device, using the ascertained radar data; ascertaining at least one angular test region using the ascertained intrinsic speed and the ascertained relative speed, the at least one angular test region corresponding to possible stationary objects that have a relative speed that substantially corresponds to the ascertained relative speed; and ascertaining whether an azimuth angle of the recognized object lies in the ascertained angular test region.

A method for enhancing situational awareness in a transportation vehicle including combination tractor and a trailer. The method includes locating a plurality of cameras on the trailer of the vehicle. Each camera is equipped with a camera wash system including a wash nozzle, dryer, and defroster. The cameras are operatively connected to a local area user network via an onboard access point. The onboard access point communicates with a data bus of the vehicle. At vehicle start-up, the cameras are automatically paired with a computing device located inside the tractor. The computing device includes a display screen and graphical interface with icon tabs representing each of the connected cameras. Using the icon tabs rendered on the display screen of the computing device, a selected camera and associated camera wash system can be manually activated.

A computer implemented method for radar data processing includes the following steps carried out by computer hardware components: acquiring radar data from a radar sensor mounted on a vehicle; determining at least one of a speed of the vehicle or a steering wheel angle of the vehicle; and determining a subset of the radar data for processing based on the at least one of the speed of the vehicle or the steering wheel angle of the vehicle.

Method and apparatus for light detection and ranging (LiDAR). In some embodiments, an emitter is used to emit a set of pulses to impinge a target, and a detector is used to detect a corresponding set of reflected pulses. Range information associated with the target is extracted using the reflected pulses. To compensate for doppler shift and enable more emitted pulses to be in-flight between the system and the target, a maximum expected doppler shift is determined, and the emitted pulses are provided with differential frequency intervals that are greater than the determined maximum expected doppler shift, such as a multiple (e.g., 2×) of the maximum expected doppler shift. In some cases, each in-flight pulse will have a unique frequency separated from all other pulse frequencies by at least the maximum expected doppler shift. Adaptive adjustments can be made such as increasing the differential frequency intervals for long distance targets.

A communication device includes a target locating unit configured to locate a position of a target having a risk of approaching a moving body. The communication device includes a transmission unit configured to transmit request information including positional information of an external terminal, for which the positional information is requested, based on the position of the target located by the target locating unit. The communication device includes a reception unit configured to receive response information with respect to the request information. The transmission unit is configured to transmit warning information based on the positional information of the external terminal included in the response information.

A method, apparatus and computer program product are provided to generate a model of one or more objects relative to a vehicle. In the context of a method, radar information is received in the form of in-phase quadrature (IQ) data and the IQ data is converted to one or more first range-doppler maps. The method further includes evaluating the one or more first range-doppler maps with a machine learning model to generate the model that captures the detection of the one or more objects relative to the vehicle. A corresponding apparatus and computer program product are also provided.

The invention relates to a method for operating a distance sensor (4) of a vehicle (1), in which method a plurality of successive measurement cycles are carried out in an operating mode, wherein, in each measurement cycle, a transmission signal is transmitted, a reception signal (Rx1 to Rx8) is determined on the basis of the transmission signal reflected in a surrounding region (9) of the vehicle (1), the object (8) is classified, and the transmission signal is selected from a plurality of predefined transmission signals in accordance with how the object (8) is classified, wherein the transmission signal is selected in accordance with an assignment rule determined in a learning mode, said assignment rule describing an assignment of the plurality of predefined transmission signals to classes of objects (8), wherein, in each measurement cycle, the object (8) is classified on the basis of the reception signal (Rx1 to Rx8) and the transmission signal is selected in accordance with how the object (8) is classified for subsequent measurement cycles.

System, methods, and other embodiments described herein relate to sensing interactions of a passenger with components within a vehicle. In one embodiment, a method includes acquiring, from a radar of a vehicle, radar data about a passenger cabin of the vehicle. The method includes determining a current state of the passenger cabin according to the radar data. The method includes, responsive to identifying that the current state indicates that a passenger satisfies a threshold in relation to an unpermitted action, generating a response that counters the unpermitted action.

Extrinsic calibration of a Light Detection and Ranging (LiDAR) sensor and a camera can comprise constructing a first plurality of reconstructed calibration targets in a three-dimensional space based on physical calibration targets detected from input from the LiDAR and a second plurality of reconstructed calibration targets in the three-dimensional space based on physical calibration targets detected from input from the camera. Reconstructed calibration targets in the first and second plurality of reconstructed calibration targets can be matched and a six-degree of freedom rigid body transformation of the LiDAR and camera can be computed based on the matched reconstructed calibration targets. A projection of the LiDAR to the camera can be computed based on the computed six-degree of freedom rigid body transformation.

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.