Methods, systems, and apparatus, including computer programs encoded on computer storage media, for unmanned aerial vehicle authorization and geofence envelope determination. One of the methods includes determining, by an electronic system in an Unmanned Aerial Vehicle (UAV), an estimated fuel remaining in the UAV. An estimated fuel consumption of the UAV is determined. Estimated information associated with wind affecting the UAV is determined using information obtained from sensors included in the UAV. Estimated flights times remaining for a current path, and one or more alternative flight paths, are determined using the determined estimated fuel remaining, determined estimated fuel consumption, determined information associated wind, and information describing each flight path. In response to the electronic system determining that the estimated fuel remaining, after completion of the current flight path, would be below a first threshold, an alternative flight path is selected.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for unmanned aerial vehicle authorization and geofence envelope determination. One of the methods includes determining, by an electronic system in an Unmanned Aerial Vehicle (UAV), an estimated fuel remaining in the UAV. An estimated fuel consumption of the UAV is determined. Estimated information associated with wind affecting the UAV is determined using information obtained from sensors included in the UAV. Estimated flights times remaining for a current path, and one or more alternative flight paths, are determined using the determined estimated fuel remaining, determined estimated fuel consumption, determined information associated wind, and information describing each flight path. In response to the electronic system determining that the estimated fuel remaining, after completion of the current flight path, would be below a first threshold, an alternative flight path is selected.

An aircraft mission calculation system is configured to calculate an environmental benefit index. The system includes an aircraft trajectory calculation engine, able to calculate at least one potential mission trajectory between a geographic point of origin and a geographic point of destination. The aircraft trajectory calculation engine comprises an environmental benefit index calculation module, able to activate the calculation engine. The environmental benefit index calculation module is able to determine an environmental benefit index (GI) of the potential trajectory from the first amount of carbon dioxide (Q1(TR1)) produced on a first reference trajectory defining a fastest mission, the second amount of carbon dioxide produced on a second reference trajectory (Q2(TR2)), defining a mission minimizing the amount of carbon dioxide produced, and the potential amount of carbon dioxide produced on the potential trajectory.

An aerial vehicle includes a communication unit configured to receive a wireless signal from a geo-fencing device, and a flight controller configured to generate one or more control signals that cause the aerial vehicle to operate in accordance with a set of flight regulations generated based on the wireless signal. The geo-fencing device is configured not for landing of the aerial vehicle. The set of flight regulations includes rules for controlling at least one of the aerial vehicle, a carrier carried by the aerial vehicle, or a payload of the aerial vehicle.

An aircraft data collection system comprising a set of removable data collection units and a computer system. The set of removable data collection units is loadable into a compartment in a commercial aircraft. The computer system is configured to control operation of the set of removable data collection units to collect data during a flight of the commercial aircraft on a flight path. A third party can use a smart phone or other electronic device to control the data collection unit during a commercial aircraft flight. The third party is different from the airline operating the commercial aircraft.

Systems, computer readable medium and methods for navigation correction for excessive wind in an autonomous drone are disclosed. Excessive winds can be a particular problem for small autonomous drones as safety and retrieval of the autonomous drones is important and the autonomous drones often have limited thrust and batteries. Autonomous drones are disclosed that detect and correct flight plans when excessive winds are detected. The autonomous drone determines based on the severity of the excessive winds whether to return to a home position which is typically a position of a user of the autonomous drone or to land in place. If the excessive winds subside, then the autonomous drone returns to its original flight plan at the point where the autonomous drone was blown off course by the excessive winds. The autonomous drone detects excessive winds either directly by sensor data or inferentially by unanticipated movement of the autonomous drone.

A method of management of a flight of an aircraft is provided. The method includes receiving a data stream from an automatic dependent surveillance broadcast (ADS-B) receiver during the flight, and the data stream includes an ADS-B message, a geographic position of the aircraft, and attitude and heading reference system (AHRS) data. The method includes accessing data that indicates a weight of the aircraft, identifying a force event experienced by the aircraft based on the geographic position, the AHRS data, and the weight of the aircraft, and classifying the force event by level of the force event, and by type of the force event as a turbulence event or a non-turbulence event. And the method includes outputting a report that indicates the force event as classified, at least when the force event is classified as a turbulence event.

A computer implemented method and system of instructing one or more weather drones. The method includes analysing a first data set comprising flight path data indicative of the flight paths of one or more aircrafts over a predefined time period. The method includes identifying, based on said analysis, at least one geographical region which is not intercepted by or adjacent to, any of the flight paths of the one or more aircrafts. The method includes instructing one or more weather drones to fly to the at least one geographical region.

A vehicle management system includes a missile avoidance system that generates command for controlling at least one function of a vehicle. The missile avoidance system includes a maneuver control unit and a missile avoidance management unit. The maneuver control unit includes at least two control models. Each of the at least two control models generates the command for controlling the at least one function of the vehicle, and each of the at least two control models can be selectively put in an active state or an inactive state. The missile avoidance management unit selects one of the at least two control models and putts it in the active state. The maneuver control unit outputs the command for controlling the at least one function of the vehicle provided by the control model that is in the active state.

An aircraft having an augmented reality flight control system integrated with and operable from the pilot seat and an associated pilot headgear unit, wherein the flight control system is supplemented by flight-assisting artificial intelligence and geo-location systems. Embodiments include an augmented reality flight control system incorporating real-world objects with virtual elements to provide relevant data to a pilot during aircraft flight. A translucent substrate is disposed in the pilot's field of view such that the pilot can see therethrough, and observe virtual elements displayed on the substrate. The system includes a headgear that is worn by the pilot. A flight assistance module is configured to receive data related to the aircraft and provide predictive assistance to the pilot during flight based on the received data based in part on a pilot profile having preferences related to the pilot.