In an example method, a perception system receives first data representing a point cloud having a plurality of points, and clusters the points into a plurality of clusters. The clusters include a first cluster representing a first portion of an object and a second cluster representing a second portion of the object. Further, the perception system generates a first bounding box enclosing at least the first cluster and the second cluster, and generates a second bounding box enclosing at least the first cluster and the second cluster. The perception system selects either the first bounding box or the second bounding box, and outputs second data representing the object. The second data includes an indication of the selected bounding box and an indication of the object.

A vehicle computing system validates location data received from a Global Navigation Satellite System receiver with other sensor data. In one embodiment, the system calculates velocities with the location data and the other sensor data. The system generates a probabilistic model for velocity with a velocity calculated with location data and variance associated with the location data. The system determines a confidence score by applying the probabilistic model to one or more of the velocities calculated with other sensor data. In another embodiment, the system implements a machine learning model that considers features extracted from the sensor data. The system generates a feature vector for the location data and determines a confidence score for the location data by applying the machine learning model to the feature vector. Based on the confidence score, the system can validate the location data. The validated location data is useful for navigation and map updates.

Aspects relate to techniques for joint communication-ranging (JCR) channel estimation. A first wireless communication device may transmit a sidelink message to a second wireless communication device and receive bistatic communication channel feedback from the second wireless communication device based on the sidelink message. The first wireless communication device may further transmit a ranging signal, such as a radar signal or lidar signal, and obtain a monostatic ranging channel estimate based on the received reflected ranging signals. The first wireless communication device may then associate and correlate the monostatic ranging channel estimate with the bistatic communication channel feedback to obtain joint communication-ranging (JCR) side information. The first wireless communication device may then transmit a sidelink transmission to the second wireless communication device using a transmit power and/or a beamforming parameter selected based on the JCR side information.

An in-vehicle radar signal control method includes: determining a target interference area of a first vehicle, a vehicle in the target interference area interfering with an in-vehicle radar signal of the first vehicle; determining vehicles in the target interference area as a first vehicle cluster, and determining strength of in-vehicle radar signals of vehicles in the first vehicle cluster; determining whether a new second vehicle enters the target interference area; and in response to a determination that the second vehicle enters the target interference area, obtaining an adjustment signal; the adjustment signal indicating one or more of: increasing or reducing strength of the in-vehicle radar signal of the first vehicle, adjusting a travel speed of the first vehicle, and adjusting a travel direction of the first vehicle.

A radar sensing system including transmit antennas and receive antennas, transmitters, receivers, and a controller. The system further includes a transmit antenna switch selectively coupling each of the transmitters to a respective transmit antenna, and a receive antenna switch selectively coupling at least one receiver of the receivers to respective receive antennas. A quantity of receivers is different from a quantity of the receive antennas. The controller is operable to select a quantity of receivers to be coupled to receive antennas to realize a desired quantity of virtual receivers. The controller is operable to select an antenna pattern as defined by the selected quantity of receivers coupled to receive antennas.

Methods, systems, and products for resolving level ambiguity for radar systems of autonomous vehicles may include detecting a plurality of objects with a radar system. Each first detected object may be associated with an existing tracked object based on a first position thereof. First tracked object data based on a first height determined for each first detected object may be stored. The first height may be based on the position of the detected object, the existing tracked object, and a tile map. Second tracked object data based on a second height determined for each second detected object not associated with the existing tracked object(s) may be stored. The second height may be based on a position of each second detected object, a vector map, and the tile map. A command to cause the autonomous vehicle to perform at least one autonomous driving operation may be issued.

A detection system includes a first-sensor, a second-sensor, and a controller. The first-sensor is mounted on a host-vehicle. The first-sensor detects objects in a first-field-of-view. The second-sensor is positioned at a second-location different than the first-location. The second-sensor detects objects in a second-field-of-view that at least partially overlaps the first-field of view. The controller is in communication with the first-sensor and the second-sensor. The controller selects the second-sensor to detect an object-of-interest in accordance with a determination that an obstruction blocks a first-line-of-sight between the first-sensor and the object-of-interest.

A control apparatus (10) generates probe data from sensing data obtained by sensing objects in a mobile object's surroundings. The control apparatus (10) selects at least some pieces of probe data as transmission data from the probe data generated, according to a communication resource determined according to a role of the mobile object. The control apparatus (10) transmits the transmission data selected to a management server (20). The management server (20) updates management data such as a dynamic map based on the transmission data.

An example system includes a roadside apparatus and an in-vehicle device for position-based parking of a vehicle, for example, in environments with weak GPS signals. The roadside apparatus determines a first posture data of a vehicle that includes a relative position and an orientation of the vehicle. The relative position is with respect to a predetermined location associated with the roadside apparatus. The roadside apparatus transmits the first posture data, and the in-vehicle device receives the first posture data. The in-vehicle device dynamically evaluates a predetermined rule with the first posture data. The predetermined rule defines a target posture data with respect to both relative position and orientation. The in-vehicle device controls, in response to the predetermined rule failing to be satisfied, the vehicle to perform a posture adjustment operation based on posture adjustment data determined from a difference between the target posture data and the first posture data.

A system for estimating a distance between vehicles may include an oscillator, a transmitter, a receiver, a summing circuit, a signal analyzer, a tunable phase shifter, a distance estimator, and/or a vehicle identifier. The oscillator may generate a generated oscillating signal, transmitted by the transmitter. The receiver may receive a processed signal derived by a system of a second vehicle. The summing circuit may add the generated oscillating signal to the received signal to produce the updated oscillating signal. The signal analyzer may detect a spike in amplitude associated with the updated oscillating signal. The tunable phase shifter may shift a phase of the generated oscillating signal by an incremental phase shift amount until a spike in amplitude is detected. The distance estimator may estimate the distance between the first vehicle and the second vehicle based on a total phase shift amount and the predetermined wavelength.