55 results about "Air traffic controller" patented technology

The invention, which relates to the technical field of aviation training and simulation, discloses a virtual low-altitude air traffic controller AI model training system comprising a data acquisition and preprocessing module, an AI core model module and a communication and interaction module. The data acquisition and preprocessing module is used for collecting data from a simulated low-altitude radar, low-altitude weather, low-altitude geographic information and a low-altitude flight plan data source, and performing cleaning, denoising, format conversion and integration processing on the data to generate preprocessed data used by the AI core model. According to the virtual low-altitude air traffic controller AI model training system provided by the invention, the effect and quality of low-altitude flight training of a pilot are remarkably improved, and the pilot can perform a large amount of practical operation and emergency treatment training in a safe environment by simulating various real low-altitude flight scenes and complex conditions; the coping ability of the system to low-altitude flight rules, control programs and various complex conditions is enhanced, the training period is shortened, and the training cost is reduced.

The invention discloses an aircraft wake flow real-time monitoring method based on laser radars, and the method comprises the steps: collecting the real-time wake flow data in a five-side approaching stage of a front aircraft through a plurality of laser radar devices, and determining the space coordinates and three-dimensional contour of the edge of a wake flow region through an edge detection algorithm; according to the coordinates of the left and right edges and the upper and lower edges of the wake flow area, the front and tail flow areas are displayed in real time; the method comprises the following steps: intercepting a two-dimensional cross section of a front aircraft tail flow area at a rear aircraft real-time flight height, calculating a rolling instability index generated by the two-dimensional cross section area to a rear aircraft wing, determining a wake flow minimum safety interval according to a preset rolling instability index threshold value, and displaying the wake flow minimum safety interval on an air traffic control system radar interface in real time, thereby realizing the purpose that in a five-side approach stage of an aircraft, the flight speed of the aircraft is increased. The front aircraft wake flow area and the rear aircraft wake flow area are displayed in real time, and the minimum safety interval of the front aircraft and the rear aircraft considering the real-time flight height is considered, so that an air traffic controller can clearly know the real-time state and the potential risk of the aircraft wake flow, and the wake flow monitoring accuracy and the flight safety are improved.

The invention discloses an aircraft simulation data generation and situation deduction method based on a flight plan, and the method comprises the steps: firstly constructing an analysis model which is used for receiving a flight plan generated by a front end and carrying out the preprocessing, and then carrying out the aircraft situation deduction based on the information of each flight segment. The method comprises the following steps: generating an independent aircraft class, attaching different state attributes to the aircraft class, establishing an aircraft climbing and descending model, and continuously updating the state attributes of the aircraft class according to real-time deduction data. And finally, designing cyclic output of the aircraft simulation situation data once every 4 seconds. The method aims at providing assistance for work of a controller and improving situation awareness and real-time state monitoring of the aircraft in the operation stage. Meanwhile, an aircraft driver is assisted to make a decision autonomously, and control over the aircraft by the driver and information interaction between the driver and a controller are enhanced; and enough reaction time can be reserved for a driver and a controller at the emergency moment.

The invention provides a method for systematically monitoring aircraft pilot and air traffic control (ATC) radio communications to detect predefined aviation-specific keywords indicative of operational conditions affecting flight safety or efficiency, such as turbulence, icing, or visibility constraints. Detected keywords and semantic equivalents from voice transmissions are transformed into structured data formats. These structured data are correlated with Automatic Dependent Surveillance-Broadcast (ADS-B) data, including precise aircraft position, altitude, heading, and speed. Leveraging this integrated data, the system generates automated, quantitative visualizations, such as condition-specific heatmaps or other graphical representations, illustrating spatial distributions of reported in-flight phenomena like turbulence, icing, or hazardous conditions. These visualizations enable air traffic controllers, pilots, and aviation stakeholders to rapidly assess and disseminate real-time observations and historical patterns of flight hazards, thereby significantly enhancing situational awareness, operational safety, and decision-making effectiveness without manual input or subjective interpretation, improving overall aviation operational efficiency and safety.

The invention relates to the technical field of civil aviation air traffic management, and discloses a pre-post air traffic controller fatigue objective prediction method and system, and the method comprises the steps: presenting a mental movement alertness task to a user; the method comprises the following steps: in the process of executing a mental movement alertness task by a user, acquiring eye image data containing the user through image acquisition equipment, and recording the response time and error rate of the user to the mental movement alertness task; calculating to obtain an eyelid closure parameter based on the eye image data; calculating a reaction time parameter and an error rate parameter based on the reaction time and the error rate; and determining a comprehensive fatigue value of the user based on a weighted combination of the eyelid closure parameter, the response time parameter and the error rate parameter. The invention aims to provide an objective fatigue prediction method and system for a pre-post air traffic controller so as to overcome the defects that a traditional subjective scale is insufficient in reliability, a standard objective test consumes too long time and is not suitable for pre-class rapid screening.

The embodiment of the invention discloses a training system and method combining a large model and an eVTOL simulation cabin. The system comprises an air traffic control voice recognition module which carries out fine tuning on a general voice model and obtains a pilot instruction based on the fine-tuned model and an intelligent error correction algorithm; the large model intelligent control module is used for finely adjusting the base large model and processing the virtual scene information and the pilot instruction based on the finely-adjusted model to obtain a control instruction; the control voice synthesis module is used for performing fine tuning on the general text-to-voice large model and obtaining voice data based on the fine-tuned model; and the training system management platform is used for realizing man-machine interaction between the training system and the pilot and the controller. According to the invention, a virtual controller system is constructed based on large model fine tuning, the problems of large workload of controllers, lack of controllers during pilot training and the like can be solved, and the efficiency, quality and precision of pilot training can be effectively improved.

Generally discussed herein are systems, apparatuses, and methods for generating a Controller Pilot Data Link Communication (CPDLC) digital message. This can include: a digital interface system configured to receive input from one of a pilot or an air traffic controller. The digital interface system can optionally include: a digital message generator configured to receive the input and decode an intent of the input within an aviation context. The digital message generator can be configured to determine a sample response based upon the intent. This can further include: a compliance system configured to review the sample response for a potential error. If cleared by the review of the compliance system, the digital interface system issues the sample response as the CPDLC digital message.

A system and method for implementing one or more real-time flight operations quality assurance (RTS-FOQA) systems and protocols is disclosed. RTS-FOQA systems assist pilots and other personnel in managing hazards and risks to protect the safety of passengers, pilots, flight attendants, crew, as well as people on the ground. The system is configured to capture voice data from the cockpit, recognize words spoken by the pilots, air traffic controllers (ATC), and other personnel; convert the recognized words into text; compare the text derived from the words spoken by the pilots, ATC, and other personnel to a standard operational procedure (SOP) sequence, wherein the sequence comprises a plurality of SOP operational steps; identify at least one of a plurality of flight operations executed by the pilots; compare the plurality of flight operations executed by the pilots with the required SOP operational procedures; identify at least one of the plurality of SOP operational steps not executed or incorrectly executed by the pilots; and alert the pilots if and when the pilots fails to execute or incorrectly execute any of the plurality of SOP operational steps. In addition to alerting the pilots of the deviation(s) from the SOP sequence(s), the system may automatically generate a SOP exceedance report for recording the SOP operational step(s) not executed or incorrectly executed by the pilot(s), as well as automatically execute an emergency response, automatically execute an evasive maneuver, and / or automatically implement an autopilot—E.G., initiate execution of remotely-piloted, semi-autonomous, or autonomous, arrival approach, and landing procedures.

The invention discloses an air traffic control fatigue monitoring system and method based on voiceprint recognition, relates to the technical field of fatigue monitoring, and solves the problems that the fatigue state of a corresponding air controller is monitored by using a unified voiceprint reference in the existing fatigue monitoring technology, so that the fatigue state judgment accuracy of the air controller is reduced, and the fatigue monitoring efficiency is improved. And the efficiency of voiceprint monitoring of the fatigue state is reduced. The sound acquisition module is used for acquiring on-site sound data; the reference voiceprint construction unit is used for constructing reference voiceprint feature data according to the initial state voice; the semantic processing unit is used for generating a semantic association degree score according to the current state voice; the voiceprint processing unit is used for generating current voiceprint feature data according to the current state voice; generating a voiceprint state score according to the current voiceprint feature data and the reference voiceprint feature data; the alarm module is used for fusing the semantic association degree score and the voiceprint state score to obtain a fatigue degree score; and the fatigue state judgment accuracy is improved.

The invention discloses an air traffic control voice recognition method and system, and relates to the field of voice recognition, and the method comprises the steps: obtaining the voice data of an air traffic controller; performing classification and enhancement by using a double-flow generative adversarial network according to the air traffic controller voice data to obtain an enhanced voice signal; performing feature extraction and fusion by using a multi-modal feature fusion encoder according to the enhanced voice signal to obtain a context embedding vector and a fusion feature; performing prediction by using a parameter range prediction head and a scene adaptation classification head according to the context embedding vector to obtain a predicted parameter legal value domain and an allowed instruction action type; and according to the fusion feature, based on the prediction parameter legal value domain and the allowed instruction action type, carrying out constraint, and generating an instruction text sequence by using a decoder. The identification accuracy can be improved.

Systems and methods for simulating aircraft systems are provided. A system includes simulation entity agents defined to represent the behavior of multi-modal ride-sharing agents (e.g., aerial vehicle, ground vehicle, air traffic controllers, etc.) and world data representing a world environment within which the simulation entity agents may operate. The system obtains agent data indicative of a simulation aerial vehicle and world data indicative of a particular simulated world environment. The system determines scenario data including a scenario definition defining a simulation scenario and generates a simulation instance based on the scenario data. The simulation instance includes the simulation aerial vehicle within the simulated world environment. The simulation aerial vehicle can have access, within the simulation, to one or more backend services of a transportation services system configured to facilitate an aerial transportation service. The system can initiate the simulation instance and obtain data while the simulation is running.

To provide a system for preventing an accident by detecting a recognition discrepancy or an operation mistake between a controller and a pilot in real time.SOLUTION: A system comprising: means for receiving voice communication data between an air traffic controller and a pilot of an aircraft; means for converting the received voice communication data into text data; means for extracting instruction content from the converted text data; means for generating a predicted action based on the extracted instruction content; means for collecting current position data of the aircraft from a GPS; means for monitoring an actual action of the aircraft based on the collected GPS data; means for comparing the monitored action of the aircraft with the predicted action to detect an abnormality; and means for generating and notifying an alert when the abnormality is detected.SELECTED DRAWING: Figure 1

The application provides a controller CBTA evaluation system and method based on a multi-dimensional competency model. A first air traffic control task is input by an input module. The first air traffic control task includes multiple task stages and multiple sets of task parameters. Each task stage corresponds to a set of task parameters. A loading module loads a multi-dimensional competency model. The multi-dimensional competency model includes multiple competency models. A data acquisition module is configured to obtain multiple sets of historical assessment data corresponding to multiple air traffic controllers according to the multiple task stages and the multiple sets of task parameters. An evaluation module determines multiple evaluation results according to the multiple task stages, the multiple sets of task parameters, the multi-dimensional competency model, and the multiple sets of historical assessment data. An output module selects a target evaluation result according to the multiple evaluation results and outputs a target air traffic controller corresponding to the target evaluation result. The corresponding controller can be dynamically matched based on the task itself, so that the controller CBTA evaluation is more intelligent.

The invention discloses an air traffic controller multi-dimensional core competency evaluation system, and the system comprises a model management module which is used for loading and operating a stored competency evaluation model which is suitable for the multi-dimensional capability evaluation of an air traffic controller; the data processing module is used for acquiring and storing various data for competency evaluation calculation; the weight calculation module is used for calculating a subjective weight and an objective weight of each competency evaluation index based on the comparison data set and the objective performance scoring data set respectively; respectively calculating the combined weight of each competency evaluation index by taking the minimization of the deviation between the weight vectors as a target; the evaluation result generation module is used for calculating to obtain a quantitative evaluation result of the competency of the target controller; and the result output module is used for outputting the target controller information of which the quantitative evaluation result meets the competency requirement of the target task. The method has the advantages of being scientific and comprehensive in evaluation system, objective and quantitative in evaluation result, high in dynamic adaptability, easy to deploy and expand and the like.

A flight management system executes a method for arrival procedure display logic to reduce the overhead of pilots and air traffic controller by displaying a list of available arrival procedures sorted in a priority order based on headwind, estimated fuel on board, and estimated time of arrival. The pilot can select one of the available arrival procedures and request approval of the selected arrival procedure from the air traffic controller. The air traffic controller can clear the pilot for the selected arrival procedure or reject the selected arrival procedure if the selected arrival procedure is unavailable.

The present disclosure envisages in the field of navigation of aircrafts, their landing and take-off in low visibility situations. The system (100) comprises User device (200), Terminal (300), Aircraft Speed, Brake & Engine Control Module (500), a server (400) and pass-through points (600). Terminal (300) is configured to Aircraft Speed, Brake & Engine Control Module (500) which is configured to Aircraft Speed System. The server (400) through user device (200) with air traffic controller creates geofences (on the defined stretched of aircraft flight paths, runway zones / taxi bay lanes) and stores rules associated with each such geofences. Terminal (300) when it is found in a geofence gets instructions / messages from server (400) and communicate to Aircraft Speed, Brake & Engine Control Module (500). Aircraft Speed, Brake & Engine Control Module (500) connected to aircraft speed management system accordingly changes / regulates the speed of the aircraft which remains valid until Terminal (300) gets a new instruction / message from server (400) once Terminal (300) is at a new geofence. Precise location coordinates-based navigation map (based on multiple geofences fusion / intersection / overlap) and glidepath is created connecting the centerline of touchdown zone of runway to the terminal (300) of the aircraft when terminal (300) is found at desired descent zone geofence location coordinates. Pilot follows the glidepath i.e. precise navigation map and altitude (and after considering other usual parameters like speed, wind speed and direction) at various stages of landing and take-off without a need of visuals / lighting system which is not available in low visibility situations like fog, heavy rains, night-time etc. The present disclosure provides a solution for landing and take-off in low visibility situation without investing heavily on infrastructure and certification of operations levels of airports like CAT II and CAT III.

An apparatus for communicating between remote pilots of unmanned aircraft and air traffic controllers is disclosed. The apparatus includes a gateway having a user management unit configured to receive a user message from a software application corresponding to a remote pilot, and authenticate the remote pilot based on the user message or the corresponding data connection; an application programming interface configured to generate an access token if the remote pilot is authenticated, and make a call to an API endpoint of an air traffic controller communications network; an emulator configured to parse the user message and to convert it into a compliant format; and a datalink connector configured to push the converted user message and the access token to the application programming interface endpoint. The datalink connector receives a message from the air traffic controller communications network and the user management unit communicates the message to the software application.

The invention discloses a physiological data acquisition method for an air traffic controller, and relates to the technical field of data acquisition, and the method comprises the steps: obtaining the multi-modal physiological data of the air traffic controller at the current moment; inputting the multi-modal physiological data into the trained fatigue-emotion evaluation model to obtain a predicted fatigue score and predicted emotion state probability distribution at the current moment; based on the predicted fatigue score, the predicted emotional state probability distribution and the multi-modal physiological data, processing tasks of different priorities are generated; processing tasks are executed according to priorities through a hierarchical scheduling algorithm, and physiological data collection is completed. Through multi-modal data fusion and model evaluation, the physiological state of the controller is accurately obtained, tasks are processed according to priorities, timely response of key data is guaranteed, reliable physiological information support is provided for air traffic control, and the flight safety guarantee level is improved.

A method for automatically proposing an air conflict resolution, the method includes a step of receiving air conflict and air situation data at a time when an air conflict is detected, the method comprising the steps of: determining a conflict category associated with the detected air conflict based on the conflict data; determining a degree of relevance in proposing a resolution to the air conflict according to the category and the air situation; determining one or more types of resolution to be applied to resolve the detected air conflict according to the degree of relevance; determining set of alternative trajectories corresponding to the one or more types of resolution; determining a set of candidate trajectories from among the set of alternative trajectories, a candidate trajectory being an alternative trajectory which does not generate an air conflict; selecting, from among the candidate trajectories, a candidate trajectory which fulfills a selection criterion relating to the operational relevance of the candidate trajectories and to the acceptability of the candidate trajectories by the flight plan management system; returning the candidate trajectory, the candidate trajectory being saved and re-evaluated as long as it does not generate an air conflict or has not been accepted by an air traffic controller.

The invention provides a voice call scoring method and device for controller simulation training, equipment and a medium. The method comprises the steps that the total number of execution instructions and the number of matching instructions are determined according to a call voice recognition text; determining the number of successful execution instructions according to the instruction execution result state; determining the number of state invalid instructions according to the call voice recognition text and the instruction execution result state; determining an identification accuracy score according to the matching instruction number and a preset accuracy weight; determining an identification validity score according to the number of successful execution instructions and a preset success rate weight; determining a flow normalization score according to the missing instruction number, the execution sequence error instruction number and the redundant instruction number; determining a scene awareness score according to the number of state invalid instructions and the total number of execution instructions; summing the identification accuracy score, the identification validity score, the process normalization score and the scene consciousness score to obtain a simulation training score; and determining a simulation training evaluation grade according to the simulation training score. And the evaluation efficiency is effectively improved.

A ground station is used by an air traffic controller to provide support to an aircraft. In particular, the ground station may mirror or regenerate a weather radar overlay of a flight display of the aircraft. The air traffic controller and the flight crew may then both see the same real-time weather information with minimum delay and achieve a similar level of situation awareness. The weather radar overlay may be displayed on a display of the ground station. The ground station may receive weather data and ADS-B data or other forms of location data and intended flight path from the aircraft via an air-to-ground communication channel. The weather data may be used to regenerate the weather radar overlay. The ground station may also use the ADS-B data to generate a coverage map of the aircraft in a selected airspace.

The invention discloses a method for continuously monitoring cognitive load of an air traffic controller, which comprises the following steps of: firstly, acquiring multi-channel electroencephalogram signals of the air traffic controller under different working scenes and different cognitive load levels, and constructing a sample relation set with subject invariant, scene invariant and double-domain invariant constraints; then, inputting the windowed electroencephalogram into a double-branch space-time encoder, extracting multi-band local space-time characteristics by one branch, learning global function connection characteristics between channels by the other branch, and carrying out difference fusion on two outputs to obtain unified multi-scale potential representation; and through a decoupling projection module and a multi-domain contrast loss function, samples of the same cognitive load level are gathered in each space, and samples of different load levels are separated in each space, so that the interference of individual difference and scene difference on a discrimination result is explicitly weakened. The method still has high decoding precision and stability under the condition that significant individual differences and scene differences exist, and reliance on person-by-person calibration is relieved.

The present disclosure envisages in the field of navigation of aircrafts, their landing and take-off in low visibility situations. The system (100) comprises User device (200), Terminal (300), Aircraft Speed, Brake & Engine Control Module (500), a server (400) and pass-through points (600). Terminal (300) is configured to Aircraft Speed, Brake & Engine Control Module (500) which is configured to Aircraft Speed System. The server (400) through user device (200) with air traffic controller creates geofences (on the defined stretched of aircraft flight paths, runway zones / taxi bay lanes) and stores rules associated with each such geofences. Terminal (300) when it is found in a geofence gets instructions / messages from server (400) and communicate to Aircraft Speed, Brake & Engine Control Module (500). Aircraft Speed, Brake & Engine Control Module (500) connected to aircraft speed management system accordingly changes / regulates the speed of the aircraft which remains valid until Terminal (300) gets a new instruction / message from server (400) once Terminal (300) is at a new geofence. Precise location coordinates-based navigation map (based on multiple geofences fusion / intersection / overlap) and glidepath is created connecting the centerline of touchdown zone of runway to the terminal (300) of the aircraft when terminal (300) is found at desired descent zone geofence location coordinates. Pilot follows the glidepath i.e. precise navigation map and altitude (and after considering other usual parameters like speed, wind speed and direction) at various stages of landing and take-off without a need of visuals / lighting system which is not available in low visibility situations like fog, heavy rains, night-time etc. The present disclosure provides a solution for landing and take-off in low visibility situation without investing heavily on infrastructure and certification of operations levels of airports like CAT II and CAT III.

This invention discloses a method and system for predicting the performance of air traffic controllers in high-altitude areas based on smart bracelets. It relates to the fields of air traffic management, high-altitude medicine, and wearable computing. The method includes collecting physiological data such as heart rate, blood oxygen, and blood pressure via a smart bracelet; simultaneously acquiring environmental data such as altitude and visibility; extracting reaction time and error rate from voice data; performing data cleaning and alignment; inputting multimodal data into a deep fusion neural network model to calculate comprehensive risk indicators; triggering alerts and visually outputting the status when the indicators exceed dynamic thresholds, while simultaneously generating automated intervention suggestions. This invention, specifically designed for the low-oxygen environment of high altitudes, achieves deep attentional fusion of physiological, environmental, and behavioral data, constructing a dedicated prediction model suitable for high-altitude airports and forming a complete closed loop of "perception-prediction-intervention," providing an intelligent and non-intrusive proactive management tool for air traffic control safety.

A system is provided.SOLUTION: A system comprising: means for receiving real-time communications from pilots and air traffic controllers; means for converting the received communications into text data; means for inputting the text data into a generative AI model for analysis; means for detecting errors that have occurred and generating warning messages; and means for transmitting the warning messages to terminals for display.SELECTED DRAWING: Figure 1

The invention relates to an aeronautical meteorology and track cooperative monitoring method, and belongs to the technical field of civil aviation monitoring methods. The method comprises the following specific steps: step (1), multi-source data acquisition and access: receiving two types of data in real time through a standard data interface; (2) data analysis processing: analyzing and decoding the received heterogeneous data; step (3), data fusion and association, including spatial superposition, space-time matching, influence area analysis and track-weather association; and step (4), layered collaborative rendering and visual output are carried out. According to the method, deep data fusion is realized, simple layer superposition is exceeded, association and influence analysis of the track and the meteorological data are realized, a prospective decision basis is provided for air traffic controllers and dispatchers, cognitive loads are reduced, working efficiency is improved, the error rate is reduced, and safety is improved.

Systems and methods for simulating aircraft systems are provided. A system includes simulation entity agents defined to represent the behavior of multi-modal ride-sharing agents (e.g., aerial vehicle, ground vehicle, air traffic controllers, etc.) and world data representing a world environment within which the simulation entity agents may operate. The system obtains agent data indicative of a simulation aerial vehicle and world data indicative of a particular simulated world environment. The system determines scenario data including a scenario definition defining a simulation scenario and generates a simulation instance based on the scenario data. The simulation instance includes the simulation aerial vehicle within the simulated world environment. The simulation aerial vehicle can have access, within the simulation, to one or more backend services of a transportation services system configured to facilitate an aerial transportation service. The system can initiate the simulation instance and obtain data while the simulation is running.

The invention discloses a multi-dimensional core competency evaluation method for air traffic controllers. The method comprises the following steps executed by a cloud platform: loading and operating a competency evaluation model stored in the cloud platform; receiving and storing various data for competency evaluation calculation; calculating the subjective weight and the objective weight of each competency evaluation index based on the comparison data set and the objective performance scoring data set; based on the subjective weight and the objective weight, respectively calculating the combined weight of each competency evaluation index by taking minimization of the deviation between weight vectors as a target; based on the objective performance scoring data and the combined weight of the target controller, calculating to obtain a quantitative evaluation result of the competency of the target controller; and outputting the target controller information of which the quantitative evaluation result meets the competency requirement of the target task. The method has the advantages that the evaluation system is more scientific and comprehensive, the evaluation result is more objective and quantitative, the dynamic adaptability is high, and the evaluation efficiency and the data utilization rate are remarkably improved.

The present invention discloses a method for selecting an air traffic flow control strategy considering multiple objectives, including: flight data collection; constructing an evaluation index system for air traffic flow control strategies; constructing a comprehensive evaluation model for air traffic flow control strategies; taking the minimization of the index values in the evaluation index system for air traffic flow control strategies as the optimization objective, determining decision variables under different air traffic flow control strategies, and solving the index values of each flight based on the decision variables under different air traffic flow control strategies according to the collected flight data; calculating the optimal comprehensive evaluation cost index of each flight under the corresponding air traffic flow control strategy according to the comprehensive evaluation model; and selecting and using the air traffic strategy with the lowest comprehensive evaluation cost index. This method provides a decision-making basis for airlines to select flight routes and for air traffic controllers to manage traffic flow, and has practical application value in air traffic flow management.