Abstract: This disclosure provides systems and methods for controlling a vehicle. The method comprises receiving data from a set of sensors, wherein the data represents objects or obstacles in an environment of the autonomous vehicle; identifying objects or obstacles from the received data; determining multiple sets of attributes of the objects or obstacles, wherein each set of attributes of the objects or obstacles are determined based on data received by an individual sensor; determining a candidate trajectory for the autonomous vehicle based on the multiple sets of attributes of the objects or obstacles; and controlling the autonomous vehicle according to the candidate trajectory.

Abstract: Systems and methods for detecting a presence of water along a surface and adjusting a speed of a vehicle are provided. The method comprises generating one or more data points from one or more sensors coupled to a vehicle, and, using a processor, determining, based on the one or more data points, whether water is present along a surface, when water is present along the surface, determining a speed adjustment of the vehicle based on the water present along the surface, and generating a control signal configured to cause the vehicle to adjust a speed of the vehicle according to the speed adjustment.

Abstract: Systems, including remote station systems, and methods for remotely controlling a vehicle are provided. The remote station system may comprise a transmitter configured to receive one or more data points generated by one or more sensors coupled to a vehicle and, from the vehicle, a trajectory of the vehicle. The remote station system may comprise a display configured to display the one or more data points generated by the one or more sensors and display the trajectory of the vehicle. The remote station system may comprise one or more remote actuation controls configured generate one or more driving actions. The one or more driving actions may correlate to one or more actuator commands configured to cause the vehicle to perform the one or more driving actions. The transmitter may be configured to transmit the one or more driving actions to the vehicle.

Abstract: Systems and methods for controlling a vehicle is provided. The system may comprise a vehicle, one or more sensors, coupled to the vehicle, configured to generate one or more data points, one or more actuation controls configured to enable the vehicle to perform one or more driving actions, and an automatic trajectory control system, comprising a processor, configured to perform automatic trajectory control. The automatic trajectory control system may be configured to receive one or more data points generated by the one or more sensors, automatically generate an automatic trajectory command, generate one or more driving actions, and cause the vehicle, via the one or more actuation controls, to perform the one or more driving actions in accordance with the automatic trajectory command. The system may comprise a switch configured to switch command of the vehicle between automatic trajectory control and a remote station system control.

Abstract: Systems and methods for controlling a vehicle are provided. The system may comprise a vehicle, one or more sensors, one or more actuation controls configured to enable the vehicle to perform one or more driving actions, and a controller, comprising a processor, configured to receive one or more trajectory commands, automatically generate an automatic trajectory command, and generate one or more driving actions. The one or more driving actions may correlate to one or more actuator commands configured to cause the vehicle to be positioned in accordance with the one or more trajectory plot points of the automatic trajectory command. The system may comprise a remote station system comprising one or more remote actuation controls configured generate the one or more driving actions of the remote trajectory command. The remote station system may be configured to generate one or more driving actions.

Abstract: Systems and methods for controlling a vehicle are provided. The system may comprise a vehicle, one or more sensors configured to generate one or more data points, one or more actuation controls configured to enable the vehicle to perform one or more driving actions, and an automatic trajectory control system, comprising a processor, configured to perform automatic trajectory control. In the performing the automatic trajectory control, the automatic trajectory control system may be configured to transmit an automatic trajectory command to a remote station system. The system may comprise the remote station system. The remote station system may be configured to receive the one or more data points generated by the one or more sensors and generate one or more driving actions. The one or more driving actions may correlate to one or more actuator commands configured to cause the vehicle to perform the one or more driving actions.

Abstract: Systems and methods for controlling a vehicle are provided. The system may comprise a vehicle, one or more sensors configured to generate one or more data points, one or more actuation controls configured to enable the vehicle to perform one or more driving actions and a controller, configured to automatically generate an automatic trajectory command, generate, based on the one or more automatic trajectory plot points, one or more driving actions, determine whether a remote trajectory command is present for a predetermined timeframe, determine whether the remote trajectory command is different from the automatic trajectory command when the remote trajectory command is present for the predetermined timeframe, and cause the vehicle, via the one or more actuation controls, to perform the one or more driving actions during the predetermined timeframe in accordance with the remote trajectory command when the remote trajectory command is different from the automatic trajectory command.

Abstract: Systems and methods for controlling a vehicle are provided. The system may comprise a vehicle and one or more sensors, coupled to the vehicle, configured to generate one or more data points pertaining to one or more of an environment of the vehicle and one or more system component measurements of the vehicle. The system may comprise one or more actuation controls configured to enable the vehicle to perform one or more driving actions and a remote station system configured to receive the one or more data points generated by the one or more sensors, generate one or more driving actions, and transmit the one or more driving actions to the vehicle. The system may comprise a switch configured to switch command of the vehicle between automatic trajectory control and remote station system control.

Abstract: Systems (e.g., remote station systems) and methods for remotely controlling a vehicle are provided. The remote station system may comprise a transmitter configured to receive one or more data points and a processor configured to identify one or more objects within a field of view of the vehicle, using the one or more data points and generate a signal to magnify a section of the field of view of the vehicle containing the one or more objects. The remote station system may comprise a display configured to display the one or more data points generated by the one or more sensors and display the one or more objects in a magnified state. The remote station system may comprise one or more remote actuation controls configured generate one or more driving actions. The one or more driving actions may correlate to one or more actuator commands.

Abstract: A health indicator system for a sensor pod includes one or more sensors associated with the sensor pod, a sensor pod housing, an internal sensor status monitoring system configured to determine a status of at least one sensor of the one or more sensors, and a plurality of visual indicators located on at least one exterior surface of the sensor pod housing, the plurality of visual indicators configured to display a predetermined configuration based on the determined status of each of the one or more sensors. The plurality of visual indicators are located on the sensor pod housing at a level such that when an external operator standing on a ground surface approaches the vehicle, the plurality of visual indicators is within the external operator's field of view.

Abstract: Systems and methods are provided for providing redundant pulse-width modulation (PWM) throttle control. The system includes a manual throttle controller configured to generate a manual PWM throttle control signal, and an automated throttle control system. The automated throttle control system includes a plurality of automated throttle controllers, each of which being configured to independently control a throttle of a vehicle, and each including a processor configured to generate and output an automated PWM throttle control signal, a first double pole double throw (DPDT) relay that, when engaged, is configured to receive and output the manual PWM throttle control signal, and a second DPDT relay, configured to receive and output the automated PWM throttle control signal to an engine, when the second DPDT relay is engaged; and receive and output the manual PWM throttle control signal to the engine, when the DPDT relay is disengaged.

Abstract: Systems and methods for deploying warning devices for a vehicle. The vehicle can be an autonomous vehicle. A method of deploying warning devices for a vehicle includes deploying one or more warning devices from the vehicle, the one or more warning devices being coupled to a deployment vehicle. Deploying the one or more warning devices includes controlling the deployment vehicle. A system for deploying warning devices for a vehicle includes a deployment vehicle and one or more warning devices coupled to the deployment vehicle. The system includes a controller configured to deploy the one or more warning devices from the vehicle. Deploying the one or more warning devices includes the controller configured to control the deployment vehicle.

Abstract: Systems and methods for detecting a portion of an environment of a vehicle are provided. The method may comprise generating, using one or more sensors coupled to a vehicle, environment data from an environment of the vehicle, wherein the environmental data comprises one or more of the following: ground LiDAR data from the environment; camera data from the environment; and path data corresponding to a change in position of one or more other vehicles within the environment. The method may comprise inputting the environmental data into a machine learning model trained to generate a heatmap, and, using a processor, based on the environmental data, determining a portion of the environment, wherein the portion of the environment comprises an area having a likelihood, greater than a minimum threshold, of being adjacent to one or more pavement markings, and generating the heatmap, wherein the heatmap corresponds to the portion of the environment.

Abstract: Systems and methods are provided for identifying a vehicle subject to an emergency alert. The method includes receiving an emergency alert, wherein the emergency alert includes a geographic region associated with the emergency alert and one or more identifiable markers of a wanted vehicle, determining whether the autonomous vehicle is within the geographic region associated with the emergency alert, and detecting, using one or more detection mechanisms coupled to the autonomous vehicle, a detected vehicle within an environment of the autonomous vehicle. The method further includes, when the autonomous vehicle is within the geographic region associated with the emergency alert, determining, for each identifiable marker, whether the detected vehicle matches the identifiable marker, and when the detected vehicle matches the one or more identifiable markers, generating, using a processor coupled to the autonomous vehicle, a signal indicating that the detected vehicle is the wanted vehicle.

Abstract: Systems and methods are provided for identifying a vehicle subject to an emergency alert are provided. The system comprises one or more autonomous vehicles, each autonomous vehicle comprising a vehicle detection and identification system configured to analyze one or more vehicles within a surrounding environment, and a wireless emergency alert system. The wireless emergency alert system may be configured to receive or generate an emergency alert, wherein the emergency alert includes a geographic region associated with the emergency alert and one or more identifiable markers of a wanted vehicle, determine one or more autonomous vehicles to receive the emergency alert, and relay the emergency alert to the one or more autonomous vehicles.

Abstract: This disclosure provides methods and systems for dynamically creating a trajectory for navigating a vehicle. The method may include receiving sensor data from at least one sensor of the autonomous vehicle, the sensor data representative of a driving surface in a field of view of the autonomous vehicle; segmenting a portion of the driving surface in the field of view of the autonomous vehicle by determining nominal path based at least in part on the image data; assigning a plurality of nodes to at least a portion of the nominal path; associating the plurality of the nodes assigned to the nominal path with a line to generate at least one segmentation polyline; determining updated nominal path by fitting the each of the plurality of segmentation lines to the nominal path; generating a trajectory based on the updated nominal path; and navigating the autonomous vehicle according to the trajectory.

Abstract: Systems and methods for detecting and measuring object velocity are provided. The method comprises, using a spinning Light Detection and Ranging (LiDAR) system, generating a first LiDAR point cloud of an environment surrounding a vehicle, using a scanning LiDAR system, generating a second LiDAR point cloud of the environment surrounding the vehicle, and, using a processor, identifying points within the first LiDAR point cloud coinciding with a position of an object and points within the second LiDAR point cloud coinciding with a position of the object, determining whether the points within the second LiDAR point cloud line up with the points within the first LiDAR point cloud, and, when the points within the second LiDAR point cloud do not line up with the points within the first LiDAR point cloud, determining that the object is moving.

Abstract: Systems and methods are provided of downsampling an image to a plurality of image resolutions. The method comprises capturing, using a camera, an image depicting an environment within view of the camera, identifying a first section of the image depicting an area of the environment spaced within a first distance range from the camera, identifying a second section of the image depicting an area of the environment spaced within a second distance range from the camera, identifying a third section of the image depicting an area of the environment spaced within a third distance range from the camera, and downsampling the first section of the image to a first image resolution, generating a first processed image, the second section of the image to a second image resolution, generating a second processed image, and the third section of the image to a third image resolution, generating a third processed image.

Abstract: This disclosure provides methods and systems for detecting and tracking objects in an environment of an autonomous vehicle.

Abstract: This disclosure provides methods and systems for generating a training set for a neural network configured to generate candidate trajectories for an autonomous vehicle, comprising: receiving a set of sensor data representative of one or more portions of a plurality of objects in the environment of the autonomous vehicle; for each object, calculating a representative box enclosing the object, the representative box having portions comprising corners, edges, and planes; for each representative box, calculating at least one vector into the representative box from a position on the autonomous vehicle; for each vector, calculating a first and second corner position of the representative box, an edge of the representative box, and a plane of the representative box; determining the highest confidence corners, edge, and plane of each representative based on calculation from the at least one vector; and generating a training set including the highest confidence corners, edge, and plane of each representative box.