ESTIMATION OF BAD WEATHER CONDITIONS INFLUENCE ON DIFFERENT PHASES OF FLIGHT USING EXPERT JUDGEMENT METHOD
DOI:
https://doi.org/10.18372/2306-1472.79.13827Keywords:
accident, artificial intelligence, bad weather conditions, expert judgement method, machine learning, stages of flightAbstract
Purpose: estimation of the influence of five different types of bad weather conditions: fog, wind shear, thunderstorm, icing and snow on the aircraft operations during three stages of flight: takeoff and climb, enroute, descent and landing. Methods: using the significance of influence on the flight operations as the parameter of comparison, bad weather conditions are compared by experts in their questionnaires. With the help of expert judgement method, the experts’ group opinions are obtained, coordinated, the significance of calculations criteria and weight coefficients are calculated. Using the results of calculations, the general histogram of weight coefficients for three different stages of flight is built, representing the significance of bad weather conditions influence on aircraft operations. Results: the expert system methodology presented in this work helps to evaluate the impact of weather events on the flight operations and select the appropriate measures of preventing bad weather conditions influence on each stage of flight. Discussion: the derived expert system can be used in airplane operations to evaluate the impact caused by weather, for further improvement of the situational awareness and decision making process of aviation staff with the application of new artificial intelligence technologies.
References
Airservices Australia. Impact of weather on operations. Available at:
http://www.airservicesaustralia.com/services/how-air-traffic-control-works/impact-of-weather/
European Aviation Safety Agency (2018) Weather Information to Pilots Strategy Paper. Flight Standards Air Traffic Management/Air Navigation Services (ATM/ANS) Development.– 45 p.
International Civil Aviation Organization (2002) Global Air Navigation Plan for CNS/ATM Systems – Doc 9750 AN/963.
Salem A., Shmelova T. (2018) Intelligent Expert Decision Support Systems: Methodologies, Applications and Challenges. International Publisher of Progressive Information Science and Technology Research. – USA, Pennsylvania. – P. 215-242
Friedman M., Carterette E., Wiener E., Nagel D. (2014) Human Factors in Aviation. 1st еd.– USA, Massachusetts, Academic Press Publ., 684 p.
International Civil Aviation Organization (2002) Human Factors Guidelines for Safety Audits Manual. 1st ed. Doc. ICAO 9806-AN/763, Canada, Montreal, ICAO Publ., 138 p.
International Civil Aviation Organization (2004) Cross-Cultural Factors in Aviation Safety: Human Factors Digest № 16. Сir. ІСАО 302-AN/175. Canada, Montreal, ICAO Publ., 52 p.
International Civil Aviation Organization (2009) Global Performance of the Air Navigation System. 1st ed. Doc. ICAO 9883, Canada, Montreal, ICAO Publ., 176 p.
International Civil Aviation Organization (2013) Safety Management Manual (SMM). 3rd ed. Doc. ICAO 9859-AN 474.– Canada, Montreal, ICAO Publ., 300 p.
International Civil Aviation Organization (2014) Manual on Collaborative Decision-Making (CDM). 2nd ed. Doc. ICAO 9971.– Canada, Montreal, ICAO Publ., 166 p.
International Civil Aviation Organization (2012) Manual on Flight and Flow Information for a Collaborative Environment (FF-ICE). 1st ed. Doc. ICAO 9965.– Canada, Montreal, ICAO Publ., 140 p.
International Civil Aviation Organization (2005) Global Air Traffic Management Operational Concept. 1st ed. Doc. ICAO 9854.– Canada, Montreal, ICAO Publ., 82 p.
Ministry of Civil Aviation of the USSR (1985) Nastavlenie po proizvodstvu poletov v grazhdanskoy aviatsii SSSR (s izmeneniyami i dopolneniyami) [Manual on the production of flights in the civil aviation of the USSR (with changes and additions)], Moscow, Air Transport Publ., 262 p. (In Russian)
International Civil Aviation Organization (2007) Air Traffic Management. 15th еd. Doc. ICAO 4444-RAC/501.– Canada, Montreal, ICAO Publ., 425 p.
Golovnin S.М. (2016) Podgotovka pilotov i dispetcherov v virtualnoy srede pilotirovaniya i upravleniya vozdushnyim dvizheniem [Training pilots and controllers in the virtual environment of piloting and air traffic control]. Available at: www.researchgate.net/publication/303859941_Aviation_Training_Pilots_Air_Traffic_Controller.
Aviation Accident Statistics. (2017). National Transportation Safety Board. Retrieved from www.ntsb.gov/aviation/ aviation.html
International Air Transport Association (2017) IATA Safety Report 2016. 53rd ed. – Montreal, Quebec, Canada.– 254 p.
Aviation Safety Network (2018) ASN Wikibase. Available at: www.aviation-safety.net/wikibase/
International Air Transport Association (2018) White Paper - AI In Aviation. Exploring the fundamentals, threats and opportunities of artificial intelligence (AI) in the aviation industry.– 20 p.
McGovern A., Elmore K., Gagne II D., Haupt S., Karstens C., Lagerquist R., Smith T., Williams J. (2017) Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather. The Bulletin of the American Meteorological Society (BAMS). – School of Computer Science, University of Oklahoma: American Meteorological Society.– P. 2073–2090.
Air Traffic Management. ICAO sees Artificial Intelligence as the NORM.
Available at: https://airtrafficmanagement.keypublishing.com/2018/09/18/icao-sees-artificial-intelligence-as-the-norm/
