Abstract: Systems, methods, and computer-readable media are provided for detecting a pavement marking around an autonomous vehicle, comparing the detected pavement marking with a pavement marking present in a semantic data map, determining whether a change has occurred between the detected pavement marking and the pavement marking present in the semantic data map, and updating the semantic data map based on the determining of whether the change has occurred between the detected pavement marking and the pavement marking present in the semantic data map.

Abstract: Systems and methods for collision imminent detection are provided. A method includes collecting sensor data generated by one or more sensors of a vehicle; detecting, by a fallback control system of the vehicle based on the sensor data, an imminent collision between the vehicle and an object in an environment of the vehicle using a first process different from a second process of a primary control system of the vehicle, wherein the first process and the second process are associated with at least one of a perception or a prediction; and transmitting, by the fallback control system to the primary control system, an indication of the detected imminent collision.

Abstract: A method is described and includes receiving a frame of point cloud data from at least one onboard light detection and ranging (LIDAR) sensor of a vehicle; discarding points of the received frame of point cloud data that are outside a defined geographic area around the vehicle; and, subsequent to the discarding, performing ray tracing in connection with the remaining points of the received frame of point cloud data. The method may further include characterizing an occupancy condition of each of a plurality of cells of a three-dimensional (3D) grid corresponding to the defined geographic area based on the ray tracing of the received frame of point cloud data, wherein the 3D grid corresponds to the received frame of point cloud data.

Abstract: Systems and methods for a vehicle to use a fallback control system orthogonal to a primary control system are provided. A method includes collecting, by a fallback control system of a vehicle, sensor data generated by one or more sensors of the vehicle; determining, by the fallback control system using a first process different from a second process of a primary control system of the vehicle, an alternative action for the vehicle based on the sensor data; and sending, by the fallback control system based on the alternative action, an instruction for modifying an action associated with the primary control system upon a faulty condition associated with the primary control system.

Abstract: A method is described and includes receiving an indication that a collision between a vehicle and an object is predicted; processing first sensor data obtained from a first onboard sensor of the vehicle to determine whether an actual occurrence of the predicted collision can be confirmed from the first sensor data and if not, processing second sensor data obtained from a second onboard sensor of the vehicle to determine whether the actual occurrence of the predicted collision can be confirmed from the second sensor data. If the actual occurrence of the predicted collision is confirmed from one of the first sensor data and the second sensor data, determining a severity of the collision based on the indication and the one of the first sensor data and the second sensor data; and prompting an action to be based on the determined severity of the collision.

Abstract: Systems, methods, and computer-readable media are provided for detecting a pavement marking around an autonomous vehicle, comparing the detected pavement marking with a pavement marking present in a semantic data map, determining whether a change has occurred between the detected pavement marking and the pavement marking present in the semantic data map, and updating the semantic data map based on the determining of whether the change has occurred between the detected pavement marking and the pavement marking present in the semantic data map.

Abstract: The disclosed technology provides solutions for enhanced road paint feature detection, for example, in an autonomous vehicle (AV) deployment. A process of the disclosed technology can include steps for receiving image data from a vehicle mounted camera, receiving height map data corresponding to a location associated with the image data, and calculating a region of interest that includes a portion of the image data determined based on the height map data. An image patch is generated by projecting the portion of image data included within the region of interest into a top-down view. The image patch is analyzed to detect one or more road paint features in the top-down view, and, in response to detecting an unlabeled road paint feature, the unlabeled road paint feature is localized based at least in part on the height map data. Systems and machine-readable media are also provided.

Abstract: Systems, methods, and computer-readable media are provided for detecting a pavement marking around an autonomous vehicle, comparing the detected pavement marking with a pavement marking present in a semantic data map, determining whether a change has occurred between the detected pavement marking and the pavement marking present in the semantic data map, and updating the semantic data map based on the determining of whether the change has occurred between the detected pavement marking and the pavement marking present in the semantic data map.

Abstract: The disclosed technology provides solutions for updating high definition maps based on low resolution map assets. In some aspects, a process of receiving a change detection relating to a change in the real world is provided. The process can include steps for receiving autonomous vehicle drive data based on the change in the real world, generating low resolution tile data based on the autonomous vehicle drive data based on the change in the real world, generating updated semantic data based on the low resolution tile data generated, and providing the updated semantic data to an autonomous vehicle to update a proximate area of the change in the real world of a base map of the autonomous vehicle. Systems and machine-readable media are also provided.

Abstract: Systems, methods, and computer-readable media are provided for detecting a pavement marking around an autonomous vehicle, comparing the detected pavement marking with a pavement marking present in a semantic data map, determining whether a change has occurred between the detected pavement marking and the pavement marking present in the semantic data map, and updating the semantic data map based on the determining of whether the change has occurred between the detected pavement marking and the pavement marking present in the semantic data map.