Abstract: A system of linearizing a trajectory of an autonomous vehicle about a reference path includes a computing device and a computer-readable storage medium.

Abstract: Systems, methods, and computer-readable media are disclosed for a systems and methods for improved LIDAR return light capture efficiency. One example method may include comparing, by a controller including a processor and at a first time, a first temperature of a first computing element to a first threshold temperature and a second temperature of a second computing element to a second threshold temperature. The example method may also include sending, based on a determination that the first temperature is below the first threshold temperature and the second temperature is above the second threshold temperature, a first signal to a switch to activate a data output corresponding to the second computing element. The example method may also include sending, to the second computing element, a second signal to cause a third computing element to increase heat dissipation from the third computing element to the first computing element.

Abstract: Lidar systems may use highly sensitive GmAPD detectors to track obstacles in the environment of an autonomous vehicle. Data sensed by a lidar GmAPD detector can be pre-conditioned to facilitate differentiating low intensity signals from background noise. By sampling raw avalanche counts accumulated by the detector as Bernoulli trials, binomial statistics can be leveraged to transform raw data to a probability distribution, and then to a normalized data set suitable for signal processing.

Abstract: Systems, methods, and computer-readable media are disclosed for identifying light flares in images. An example method may involve receiving an image from an imaging device, the image including data indicative of a flare artifact originating from a region of the image. The example method may also involve determining, based on the image data, a first array of pixels extending radially outwards from the region and a second array of pixels extending radially outwards from the region. The example method may also involve creating, based on the image data, a flare array, the flare array including the first array of pixels and the second array of pixels. The example method may also involve determining, based on the flare array, a peak flare artifact value indicative of a size of the flare artifact. The example method may also involve determining, based on the peak flare artifact value, a flare artifact score for the imaging device.

Abstract: A single photon counting sensor array includes one or more emitters configured to emit a plurality of pulses of energy, and a detector array comprising a plurality of pixels. Each pixel includes one or more detectors, a plurality of which are configured to receive reflected pulses of energy that were emitted by the one or more emitters. A mask material is positioned to cover some but not all of the detectors of the plurality of pixels to yield blocked pixels and unblocked pixels so that each blocked pixel is prevented from detecting the reflected pulses of energy and therefore only detects intrinsic noise.

Abstract: At compile-time, a processor develops a computer program by receiving an input that includes multiple nodes and connections between pairs of the nodes. The nodes represent object properties such as properties of objects that an autonomous vehicle (AV) detects while moving about an environment. For each node, the system will identify a depth that represents a number of nodes along a longest path from that node to any available input node. The system will order the nodes by depth in a sequence, and it will build a graph-based program specification that includes the nodes in the sequence, along with the connections. The graph-based program specification may correspond to a directed acyclic graph (DAG). The system will compile the graph-based program specification into a computer-readable program, and it will save the computer-readable program to a memory so that the AV or other system can use it at run-time.

Abstract: Systems, methods, and computer-readable media are disclosed for context aware verification for sensor pipelines. Autonomous vehicles (AVs) may include an extensive number of sensors to provide sufficient situational awareness to perception and control systems of the AV. For those systems to operate reliably, the data coming from the different sensors should be checked for integrity. To this end, the systems and methods described herein may use contextual clues to ensure that the data coming from the different the sensors is reliable.

Abstract: A system provides navigational control information to a fleet of vehicles and includes a network of nodes within a geographical area. Each node is located at a different intersection in the geographical area. Each node includes a node vision range and a processor which generates augmented perception data (APD) for each moving object of interest monitored in the node vision range. The system includes a remote server system that includes a database of the APD and receives a query from a vehicle of the fleet for the APD associated with an imminent path of the vehicle. The server system, in response to the query, searches the database for APD associated with the imminent path, and communicates, over a communication network, the resultant APD associated with the imminent path to the vehicle. The APD controls navigation of the vehicle through one or more imminent intersections along the imminent path.

Abstract: Systems, methods, and computer-readable media are disclosed for closed-loop control of a motor in a LIDAR system over a wireless power interface using data feedback over a unidirectional data communications interface. An example method may include receiving, by a controller on a first portion in a LIDAR system, from a second portion including a second motor, and over a unidirectional data communication interface, data associated with the second motor, wherein the second portion is configured to rotate relative to the first portion. An example method may also include providing, over a wireless power transfer interface, to the second portion, and based on the data, a power signal, wherein the power signal is used to provide power to the second motor.

Abstract: Devices, systems, and methods are provided for counter-steering penalization. A device may analyze, by one or more processors, lane geometry associated with one or more lanes at a geographic location. The device may identify one or more corners in the lane geometry. The device may select one or more desired maximum steering angles of a steering wheel of an autonomous vehicle. The device may select weight values associated with the one or more desired maximum steering angles. The device may execute a path planning optimization based on the one or more desired maximum steering angles and the weight values.

Abstract: Devices, systems, and methods are provided for enhanced sensor cleaning validation. A device may determine a baseline performance measurement associated with a clean performance baseline of a sensor. The device may actuate a cleaning mechanism to remove at least a portion of an obstruction deposited on the sensor. The device may determine a first post-clean performance measurement associated with the sensor. The device may determine a degradation measurement between the baseline performance measurement and the first post-clean performance measurement, wherein the degradation measurement indicates an effectiveness of the cleaning mechanism.

Abstract: Devices, systems, and methods are provided for enhanced rider pairing of an autonomous vehicle (AV). A system may pair a first user profile of a first user located at a first location with a first autonomous vehicle (AV) to complete a trip to a destination selected by the first user. The system may detect a second AV at the first location, wherein the second AV is associated with a second user profile. The system may connect the second AV with the first user using a connection mechanism. The system may select a profile status of the first user profile based on the connection to the second AV. The system may pair the first user profile with the second AV based on the profile status.

Abstract: Systems and methods for operating radar systems. The methods comprise, by a processor: receiving point cloud information generated by radar devices; grouping data points of the point cloud to form at least one segment; computing possible true range-rate values for each data point in the at least one segment; identifying a scan window including possible true range-rate values for a largest number of data points; determining whether at least two modulus of the data points associated with the possible true range-rate values included in the identified scan window have moduli values that are different by a certain amount; determining a new range-rate value for each data point of the segment, when a determination is made that at least two modulus of the data points do have moduli values that are different by the certain amount; and modifying the point cloud information in accordance with the new range-rate value.

Abstract: Devices, systems, and methods are provided for compressive sensing using photodiode data. A device may identify light detecting and ranging (LIDAR) data detected by a sensor, the LIDAR data including a first time-of-flight (ToF) and a second ToF. The device may generate, based on the first ToF, a first frequency value. The device may generate, based on the second ToF, a second frequency value. The device may generate, based on the first value, a first sinusoid. The device may generate, based on the second value, a second sinusoid. The device may generate, based on the first sinusoid and the second sinusoid, a compressed signal in a domain incoherent with the time domain. The device may extract range information based on the compressed signal, and may control operation of a vehicle based on the range information.

Abstract: Devices, systems, and methods are provided for reducing interference of light detection and ranging (LIDAR) emissions. A vehicle may identify location information associated with a location of the vehicle. The vehicle may select, based on the location information, a modulation code associated with a LIDAR photodiode of the vehicle. The vehicle may emit, using the LIDAR photodiode, one or more LIDAR pulses based on the modulation code.

Abstract: Systems and methods for operating a vehicle. The methods comprise, by a processor: obtaining a pair of stereo images captured by a stereo camera; processing the pair of stereo images to generate a disparity map comprising a plurality of pixels defined by intensity values; converting each intensity value to a 3D position in a map (each 3D position defining a location of a data point in a point cloud); performing a hierarchical decision tree classification to determine a classification for each data point in the point cloud (the classification being a foreground classification or a background classification); and using the classifications to facilitate autonomous control of the vehicle.

Abstract: Systems and methods are provided for representing a traffic signal device. The method includes receiving a digital image of a traffic signal device that includes one or more traffic signal elements, representing the traffic signal device as a raster image, each traffic signal element of the traffic signal device being represented by a mask corresponding to a location of the traffic signal element on the traffic signal device, representing each mask in a channel in the raster image, providing the raster image as an input to a neural network to classify a state for each of the one or more traffic signal elements, and receiving, from the neural network, a classified raster image, in which the classified raster image includes a plurality of masks, each mask representing a state of one of the one or more traffic signal elements.

Abstract: Devices, systems, and methods are provided for testing and validation of a camera. For example, a system includes a camera that is configured to capture an image of a content object. A processor is programmed to: receive a signal indicative of the image of the content object during an electromagnetic event; generate an image quality score of the image; and generate a validation status of the camera based on a comparison of the image quality score to a validation threshold.

Abstract: Systems and methods for object detection. Object detection may be used to control autonomous vehicle(s). For example, the methods comprise: obtaining, by a computing device, a LiDAR dataset generated by a LiDAR system of autonomous vehicle; and using, by the computing device, the LiDAR dataset and image(s) to detect an object that is in proximity to the autonomous vehicle. The object is detected by performing the following operations: computing a distribution of object detections that each point of the LiDAR dataset is likely to be in; creating a plurality of segments of LiDAR data points using the distribution of object detections; merging the plurality of segments of LiDAR data points to generate merged segments; and detecting the object in a point cloud defined by the LiDAR dataset based on the merged segments. The object detection may be used by the computing device to facilitate at least one autonomous driving operation.

Abstract: A system of creating a simulation to simulate behavior of an autonomous vehicle includes a simulation system having an electronic device and a computer-readable storage medium having one or more programming instructions. When executed, the one or more programming instructions cause the electronic device to identify an event that is to be analyzed, receive from an autonomous vehicle system a first data stream that includes event information from one or more vehicle event log files that corresponds to the event, receive from a vehicle dynamics model a second data stream that includes synthetic event information that corresponds to the event, until a switch point is detected operate in a pure log execution stage, upon detection of the switch point operate in a play-forward execution stage, and cause the new simulation to be executed.