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.

A method carried out in a system including at least a first imaging unit mounted on a first entity or first vehicle, at least a second imaging unit mounted on a second entity, the method including: —building, from the first imaging unit, a first map, formed as a floating map, through a simultaneous localization and mapping process; —building, from the second imaging unit, a second map; —establishing a data channel between first and second entities; —determining if there is at least an overlapping portion between first and second maps; —receiving, at the first entity, part or all the elements of the second map, from the second entity; —identifying matching candidate solutions to register the second map into the first map; and —registering and appending the second map to the first map of first vehicle.

An autonomous vehicle (AV) includes features that allows the AV to comply with applicable regulations and statues for performing safe driving operation. An example method for operating the AV includes determining a trajectory related information of a vehicle operating on a roadway on which the AV is operating; receiving sensor data of a first area that includes the vehicle; determining an additional trajectory related information for the AV by comparing the trajectory related information of the vehicle to a current trajectory related information of the AV, wherein the additional trajectory related information is based on a category to which the vehicle belongs, and wherein the additional trajectory related information allows the AV to maintain at least a distance between the AV and the vehicle; and causing the AV to operate in accordance with the additional trajectory related information.

A system to detect an occupant left in a vehicle includes a sensor, a determiner, and a controller. The sensor outputs a radio wave and detects a wave reflected by the occupant being left in the compartment. The determiner determines whether the occupant is left in the compartment, at least based on a detection result from the detected reflected wave. The controller selects a radio wave to be output from the sensor from those of different frequencies including a first radio wave a second radio wave lower in frequency than the first radio wave. The controller is configured to switch from the first radio wave to the second radio wave when the occupant is leaving the vehicle, and cause the determiner to determine whether the occupant is left, based on a detection result from the reflected wave detected by the sensor which output the second radio wave.

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.

A system for intelligently implementing an autonomous agent that includes an autonomous agent, a plurality of infrastructure devices, and a communication interface. A method for intelligently calibrating infrastructure (sensing) devices using onboard sensors of an autonomous agent includes identifying a state of calibration of an infrastructure device, collecting observation data from one or more data sources, identifying or selecting mutually optimal observation data, specifically localizing a subject autonomous agent based on granular mutually optimal observation data, identifying dissonance in observation data from a perspective of a subject infrastructure device, and recalibrating a subject infrastructure device.

Simulated degraded sensor data may be generated for use in training a model. For instance, first sensor data collected by a sensor of a perception system of an autonomous vehicle may be received and converted into the simulated degraded sensor data for a particular degrading condition, such as a weather-related degrading condition. Then, the simulated degraded sensor data may be used to train a model for evaluating performance of the perception system to detect objects external to the autonomous vehicle under one or more conditions.

A system for intelligently implementing an autonomous agent that includes an autonomous agent, a plurality of infrastructure devices, and a communication interface. A method for intelligently calibrating infrastructure (sensing) devices using onboard sensors of an autonomous agent includes identifying a state of calibration of an infrastructure device, collecting observation data from one or more data sources, identifying or selecting mutually optimal observation data, specifically localizing a subject autonomous agent based on granular mutually optimal observation data, identifying dissonance in observation data from a perspective of a subject infrastructure device, and recalibrating a subject infrastructure device.

An apparatus for radar synchronization may include a local radar device configured to transmit and receive radar signals; a wireless device configured to wirelessly transmit and receive data; at least one processor operably coupled to the wireless device and the radar device, and the at least one processor configured to perform a method including obtaining local radar information regarding one or more radar pulses sent and/or received by the local radar device; and obtaining neighboring radar information associated with radar pulses sent and/or received from one or more neighboring radar devices; and updating a radar data structure using the obtained local and neighboring radar information, wherein the radar data structure comprises radar information for each of a plurality of radar pulses transmitted by the local radar device and/or the one or more neighboring radar devices.

A system for virtual aperture array radar tracking includes a transmitter that transmits first and second probe signals; a receiver array including a first plurality of radar elements positioned along a first radar axis; and a signal processor that calculates a target range from first and second reflected probe signals, corresponds signal instances of the first reflected probe signal to physical receiver elements of the radar array, corresponds signal instances of the second reflected probe signal to virtual elements of the radar array, calculates a first target angle between a first reference vector and a first projected target vector from the first reflected probe signal, and calculates a position of the tracking target relative to the radar array from the target range and first target angle.