Flight trajectory prediction system and flight trajectory-borne automated delay risk transfer system and corresponding method thereof

An automated flight trajectory prediction and flight trajectory-borne automated delay risk-transfer system based on a recognizable nature of flight patterns related to airspace risks for risk sharing of a variable number of risk-exposed units by pooling resources of the risk-exposed units and by providing the risk-transfer system as a self-sufficient operatable risk-transfer system based on the pooled resources for the risk-exposed units by a resource-pooling system associated with the risk-transfer system, wherein the risk-exposed units are connected to the risk-transfer system by a plurality of payment-transfer devices configured to receive and store payments from the risk-exposed units for the pooling of their risks and resources, and wherein an automated transfer of risk exposure associated with the risk-exposed units is provided by the risk-transfer system, the risk-transfer system comprising:

• a monitoring device implemented by processing circuitry and configured to capture or measure air data parameters of aircraft controllers and/or ground-based flight controllers of airports or flight control systems;
• a core engine implemented by the processing circuitry and linked to the aircraft controllers and/or the ground-based flight controllers via a communication network, the core engine including a filter device configured to filter the monitored air data parameters for detection of flight indicators indicating predicted or actual flight time parameters assigned to a specific flight trajectory of the aircraft;
• and
• a trigger device implemented by the processing circuitry and configured to dynamically trigger on the data flow pathway via the communication network, the trigger device comprising a flight trigger to trigger and filter predicted flight trajectories generated by the core engine based on the measured air data parameters and flight indicators associated with the generated predicted flight trajectories, wherein the processing circuitry is configured to dynamically generate a 3D grid network table representing digitized airspace, where each grid point is a location of weather measure parameters, and generate cubes around the grid points, so an entire airspace is represented by a dynamically generated set of cubes, wherein each cube is defined by its centroid, the original grid point, and associated weather measuring parameters remaining homogeneous within the generated cube during a predefined period of time, wherein the core engine is further configured to align generated raw trajectories to the set of cube centroids as fixed 3D positions independent of trajectory data, form trajectories are generated as 4D joint cubes, each cube is a segment that is associated with spatio-temporal attributes and with the therein located weather measuring parameters, wherein a predicted flight trajectory of the predicted flight trajectories is generated as a time-ordered, dynamical set of states, wherein, the core engine by using machine learning, predicts and generates the flight trajectories, the machine learning being applied and trained based on predefined inference structures derived from historical measure data by applying a stochastic structure taking environmental uncertainties into account, wherein the stochastic structure is based on a Hidden Markov Model (HMM) structure, wherein the processing circuitry is configured to generate measure parameters from an excessive set of weather parameters during processing of the risk-transfer system by solely using a dynamically monitored real trajectory dataset with pertaining weather measuring parameters, and wherein in response to a triggering of an exceeding of the defined time-delay threshold value, operational parameters of the triggered flight trajectory of the aircraft comprising at least flight delay parameters and flight identification are captured and stored to a table element of a selectable trigger-table assigned to the flight identifier of the aircraft, wherein
• for each triggered occurrence of a time delay associated with a specific flight trajectory, the core engine is configured to set a corresponding trigger-flag to all risk-exposed units assignable to the specific flight trajectory, and a parametric transfer of payments is allocated to each trigger-flag,
• the allocation of the parametric transfer of payments to the corresponding trigger-flag is automatically activated by the risk-transfer system for a dynamically scalable loss covering of the risk-exposed units with a definable upper coverage limit, the payments being automatically scaled based on a likelihood of the risk exposure of the specific flight trajectory, and
• the risk-transfer system is configured to check and monitor the risk accumulation and determine the payment dynamically based on the total risk accumulated and based on defined travel parameters, a loss associated with the triggered time delay being distinctly covered by the risk-transfer system based on the respective trigger-flag and based on the received and stored payment parameters from the pooled risk-exposed units by the parametric payment transfer from the risk-transfer system to the corresponding risk-exposed units by the payment-transfer devices operated or steered by a dynamically generated output signal of the risk-transfer system.