A vehicle control function, UCF, and a method for the UCF that receives from a traffic management function, USS/UTM, a first positioning request message comprising a vehicle system, UAV, identity and coordinates of interest, determines with the USS/UTM a positioning configuration for the coordinates of interest, sends to a Location Server a second positioning request message comprising the UAV identity, UAV positioning configuration, receives positioning information for the UAV from the Location Server, and sends to the USS/UTM a positioning report message comprising the UAV identity and the positioning information.

The preferred embodiments pertain to a method for controlling a flight movement of an aerial vehicle that includes acquiring first image data by means of a first camera device that is arranged on an aerial vehicle and configured for monitoring an environment of the aerial vehicle while flying, wherein the first image data are indicative of a first sequence of first camera images. The method also includes acquiring second image data by means of a second camera device that is arranged on an aerial vehicle and configured for monitoring the environment of the aerial vehicle while flying, wherein the second image data are indicative of a second sequence of second camera images. The processing includes determining object parameters for a position of a flight obstacle in the environment of the aerial vehicle if the first image analysis predicts the flight obstacle in the at least one camera measurement image and the second image analysis likewise identifies the flight obstacle in the at least one camera measurement image. An aerial vehicle is furthermore disclosed.

A method to validate a flight plan for an aircraft includes receiving aviation data, determining a flight plan based on the aviation data; determining a set of flight parameters for the flight plan, receiving terrain data, and performing a safety validation of the flight plan, wherein the safety validation comprises: comparing the set of flight parameters with the terrain data; and determining, based on the comparison, whether the flight plan satisfies predetermined flight criteria, and in the event of a determination that the flight plan does not satisfy the predetermined flight criteria, displaying a first notification indicative of the determination.

A system may include a user interface and a processor. The processor may be configured to (a) pre-arm multiple actions according to a conditional timeline and any associated trigger events, and (b) output commands to cause the multiple actions to be completed at times consistent with the conditional timeline and any associated trigger events.

Systems and methods for operating done flights over public roadways are disclosed herein. An example method includes transmitting, by a first drone, a drone safety message, the drone safety message being received by a vehicle or a roadside infrastructure device located along a first planned flight path, determining an emergency condition for the first done, transmitting a warning message over a vehicle-to-everything communication that indicates that the first drone is experiencing the emergency condition. A connected vehicle or mobile device receives the warning message over the vehicle-to-everything communication. Determining drone operating evidence as the first drone traverses along the first planned flight path, and storing the drone operating evidence in a distributed ledger.

Systems and methods for service drone landing zone operations are disclosed herein. An example method includes determining location-specific information for a location, the location-specific information including at least images of the location from at least one of a vehicle or a mobile device at the location, determining a landing area for a drone at the location using the location-specific information. receiving localizing signals from at least one of the vehicle or the mobile device as the drone approaches the location, and causing the drone to land in the landing area using the localizing signals.

Methods, apparatus, systems and articles of manufacture are disclosed for collaborative aircraft checklists. An example apparatus includes at least one memory including instructions and at least one processor to execute the instructions to at least launch actions of a checklist on a user interface of a first client device, the actions including a first action to be completed in sequence to execute a flight stage of a flight project, the flight project to be accessed by the first, second, and third client devices, in response to an update of the first action by the first client device, generate a first message including the update, in response to the second client device validating the update, distribute a second message including the update to the third client device to update the checklist on the third client device, and cause the aircraft to execute the flight stage based on the update.

A method, apparatus, and system for controlling an aircraft. A target state for the aircraft is identified. A current mission state is determined for the aircraft. A sequence of actions is selected from a pool of potential actions to reach the target state from the current mission state for the aircraft. The sequence of actions is selected based on the current mission state. The actions in the sequence of actions for which preconditions for the actions that have been met are performed. The actions are performed in an order defined by the sequence of actions.

Human-machine interface for required time of arrival (RTA) constraint negotiation. Embodiments present critical RTA information and results of associated data calculations to the pilot in a concise and informative manner using a dialogue box with intuitive graphical displays. Embodiments present critical RTA information to assist a pilot in negotiating the RTA constraint with air traffic controllers, accepting the clearance, and having confidence in the system that it will achieve the defined RTA constraint.

To enable high-speed autonomous flight of a flight object. A three-dimensional real-time observation result is generated on the basis of self-position estimation information and three-dimensional distance measurement information. A prior map corresponding to a three-dimensional real-time observation result is acquired. The three-dimensional real-time observation result and the prior map are aligned. After the alignment, the three-dimensional real-time observation result is expanded on the basis of the prior map. A flight route is set on the basis of the three-dimensional real-time observation result having been expanded. In the flight object such as a drone, a somewhat long flight route can be accurately calculated at a time in a global behavior plan, which enables high-speed autonomous flight of the flight object.