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 predicting safety metrics associated with near-miss conditions for a vehicle, such as an autonomous vehicle, are discussed herein. For instance, a training system identifies an object in an environment and determines a trajectory for the object. The training system may receive a trajectory for a vehicle and associate the trajectory for the object and the trajectory for the vehicle with an event involving the object and the vehicle. In examples, the training system determines a parameter associated with motion of the vehicle as indicated by the trajectory of the vehicle relative to the trajectory of the object, and the event. Then, the training system may determine a safety metric associated with the event that indicates whether the vehicle came within a threshold of a collision with the object during a time period associated with the event.

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: 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: The present disclosure pertains to self-piloted, electric vertical takeoff and landing (VTOL) aircraft that are safe, low-noise, and cost-effective to operate for cargo-carrying and passenger-carrying applications over relatively long ranges. A VTOL aircraft has at least one wing that is rotatable relative to a fuselage of the VTOL aircraft for transitioning the VTOL aircraft between a hover configuration and a forward-flight configuration. Rotation of the wing may be passively controlled using aerodynamic forces, thereby obviating the need of using an actuator for actively controlling the rotation.

Abstract: The present disclosure pertains to self-piloted, electric vertical takeoff and landing (VTOL) aircraft that are safe, low-noise, and cost-effective to operate for cargo-carrying and passenger-carrying applications over relatively long ranges. A VTOL aircraft has a tandem-wing configuration with one or more propellers mounted on each wing to provide propeller redundancy, allowing sufficient propulsion and control to be maintained in the event of a failure of any of the propellers or other flight control devices. The arrangement also allows the propellers to be electrically-powered, yet capable of providing sufficient thrust with a relatively low blade speed, which helps to reduce noise. In addition, each wing is designed to tilt, thereby rotating the propellers, as the aircraft transitions between forward flight and hover flight. While in the hover flight, the propellers may be offset from vertical so that horizontal thrust components of the propellers may be used to provide efficient yaw control.

Abstract: The present disclosure pertains to self-piloted, electric vertical takeoff and landing (VTOL) aircraft that are safe, low-noise, and cost-effective to operate for cargo-carrying and passenger-carrying applications over relatively long ranges. A VTOL aircraft has a tandem-wing configuration with one or more propellers mounted on each wing to provide propeller redundancy, allowing sufficient propulsion and control to be maintained in the event of a failure of any of the propellers or other flight control devices. The arrangement also allows the propellers to be electrically-powered, yet capable of providing sufficient thrust with a relatively low blade speed, which helps to reduce noise. In addition, the aircraft is aerodynamically designed for efficient flight dynamics with redundant controls for yaw, pitch, and roll.

Abstract: A vertical takeoff and landing aircraft includes rotors that provide vertical and horizontal thrust. During forward motion, the vertical lift system is inactive. A lift fan mechanism positions the fan blades of the aircraft in a collapsed configuration when the vertical lift system is inactive and positions the fan blades of the aircraft in a deployed configuration when the vertical lift system is active.