Research On Application Of Ontology-driven Bayesian Network For Human Error Analysis Of Air Traffic Control

In the face of the complex air traffic situation from the external,the controller needs to respond quickly and make the correct decision in a timely manner.The heavy and spiritual pressure of the control task makes human errors inevitable.In order to improve that operation quality of the ATC(air traffic control,ATC)and to assist the decision-making suggestion of risk control,the ontology-driven Bayesian network modeling technology is proposed,the domain knowledge is represented by the ontology semantic description logic,and the probability reasoning mechanism of Bayesian Network is combined to quantify and analyze the safety-related uncertainty of the ATC,and gives some preventive measures.By summing up the application of integrated modeling technology in the fields of uncertainty information processing,reliability evaluation and fault diagnosis,combined with the characteristics of control activities,referring to the relevant literature in the field and practical controller work,The overall framework is designed.Based on the knowledge engineering modeling method and ontology semantic description logic,the domain concepts,attributes and relationships are formalized,on the basis of which the machine learning of human error unsafe event data of air traffic control is carried out.The evolution mechanism of air traffic management safety risk is analyzed by using BN probability reasoning mechanism,and the corresponding prevention and countermeasures are given.The results show that the proposed method can improve the ability of situation awareness of flight conflict,realize the key cause diagnosis of human error in the control of handover,and improve the level of risk control in airport scene operation.The effective management of the knowledge in the field of human errors and the rational quantification of the risk-related uncertainty probability information are realized,which provides a better application support for the intelligence of the security information in the operation of the air traffic control system.