Research On Intelligent Diagnosis Of Serious Incident For Runway Incursion

The risk of runway incursions heavily impacts the airdrome surface safety operation with the rapid growth of flight traffic flow in multi-runway airport,furthermore,which obviously reduces the safety margin among aircraft.To enhance the analysis abilities through intelligence and automation in runway incursions prevention,a formal modeling method is proposed,thanks to artificial intelligence in which ontology and SWRL are applied to make the diagnosis of serious incidents for runway incursions.This paper puts forward general modeling steps of domain ontology to meet the needs of runway incursions prevention,which is done via analysis of situation and main characteristics of ontology and SWRL.To build ontology,class hierarchy is carried out,and as per expert experience SWRL rules are defined.The developed ontology and SWRL rules are combined to construct framework of intelligent diagnosis system,which aimed at mitigating against runway incursions.Actual cases are reasoned by professional pellet reasoner,both inference results and response measures are offered.Intelligent diagnosis tools are developed based on above methods to support further research such as: airport safety hotspots,serious incidents for runway incursions,as well as runway incursions on civil-military airport.Results show that excellent performance of ontology and rule-based reasoning in knowledge retrieving and inferring,which laies a solid foundation for application in airport surface safety management with artificial intelligence.