A teleoperations system may be used to selectively override conditions detected by an autonomous vehicle to enable the autonomous vehicle to effectively ignore detected conditions that are identified as false positives by the teleoperations system. Furthermore, a teleoperations system may be used to generate commands that an autonomous vehicle validates prior to executing to confirm that the commands do not violate any vehicle constraints for the autonomous vehicle. Still further, an autonomous vehicle may be capable of dynamically varying the video quality of one or more camera feeds that are streamed to a teleoperations system over a bandwidth-constrained wireless network based upon a current context of the autonomous vehicle.

A method is provided. An unmanned aerial vehicle (UAV) is operated. A position of the UAV is determined while in flight, and a nonce is generated. A Merkel root is generated based at least in part on a timestamp and the position of the UAV. A current block is calculated based at least in part on a previous block, the Merkel root, and the nonce, and the current block, the timestamp, the nonce, the prior block, and the position of the UAV are transmitted.

An on-board computing system for a vehicle is configured to generate and selectively present a set of autonomous-switching directions within a navigation user interface for the operator of the vehicle. The autonomous-switching directions can inform the operator regarding changes to the vehicle's mode of autonomous operation. The on-board computing system can generate the set of autonomy-switching directions based on the vehicle's route and other information associated with the route, such as autonomous operation permissions (AOPs) for route segments that comprise the route. The on-board computing device can selectively present the autonomy-switching directions based on locations associated with anticipated changes in autonomous operations determined for the route of the vehicle, the vehicle's location, and the vehicle's speed. In addition, the on-board computing device is further configured to present audio alerts associated with the autonomy-switching directions to the operator of the vehicle.

The present teaching relates to method, system, and medium, for generating an augmented alert in a hybrid vehicle. First information indicating an upcoming switch in an operating mode of the vehicle is received, which specifies a set of tasks, arranged in an order, to be completed by a driver in the vehicle to achieve the upcoming switch, and a task duration for each of the set of tasks by which the task is to be completed. A current state of the driver is obtained and used to determine a set of warnings to alert the driver to perform the set of tasks. Each warning corresponds to a task in the set of tasks and is created based on the current state of the driver. A warning schedule is generated based on the set of warnings in the order of the set of tasks and transmitted so that warnings in the warning schedule are delivered to the driver.

A vehicle includes a detection system configured to acquire data regarding operation of the vehicle, and a robotic driving device configured to provide robotic control of the vehicle. The vehicle also includes a control system configured to determine whether the robotic driving device is activated, such that the vehicle is in robotic driving mode; receive a request by a prospective operator of the vehicle to deactivate the robotic driving device to initiate a manual driving mode; determine whether the prospective operator is impaired based on the data; and selectively grant or refuse the request based on the determination.

A control device of a vehicle comprises: a driving plan generating part 90 configured to generate a driving plan in automated driving of the host vehicle; a package extracting part 91 configured to extract driving assistance packages packaging permissions for a plurality of driving assistance operations based on at least one of the surrounding environment information, the vehicle information, and the driver information; a package proposing part 92 configured to propose driving assistance packages to the driver of the host vehicle based on the driving assistance packages extracted by the package extracting part and the driving plan; and an automated driving executing part 93 configured to perform driving assistance operations permitted in a driving assistance package proposed by the package proposing part and approved by the driver of the host vehicle.

Disclosed are systems, methods and devices for centralized control of autonomous vehicles. In some embodiments, a system and method allow an autonomous control system on-board an autonomous vehicle to pass control of the autonomous vehicle to an offboard panel of experts upon encountering an anomaly. In some embodiments, a system and method allow a regulatory entity to proactively distribute rules and requirements to autonomous vehicles while operating within a regulated space.

An automated aircraft recovery system is disclosed. In various embodiments, the system includes an interface configured to receive sensor data; and a control mechanism configured to: perform automatically a recovery action that is determined based at least in part on the sensor data. In various embodiments, the control mechanism may determine an expected state of an aircraft, determine whether a state of the aircraft matches the expected state, and in the event the state of the aircraft does not match the expected state, perform the recovery action.

Vehicles may have the capability to navigate according to various levels of autonomous capabilities, the vehicle having a different set of autonomous competencies at each level. In certain situations, the vehicle may shift from one level of autonomous capability to another. The shift may require more or less driving responsibility from a human operator. Sensors inside the vehicle collect human operator parameters to determine an alertness level of the human operator. An alertness level is determined based on the human operator parameters and other data including historical data or human operator-specific data. Notifications are presented to the user based on the determined alertness level that are more or less intrusive based on the alertness level of the human operator and on the urgency of an impending change to autonomous capabilities. Notifications may be tailored to specific human operators based on human operator preference and historical performance.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.