A device and a method for controlling flight of an unmanned aerial vehicle are provided. To efficiently acquire environment information required to generate a navigation route of a vehicle, the device include a receiver that receives departure point information and destination information of a vehicle. A controller that generates a flight route corresponding to a travel route from a departure point to a destination of the vehicle based on at least one of a sensing range of a sensor mounted on the unmanned aerial vehicle, a flight available distance based on a fuel amount, and a communication available distance of a communication device mounted on the unmanned aerial vehicle, and operates the unmanned aerial vehicle to follow the generated flight route.

Disclosed is a method for determining an atmospheric radiative forcing difference by optimising or preventing contrail formation caused by an aircraft. The method comprises receiving one or more weather parameters to determine contrail forecast data; receiving one or more flight parameters associated with aircraft to determine flight data; determining tentative atmospheric radiative forcing quantity, along tentative flight trajectory, based on contrail forecast data and flight data; altering one or more flight parameters to determine optimised flight trajectory having optimum atmospheric radiative forcing quantity, wherein optimised flight trajectory is validated using imagery data; and determining an atmospheric radiative forcing difference to evaluate offset value for at least one forcing parameter associated with atmospheric radiative forcing difference. Disclosed also is an apparatus for determining atmospheric radiative forcing caused by aircraft by optimising or preventing contrail formation. Further, disclosed is computer program product to carry out aforementioned method.

A system including a processor and memory may provide for automatically activating or deactivating a feature of a fleet vehicle. For example, one or more fleet vehicles may include one or more of a global-positioning system, a speed governor, electronically-controlled brakes, an electronically-controlled accelerator, a speed limiter, or an on-board computer with a processor and memory. One or more features may be activated by a local or remote computing device or system. For example, a system may determine one or more recommended routes between two or more locations. The system may track a fleet vehicle’s progress along a route, and activate a feature of the fleet vehicle based on the fleet vehicle following or not following the recommended route. For example, the system may cause activation of a speed limiter on the fleet vehicle, disable the fleet vehicle, and/or activate or deactivate autonomous features of the fleet vehicle.

A system and method of generating optimised aircraft flight trajectories on Flight Management Systems with limited computational power that takes into account developing operational conditions, air traffic constraints and aircraft performance in a timely manner on the flight management system that can allow tactical flight plan changes to be incorporated without unduly introducing operational or financial penalties to the operator. An example method involves parameterisation of optimal trajectories as functions of operational parameters thereby allowing computational systems to use such computed functions in the air to determine the optimal trajectory or flight profile required for the specific operating conditions quickly and accurately.

Air traffic control systems and methods include communicating with passenger drones via one or more cell towers associated with the one or more wireless networks, wherein the passenger drones each include hardware and antennas adapted to communicate to the one or more cell towers, and wherein each passenger drone has a unique identifier in the air traffic control system; obtaining data associated with flight of each of the passenger drones based on the communicating; and managing the flight of each of the passenger drones based on the obtained data and performance of one or more functions associated with air traffic control, wherein each passenger drone is configured to constrain flight based on coverage of the one or more cell towers such that each passenger drone maintains communication on the one or more wireless networks.

The disclosure generally pertains to minimizing battery power consumption while employing local wireless communication to activate an operation of an autonomous vehicle. In an example implementation, a vehicle controller of an autonomous vehicle transitions to a powered-down state after the autonomous vehicle is parked at a parking spot that lacks cellular communication coverage. The vehicle controller may transition to a powered-up state at a scheduled time to execute an autonomous operation based on a directive stored in a cloud-based device. In no directive has been stored, the vehicle controller wakes up periodically in a partially powered-up state and transmits a query in a local wireless communications format to the cloud-based device to check for a directive. If no directive is present, the vehicle controller transitions back to the powered-down state. If a directive is present, the vehicle controller transitions to a fully powered-up state to execute the autonomous operation.

A method includes defining a two-dimensional geographic region by two-dimensional geographic coordinates to define the bounds of the region, converting each of the two-dimensional coordinates to three dimensional coordinates by way of a lookup stored in a computer readable medium, generating a three-dimensional grid of points, each spaced in an arrangement to encompass coverage of a predetermined ground area, and applying heuristics for a shortest path planning, relative to the three-dimensional grid of points.

A method and system for optimizing drone delivery efficiency. The method includes determining an optimal intermediate location for a UAV based on historical payload delivery data related to a payload carried by the UAV, wherein the distance between the optimal intermediate location and each of a group of potential recipient devices is less than a predetermined threshold; causing the UAV to navigate to the optimal intermediate location; sending, to each potential recipient device having a probability of requesting the payload carried by the UAV which exceeds a predetermined threshold, a notification indicating the payload carried by the unmanned aerial vehicle; receiving, from a first potential recipient device of the potential recipient devices, a request to deliver the payload; and causing the UAV to navigate from the optimal intermediate location to a location of the first potential recipient device when the request to deliver the payload is received.

Systems, devices, and methods including: at least one unmanned aerial vehicle (UAV); at least one battery pack comprising at least one battery; and at least one motor of the at least one UAV, where the at least one battery is configured to transfer energy to the at least one motor; where power from the at least one motor is configured to ascend the at least one UAV to a second altitude when the at least one battery is at or near capacity, and where the second altitude is higher than the first altitude; and where power from the at least one motor is configured to descend the at least one UAV to the first altitude after the Sun has set to conserve energy stored in the at least one battery.

A system and approach for a vehicle system. The vehicle system may include a vehicle, a propulsion device (e.g., a combustion engine or electric motor), and a controller. The propulsion device may at least partially power the vehicle. The controller may be in communication with the propulsion device and may control the propulsion device according to a target speed of the vehicle. The controller may include a model of energy balances of the vehicle and may use the model to estimate energy losses over a travel horizon of the vehicle. The controller may optimize a cost function over the travel horizon of the vehicle based at least in part on the estimated energy losses to set an actual speed for the vehicle. The estimated energy losses may include one or more of aerodynamic drag, vehicle friction, and conversion efficiency from the propulsion device.