Abstract: A vehicle may include a primary system and a secondary system to validate operation of the primary system and to control the vehicle to avoid collisions. For example, the secondary system may receive multiple trajectories from the primary system, such as a primary trajectory and a secondary, contingent, trajectory associated with a deceleration or other maneuver. The secondary system may determine if a trajectory is associated with a potential collision, if the trajectory is consistent with a current or previous pose, if the trajectory is compatible with a capability of the vehicle, etc. The secondary system may select the primary trajectory if valid, the secondary trajectory if the primary trajectory is invalid, or another trajectory generated by the secondary system if the primary trajectory and the secondary trajectory are invalid. If no valid trajectory is determined, the vehicle may decelerate at a maximum rate.

Abstract: A vehicle can include a primary computing device and a secondary computing device. The primary computing device can receive a trajectory and can generate control data to control the vehicle based on a computed state. Further, the primary computing device can send the internal data to the secondary computing device configured to control the vehicle in the event of a failure of the primary computing device. The secondary computing device can receive the internal data as first internal data and determine a capability associated with the primary computing device. Using the first internal data, the secondary computing device can determine second internal data and, based on the capability (e.g., in event of a failure of the primary computing device), can control the vehicle to follow a trajectory using the second internal data. Transferring state between an active to a standby computing device can ensure algorithmic synchronization and safe operation.

Abstract: Techniques for detecting and responding to an emergency vehicle are discussed. A vehicle computing system may determine that an emergency vehicle based on sensor data, such as audio and visual data. In some examples, the vehicle computing system may determine aggregate actions of objects (e.g., other vehicles yielding) proximate the vehicle based on the sensor data. In such examples, a determination that the emergency vehicle is operating may be based on the actions of the objects. The vehicle computing system may, in turn, identify a location to move out of a path of the emergency vehicle (e.g., yield) and may control the vehicle to the location. The vehicle computing system may determine that the emergency vehicle is no longer relevant to the vehicle and may control the vehicle along a route to a destination. Determining to yield and/or returning to a mission may be confirmed by a remote operator.

Abstract: Techniques for determining an error model based on vehicle data and ground truth data are discussed herein. To determine whether a complex system (which may be not capable of being inspected) is able to operate safely, various operating regimes (scenarios) can be identified based on operating data. To provide safe operation of such a system, an error model can be determined that can provide a probability associated with perception data and a vehicle can determine a trajectory based on the probability of an error associated with the perception data.

Abstract: Techniques for determining a safety metric associated with a vehicle controller are discussed herein. To determine whether a complex system (which may be uninspectable) is able to operate safely, various operating regimes (scenarios) can be identified based on operating data and associated with a scenario parameter to be adjusted. To validate safe operation of such a system, a scenario may be identified for inspection. Error metrics of a subsystem of the system can be quantified. The error metrics, in addition to stochastic errors of other systems/subsystems can be introduced to the scenario. The scenario parameter may also be perturbed. Any multitude of such perturbations can be instantiated in a simulation to test, for example, a vehicle controller. A safety metric associated with the vehicle controller can be determined based on the simulation, as well as causes for any failures.

Abstract: Techniques for determining an error model associated with a system/subsystem of vehicle controller are discussed herein. To determine whether a complex system (which may be uninspectable) is able to operate safely, errors can be introduced into operating regimes (scenarios) to validate the safe operation of such a system. By comparing captured and/or generated vehicle data with ground truth data, an error of the system can be statistically quantified and modeled. The statistical model can be used to introduce errors to the scenario to perturb the scenario to test, for example, a vehicle controller. Based on a simulation of the vehicle controlled in the perturbed scenario, a safety metric associated with the vehicle controller can be determined, as well as causes for any failures.

Abstract: Command determination for controlling a vehicle, such as an autonomous vehicle, is described. In an example, individual requests for controlling the vehicle relative to each of multiple objects or conditions in an environment are received (substantially simultaneously) and based on the request type and/or additional information associated with a request, command controllers can determine control commands (e.g., different accelerations, steering angles, steering rates, and the like) associated with each of the one or more requests. The command controllers may have different controller gains (which may be based on functions of distance, distance ratios, time to estimated collisions, etc.) for determining the controls and a control command may be determined based on the all such determined controls.

Abstract: A vehicle may include a primary system for generating data to control the vehicle and a secondary system that validates the data and/or other data to avoid collisions. For example, the primary system may localize the vehicle, detect an object around the vehicle, predict an object trajectory, and generate a trajectory for the vehicle. The secondary system may localize the vehicle, detect an object around the vehicle, predict an object trajectory, and evaluate a trajectory generated by the primary system. The secondary system may also monitor components of the vehicle to detect an error. If the secondary system detects an error with a trajectory generated by the primary system and/or an error with a component of the vehicle, the secondary system may cause the vehicle to perform a maneuver, such as decelerating, changing lanes, swerving, etc.

Abstract: A vehicle can include a primary computing device and a secondary computing device. The primary computing device can receive a trajectory and can generate control data to control the vehicle based on a computed state. Further, the primary computing device can send the internal data to the secondary computing device configured to control the vehicle in the event of a failure of the primary computing device. The secondary computing device can receive the internal data as first internal data and determine a capability associated with the primary computing device. Using the first internal data, the secondary computing device can determine second internal data and, based on the capability (e.g., in event of a failure of the primary computing device), can control the vehicle to follow a trajectory using the second internal data. Transferring state between an active to a standby computing device can ensure algorithmic synchronization and safe operation.

Abstract: A vehicle may include a primary system and a secondary system to validate operation of the primary system and to control the vehicle to avoid collisions. For example, the secondary system may receive multiple trajectories from the primary system, such as a primary trajectory and a secondary, contingent, trajectory associated with a deceleration or other maneuver. The secondary system may determine if a trajectory is associated with a potential collision, if the trajectory is consistent with a current or previous pose, if the trajectory is compatible with a capability of the vehicle, etc. The secondary system may select the primary trajectory if valid, the secondary trajectory if the primary trajectory is invalid, or another trajectory generated by the secondary system if the primary trajectory and the secondary trajectory are invalid. If no valid trajectory is determined, the vehicle may decelerate at a maximum rate.

Abstract: Remote controlling of a vehicle, such as an autonomous vehicle, may sometimes be more efficient and/or reliable. Such control, however, may require processes for ensuring safety of surrounding persons and objects. Aspects of this disclosure include using onboard sensors to detect objects in an environment and alter remote commands according to such objects, e.g. by reducing a maximum permitted velocity of the vehicle as a function of distance to detected objects. In some examples described herein, such remote controlling may be performed by using objects in the environment as control objects, with movements of the control objects resulting in movement of the vehicle.

Abstract: A method for controlling a vehicle as it travels along a road includes processing at an ECU provided image data captured by a forward viewing camera and processing at the ECU a provided output indicative of a determined geographical location of the vehicle. Responsive at least in part to processing of the provided output, a geographically-derived path of travel of the vehicle is generated. Responsive to determination of a traffic lane in which the vehicle is traveling along the road, a camera-derived path of travel of the vehicle is generated. The vehicle is controlled based on (i) the geographically-derived path of travel of the vehicle and/or (ii) the camera-derived path of travel of the vehicle. The vehicle is controlled based on diminished weight of the geographically-derived path or diminished weight of the camera-derived path when a respective reliability level is below a threshold level.

Abstract: Remote controlling of a vehicle, such as an autonomous vehicle, may sometimes be more efficient and/or reliable. Such control, however, may require processes for ensuring safety of surrounding persons and objects. Aspects of this disclosure include using onboard sensors to detect objects in an environment and alter remote commands according to such objects, e.g. by reducing a maximum permitted velocity of the vehicle as a function of distance to detected objects. In some examples described herein, such remote controlling may be performed by using objects in the environment as control objects, with movements of the control objects resulting in movement of the vehicle.

Abstract: A vision system of a vehicle includes a camera disposed at a vehicle and having a field of view forward of the vehicle and operable to capture image data. A vehicle-based GPS system is operable to determine a geographical location of the vehicle. A control includes an image processor operable to process image data captured by the camera. Responsive at least in part to processing of captured image data by the image processor to determine lane markings and responsive at least in part to the GPS system and responsive at least in part to map data mapping the road along which the vehicle is traveling, the control is operable to determine an enhanced estimation of the path of travel of the vehicle. The enhanced estimation may be based on reliability levels or weighting factors of the determined lane markings and the map data.

Abstract: Remote controlling of a vehicle, such as an autonomous vehicle, may sometimes be more efficient and/or reliable. Such control, however, may require processes for ensuring safety of surrounding persons and objects. Aspects of this disclosure include using onboard sensors to detect objects in an environment and alter remote commands according to such objects, e.g. by reducing a maximum permitted velocity of the vehicle as a function of distance to detected objects. In some examples described herein, such remote controlling may be performed by using objects in the environment as control objects, with movements of the control objects resulting in movement of the vehicle.

Abstract: A method for vehicular control includes providing a forward viewing camera, a yaw rate sensor, a longitudinal accelerometer, a speed sensor and a control system at the vehicle. While the vehicle is moving, an angular rotational velocity of the vehicle about a local vertical axis is determined, a yaw rate offset is determined, and a longitudinal acceleration is determined. A corrected yaw rate is determined responsive to the determined yaw rate offset of the yaw rate sensor and the determined longitudinal acceleration of the vehicle. The control system determines a projected driving path of the vehicle based at least in part on the determined corrected yaw rate. A hazard condition ahead of the vehicle in the projected driving path is determined at least in part responsive to detecting an object and to the projected driving path. The system automatically applies the brakes of the vehicle responsive to the determined hazard condition.

Abstract: A method for vehicular control includes providing a forward viewing camera, a yaw rate sensor, a longitudinal accelerometer, a speed sensor and a control system at the vehicle. While the vehicle is moving, an angular rotational velocity of the vehicle about a local vertical axis is determined, a yaw rate offset is determined, and a longitudinal acceleration is determined. A corrected yaw rate is determined responsive to the determined yaw rate offset of the yaw rate sensor and the determined longitudinal acceleration of the vehicle. The control system determines a projected driving path of the vehicle based at least in part on the determined corrected yaw rate. A hazard condition ahead of the vehicle in the projected driving path is determined at least in part responsive to detecting an object and to the projected driving path. The system automatically applies the brakes of the vehicle responsive to the determined hazard condition.

Abstract: A method for determining a corrected yaw rate for a vehicle includes receiving a first yaw rate input from a yaw rate sensor of the vehicle and determining if the vehicle is moving or stationary. If the vehicle is determined to be moving, the method includes determining a steering angle of the vehicle, and determining an offset correction value based at least in part on a determined speed of the vehicle and the determined steering angle. A yaw rate offset is determined based at least in part on the determined offset correction value and the received first yaw rate input. A second yaw rate input is received from the yaw rate sensor of the vehicle, and a corrected yaw rate value is determined based at least in part on the received second yaw rate input and the determined yaw rate offset.

Abstract: A method for determining a corrected yaw rate for a vehicle includes receiving a first yaw rate input from a yaw rate sensor of the vehicle and determining if the vehicle is moving or stationary. If the vehicle is determined to be moving, the method includes determining a steering angle of the vehicle, and determining an offset correction value based at least in part on a determined speed of the vehicle and the determined steering angle. A yaw rate offset is determined based at least in part on the determined offset correction value and the received first yaw rate input. A second yaw rate input is received from the yaw rate sensor of the vehicle, and a corrected yaw rate value is determined based at least in part on the received second yaw rate input and the determined yaw rate offset.

Abstract: A process for determining a stationary state of a vehicle includes providing a camera and a control having an image processor. Vehicle data is provided to the control by an accelerometer of the vehicle and by at least one of (i) a transmission sensor of the vehicle and (ii) a speed sensor of the vehicle. A determination that the vehicle is stationary is made when at least one of (i) the control determines a jerk value that is approximately zero for a selected duration of time and the control receives vehicle data indicating that the speed of the vehicle was approximately zero for the selected duration of time and (ii) the control determines a jerk value that is approximately zero for a selected duration of time and the control receives vehicle data indicating that the transmission of the vehicle was in ‘Park’ for the selected duration of time.