Abstract: Illustrative examples are provided of a process and machine configured to provide innovative technical solutions for: deriving a predicted trajectory for a vehicle; controlling a trajectory for a vehicle; and for reducing congestion in an Air Traffic Management system, via: a processor executing an algorithm specially programmed for: generating a baseline lateral profile for a baseline trajectory; subsequently generating a baseline vertical profile for the baseline trajectory; subsequently forming the baseline trajectory by merging the vertical profile with the baseline lateral profile; and using at least one of: a performance element, or a configuration element, from the baseline trajectory for deriving the predicted trajectory. The predicted trajectory is sent for use by a Flight Management System and/or an Air Traffic Management System.

Abstract: A device includes a processor configured to obtain flight data of one or more aircraft of an aircraft type. The processor is configured to identify a first portion of the flight data as first phase flight data associated with a first phase of one or more flights of the one or more aircraft, and to apply a first aircraft performance model to the first phase flight data to determine first parameter values. The processor is configured to identify a second portion of the flight data as second phase flight data associated with a second phase of the one or more flights, and to apply the first aircraft performance model to the second phase flight data to determine second parameter values. The processor is configured to generate, based on the first parameter values and the second parameter values, a second aircraft performance model of a particular aircraft of the aircraft type.

Abstract: The present disclosure provides a system that includes an ingress module arranged to receive flight data comprising a descent rate value and an altitude value; a data store comprising descent rate threshold values of at least one aircraft model, the descent rate threshold values associated, in the data store, with pressure altitude values; a descent classification module that is operably coupled to the ingress module and the data store and adapted to compare the descent rate value with the descent rate threshold values; an alert module adapted to provide, in response to the descent classification module comparing the descent rate value that exceeds at least one of the descent rate threshold values, an alert signal to a graphic user interface that is operably coupled to the alert module.

Abstract: A device includes one or more processors configured to receive an indication that a geographical area is expected to be regulated during a particular time window. The one or more processors are also configured to perform a comparison of the geographical area to route segments of a filed flight plan of a flight of an aircraft. The one or more processors are further configured to, based on determining that a route segment of the filed flight plan traverses at least a portion of the geographical area during the particular time window, determine alternate flight plans that do not traverse the geographical area during the particular time window. The one or more processors are also configured to select one of the alternate flight plans that satisfies a selection criterion as an updated flight plan of the flight, and to send the updated flight plan to a second device.

Abstract: Apparatuses, methods, systems, and program products are disclosed for dynamic selection of an aeronautical data provider. An apparatus includes a processor and a memory that stores code executable by the processor to receive a first stream of real-time aeronautical data from a first aeronautical data provider, receive at least one second stream of real-time aeronautical data from at least one second aeronautical data provider simultaneously with the first stream, provide data from the first stream and the at least one second stream to a decision model for predicting which data has a higher accuracy, and switch using data from the first stream to data from one of the at least one second streams in response to the one of the at least one second streams having a higher predicted accuracy than the first stream.

Abstract: A method of flight data prediction for an aircraft includes receiving, at a device, arrival input data for a flight of the aircraft to an arrival airport. The arrival input data includes flight plans for a plurality of aircraft expected to arrive at or depart from the arrival airport during an arrival time range, predicted weather information for the arrival airport during the arrival time range, and facilities data for the arrival airport. The method includes generating, at the device based on the arrival input data, one or more arrival sets for the aircraft. Each arrival set comprising a predicted gate arrival time for the aircraft at an arrival gate using a particular runway and a probability associated with the aircraft using the particular runway. The method also includes generating, at the device, an output based on at least one of the one or more arrival sets.

Abstract: A device includes a memory, a network interface, and a processor. The memory is configured to store an aircraft performance model. The aircraft performance model is based on historical flight data of one or more aircraft. The aircraft performance model includes a recurrent neural network layer. The network interface is configured to receive real-time time-series flight data from a data bus of a first aircraft. The processor is configured to receive, via the network interface, the real-time time-series flight data. The processor is also configured to generate, based on the real-time time-series flight data and the aircraft performance model, one or more aircraft performance parameters. The processor is further configured to provide the aircraft performance parameters to a display device.

Abstract: A method may include receiving flight plan data representing a set of current flight plans and receiving surveillance data representing a set of current aircraft statuses. The method may further include generating merged data representing a set of flight portions that remain to be flown. The method may also include receiving operational context data representing airspace configurations, airport configurations, or a combination thereof, and receiving weather data. The method may include generating predicted flight traffic data by performing a simulation of flights over a duration of time, the simulation based at least partially on the merged data, the operational context data, and the weather data. The method may further include generating a user output based at least partially on the predicted flight traffic data.

Abstract: A device for flight data prediction includes a memory, a communication interface, and one or more processors. The memory is configured to store a departure airport map. The communication interface is configured to receive location data for a plurality of aircraft expected to arrive at or depart from a departure airport during a particular time range. The one or more processors are configured to predict, based on the location data and the departure airport map, a taxi duration or a fuel usage of a first aircraft of the plurality of aircraft. The one or more processors are also configured to generate an output based on the taxi duration or the fuel usage.

Abstract: A parking stand prediction system uses statistical analysis and historical data to provide an available parking stand for an aircraft at an arrival airport. The system receives real-time surveillance data relating to airlines, on-air flights, and airline and airport ground services. The surveillance data is sorted or pre-filtered according to airport. The system also receives airport map or layout data. Parking stand identification logic is applied to the surveillance data, airport map data, and historical surveillance data. Portions of this data are stored in a parking stand database which is continuously updated with current surveillance and parking stand availability data. A user inputs parking stand search parameter data into the system and receives a parking stand prediction for the aircraft of interest at an arrival airport.

Abstract: A method may include receiving flight plan data representing a set of current flight plans and receiving surveillance data representing a set of current aircraft statuses. The method may further include generating merged data representing a set of flight portions that remain to be flown. The method may also include receiving operational context data representing airspace configurations, airport configurations, or a combination thereof, and receiving weather data. The method may include generating predicted flight traffic data by performing a simulation of flights over a duration of time, the simulation based at least partially on the merged data, the operational context data, and the weather data. The method may further include generating a user output based at least partially on the predicted flight traffic data.

Abstract: A method includes generating an initial flight context that includes a set of unresolved flight constraints. The method further includes generating a decision tree based on the initial flight context. The decision tree includes a plurality of flight contexts corresponding to leaves of the decision tree. The method also includes expanding the decision tree according to a greedy best-first strategy that selects a flight context of the decision tree for expansion based on a fitness value assigned to the flight context. The method includes selecting, as a piloting strategy, a flight context of the decision tree that includes a sequence of actions to resolve each of the unresolved flight constraints. The method further includes flying an aircraft according to the piloting strategy.

Abstract: A computer-implemented method and a system for setting up an air traffic management (ATM) simulator in an airport are described herein. The method performs the steps of receiving a set of undetermined parameters and rules (112) for configuring an ATM simulator (114) in an airport; retrieving a historical data set of variables associated with trajectory and aircraft states in an airspace region during a time interval; statistically analyzing the historical data set for modelling the airspace region and the airport, and identifying relationships between variables of the historical data set during the time interval relating to at least one undetermined parameter or rule (112); determining a parameter value (160) or rule (140,170) for configuring the ATM simulator corresponding with the at least one identified relationship.

Abstract: A method includes generating an initial flight context that includes a set of unresolved flight constraints. The method further includes generating a decision tree based on the initial flight context. The decision tree includes a plurality of flight contexts corresponding to leaves of the decision tree. The method also includes expanding the decision tree according to a greedy best-first strategy that selects a flight context of the decision tree for expansion based on a fitness value assigned to the flight context. The method includes selecting, as a piloting strategy, a flight context of the decision tree that includes a sequence of actions to resolve each of the unresolved flight constraints. The method further includes flying an aircraft according to the piloting strategy.

Abstract: The present invention provides a computer-implemented method of producing a description of aircraft intent expressed using a formal language. The description may be used to predict aircraft trajectory, for example by air traffic management. Rules are used in association with information provided to generate a set of instructions describing both the aerodynamic configuration of the aircraft and the motion of the aircraft. These instructions are checked to ensure that they describe unambiguously the aircraft's trajectory. The instructions are then expressed using a formal language.

Abstract: The present invention provides a system and method of producing a description of the flight intent of an aircraft expressed using a formal language. The description may be used to generate a predicted aircraft trajectory, for example by air traffic management. Rules are used in association with information provided to express the flight intent of the aircraft in a formal language. The flight intent describes a flight in terms of flight segments, and provides information of the path to be flown and how it is to be flown. The flight intent does not necessarily define unambiguously the aerodynamic configuration of the aircraft and the motion of the aircraft during the flight. The flight intent is used alongside other information to generate the aircraft intent that does describe unambiguously the aircraft's trajectory.

Abstract: The present invention provides a computer-implemented method of generating an aircraft intent description expressed in a formal language that provides an unambiguous four-dimensional description of an aircraft's intended motion and configuration during a period of flight. A flight intent description is parsed to provide instances of flight intent that span a flight segment, the flight segments together spanning the period of flight. The parsed flight intent is enriched with objectives and constraints according to user preferences, operational context and aircraft performance. The resulting enriched flight intent is converted into a parametric aircraft intent description by ensuring that each flight segment closes all associated degrees of freedom of motion and of configuration of the aircraft. At least some instances of aircraft intent contain a parameter range, and the method further comprises optimizing the parametric aircraft intent by determining an optimal value for the parameter of each parameter range.

Abstract: The present invention provides a computer-implemented method of producing a description of aircraft intent expressed using a formal language. The description may be used to predict aircraft trajectory, for example by air traffic management. Rules are used in association with information provided to generate a set of instructions describing both the aerodynamic configuration of the aircraft and the motion of the aircraft. These instructions are checked to ensure that they describe unambiguously the aircraft's trajectory. The instructions are then expressed using a formal language.

Abstract: The present invention provides a computer-implemented method of producing a description of aircraft intent expressed using a formal language. The description may be used to predict aircraft trajectory, for example by air traffic management. Rules are used in association with information provided to generate a set of instructions describing both the aerodynamic configuration of the aircraft and the motion of the aircraft. These instructions are checked to ensure that they describe unambiguously the aircraft's trajectory. The instructions are then expressed using a formal language.

Abstract: The present disclosure provides a computer-implemented method of generating a description of aircraft intent expressed in a formal language that provides an unambiguous description of an aircraft's intended motion and configuration during a period of flight. A description of flight intent is parsed to provide instances of flight intent, each instance of flight intent spanning a flight segment. For each flight segment, an associated flight segment description is generated that comprises one or more instances of flight intent that describe the aircraft's motion in at least one degree of freedom of motion. One or more instances of flight intent are added to flight segments to close all degrees of freedom of motion. The flight segment descriptions are collated thereby providing a description of aircraft intent for the period of flight expressed in a formal language.