Abstract: An occupancy grid determination method includes: determining a predicted occupancy grid based on a previous occupancy grid, the predicted occupancy grid comprising a plurality of first cells corresponding to sub-regions of a region, each of the plurality of first cells including a plurality of predicted indications of probability each indicative of a predicted probability of a respective possible type of occupier of the respective first cell; determining, using machine learning and based on the first sensor measurements, an observed occupancy grid comprising a plurality of second cells corresponding to the sub-regions of the region; and determining an updated occupancy grid based on the observed occupancy grid and the predicted occupancy grid.

Abstract: An occupancy grid probability prediction method includes: determining a dynamic particle probability based on a first probability that a dynamic particle will move from a donor cell of an occupancy grid to a recipient cell of the occupancy grid; and determining one or more predicted probabilities of at least one of the donor cell or the recipient cell based on the dynamic particle probability.

Abstract: An electronic imaging device and method for image capture are described. The imaging device includes a camera configured to obtain image information of a scene and that may be focused on a region of interest in the scene. The imaging device also includes a LIDAR unit configured to obtain depth information of at least a portion of the scene at specified scan locations of the scene. The imaging device is configured to detect an object in the scene and provides specified scan locations to the LIDAR unit. The camera is configured to capture an image with an adjusted focus based on depth information, obtained by the LIDAR unit, associated with the detected object.

Abstract: Techniques for determining an alternative communication mode for vehicle-to-vehicle communication at a host vehicle can include monitoring the primary mode of RF communication to ensure it is effectively communicating and, if not, intelligently selecting a backup communication mode comprising one or more other sensors and/or systems of the vehicle. The selection of the backup communication mode may take into account various factors that can affect the various modes of communication from which the backup communication mode is selected.

Abstract: Embodiments provided herein allow for identification of one or more regions of interest in a radar return signal that would be suitable for selected application of super-resolution processing. One or more super-resolution processing techniques can be applied to the identified regions of interest. The selective application of super-resolution processing techniques can reduce processing requirements and overall system delay. The output data of the super-resolution processing can be provided to a mobile computer system. The output data of the super-resolution processing can also be used to reconfigure the radar radio frequency front end to beam form the radar signal in region of the detected objects. The mobile computer system can use the output data for implementation of deep learning techniques. The deep learning techniques enable the vehicle to identify and classify detected objects for use in automated driving processes.

Abstract: Aspects of the disclosure are related to a Lidar device, comprising: a vibrating fiber optic cantilever system on a transmit (TX) path; and a two-dimensional (2D) light sensor array on a receive (RX) path.

Abstract: Methods and apparatus for providing dynamically adjusted radiated signals are disclosed. In one aspect, a method of detecting one or more objects in a path of travel of a vehicle may include generating a laser with radiated power. The method may further include emitting the laser in a direction of travel of the vehicle and receiving one or more reflections of the emitted laser reflected from the one or more objects located in the direction of travel of the vehicle. The method may also further include generating a signal indicating that the one or more objects are in a path of the vehicle based on the received one or more reflections. The method may also include dynamically adjusting the radiated power of the laser based on an input corresponding to one or more of (i) a current speed of the vehicle or (ii) a current position of the vehicle.

Abstract: Various aspects of the present disclosure generally relate to vehicle sensors. In some aspects, a device associated with a vehicle may obtain, from an external source, calibration data including a first set of measurements related to a position of one or more objects in a reference frame associated with the external source. The device may identify a second set of measurements related to the position of the one or more objects within a field of view of one or more onboard sensors, and update a calibration table based at least in part on a comparison of one or more of the first set of measurements and one or more of the second set of measurements that are most time-aligned. Accordingly, the device may convert sensor-derived location information from a source reference frame to a reference frame associated with the vehicle using the updated calibration table. Numerous other aspects are provided.

Abstract: A method includes, by a mobile device, receiving a Global Navigation Satellite System (GNSS) signal, and receiving, from a wireless device, via a PC5 interface, a message including a location of a reference structure. The method also includes determine whether the GNSS signal is a spoofing signal based on a difference between the location of the reference structure and a location of the mobile device determined based on the GNSS signal.

Abstract: The present disclosure generally relates to an object detection system. For example, aspects of the present disclosure relate to systems and techniques for performing object detection using sensor information, such as elevation and/or velocity information from one or more light-based sensors. One example apparatus generally includes one or more processors operably configured to: obtain sensor information indicating at least two objects in an environment; determine at least one of a velocity or an elevation associated with each object of the at least two objects; consolidate the at least two objects into a common object based on the at least one of the velocity or the elevation; and output an indication of the common object.

Abstract: Methods, systems, computer-readable media, and apparatuses for determining one or more attributes of at least one target based on eigenspace analysis of radar signals are presented. In some embodiments, a subset of eigenvectors to use for forming a signal or noise subspace is identified based on principal component analysis. In some embodiments, the subset of eigenvectors is identified based on estimating the total number of targets using a discrete Fourier transform (DFT) or other spectral analysis technique. In some embodiments, a DFT is used to identify areas of interest in which to perform eigenspace analysis. In some embodiments, a DFT is used to estimate one attribute of a target, and eigenspace analysis is performed to estimate a different attribute of the target, with the results being combined to generate a multi-dimensional representation of a field of view.

Abstract: Efficient super-resolution of stationary objects (e.g., objects on the roadside or above the road) can be achieved in automotive imaging radar by obtaining sensor information regarding the motion of the radar system (e.g., vehicle speed), performing analog plurality of scans of different elevations, removing motion from the data by applying the inverse of the motion of the radar system, applying a beamspace processing algorithm to achieve super resolution, and outputting a detailed high-resolution radar image of the stationary objects.

Abstract: Disclosed are systems, apparatuses, processes, and computer-readable media to implement a heterogenous biometric authentication process in a control system. A process includes obtaining radar information identifying measured properties of at least one object in an environment, generating pre-processed radar information for input into a neural network at least in part by processing the obtained radar information, generating an object detection output for the at least one object at least in part by detecting the at least one object using the neural network with the pre-processed radar information as input, and modifying, based on the obtained radar information, the object detection output for the at least one object.

Abstract: Techniques for determining an alternative communication mode for vehicle-to-vehicle communication at a host vehicle can include monitoring the primary mode of RF communication to ensure it is effectively communicating and, if not, intelligently selecting a backup communication mode comprising one or more other sensors and/or systems of the vehicle. The selection of the backup communication mode may take into account various factors that can affect the various modes of communication from which the backup communication mode is selected.

Abstract: Techniques for determining an alternative communication mode for vehicle-to-vehicle communication at a host vehicle can include monitoring the primary mode of RF communication to ensure it is effectively communicating and, if not, intelligently selecting a backup communication mode comprising one or more other sensors and/or systems of the vehicle. The selection of the backup communication mode may take into account various factors that can affect the various modes of communication from which the backup communication mode is selected.

Abstract: A range estimator determines an at least one code sequence, causes an at least one light source to send the at least one code sequence as an at least one coded light transmission toward one or more targets, wherein the at least one code sequence is encoded as an amplitude-based code over time, or as a wavelength-based code over time, or as a combination thereof, in the at least one coded light transmission, causes a reflected version of the at least one coded light transmission to be received at an at least one sensor from the one or more targets, as a reflected light signal, correlates the reflected light signal with the at least one code sequence, to generate a time-of-flight value for the at least one coded light transmission, and generates a range estimate for the at least one coded light transmission based on the time-of-flight value.

Abstract: System and method for processing a camera frame in a mobile device by partitioning the camera frame into different sections based on the distance from a vehicle to each of the sections and the required resolution of each of the sections. A mobile device comprises: a memory; a processor communicatively coupled to the memory, the processor configured to: receive a camera frame from a camera mounted on a vehicle traveling on a road; determine a drivable path of the vehicle; project the drivable path onto the camera frame; partition a part of the camera frame containing the drivable path into at least one section based on a distance from the vehicle to each of the at least one section; and determine a required resolution of each of the at least one section based on the distance from the vehicle to each of the at least one section.

Abstract: In some aspects, a device may receive point data associated with a cell of an occupancy grid for controlling a vehicle. The device may determine, based on the point data, a characteristic of the cell that is associated with an occupancy probability of the cell, wherein the occupancy probability is determined according to a first technique based on the point data. The device may configure, based on the characteristic, the occupancy probability for the cell, within the occupancy grid, according to a second technique. Numerous other aspects are described.

Abstract: A method includes, by a mobile device, receiving a Global Navigation Satellite System (GNSS) signal, and receiving, from a wireless device, via a PC5 interface, a message including a location of a reference structure, a calculated location of the mobile device, or a combination thereof. The method also includes determine whether the GNSS signal is a spoofing signal based on: a spoof indication of the GNSS signal, and whether a difference between a location of the mobile device determined based on the GNSS signal and one of the location of the reference structure, the calculated location of the mobile device, or a location of the mobile device determined based on the location of the reference structure is greater than a threshold value.

Abstract: In some aspects, a system may receive, from a first one-dimensional radar array, first information based at least in part on first reflections associated with an azimuthal plane. The system may further receive, from a second one-dimensional radar array, second information based at least in part on second reflections associated with an elevation plane. Accordingly, the system may detect an object based at least in part on the first information and may determine an elevation associated with the object based at least in part on the second information. Numerous other aspects are described.