Intelligent Automated System for Supporting the Collaborative Decision Making by Operators of the Air Navigation System During Flight Emergencies

Intelligent Automated System for Supporting the Collaborative Decision Making by Operators of the Air Navigation System During Flight Emergencies

Yuliya Sikirda (Flight Academy, National Aviation University, Ukraine), Mykola Kasatkin (Kharkiv National University of Air Forces named by I. Kozhedub, Ukraine) and Dmytro Tkachenko (Ukrainian State Air Traffic Services Enterprise (UkSATSE), Lviv, Ukraine)
DOI: 10.4018/978-1-7998-1415-3.ch003

Abstract

This chapter researches pilot and air traffic controller collaborative decision making (CDM) during flight emergencies for maximum synchronization of operators' technological procedures. Deterministic models of CDM by the Air Navigation System's human operators were obtained by network planning methods; their adequacy is confirmed by full-scale modeling on a complex flight simulator. For the sequential optimization of the collaborative two-channel network “Air traffic controller-Pilot” to achieve the end-to-end effectiveness of joint solutions, a multi-criteria approach was used: ensuring the minimum time to parry flight emergency with maximum safety/maximum consistency over the time of operators' actions. With the help of the multiplicative function, the influence of organizational risk factors on flight safety in the air traffic control was evaluated. A conceptual model of System for control and forecasting the flight emergency development on the base of Intelligent Automated System for supporting the CDM by operators was developed.
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Introduction

It is considered that aviation is the most fail-safe type of transfer. In as little as century, aviation, in the sphere of flight safety, rose through the ranks from an unstable system to the first “ultra-safe” system in the history of transport, it means system in which the number of catastrophic failures, in the sphere of safety, make up less than one per one million of production cycles (ICAO, 2013). The year 2018 was one of the safest years ever for commercial aviation, Aviation Safety Network data show (Aviation Safety Network, 2019b). Yet, 2018 year was worse than the five-year average. Over the year 2018, the Aviation Safety Network recorded a total of 15 fatal airliner accidents, resulting in 556 fatalities. This makes 2018 the third safest year ever by the number of fatal accidents and the ninth safest in terms of fatalities. The safest year in aviation history was 2017 with 10 accidents and 44 lives lost (Aviation Safety Network, 2018). Looking at that five-year average of 14 accidents and 480 fatalities, 2018 year was worse on both accounts. Twelve accidents involved passenger flights, three were cargo flights. Three out of 15 accident airplanes were operated by airlines on the E.U. “blacklist”, up by two compared to 2017. Given the estimated worldwide air traffic of about 37.800.000 flights, the accident rate is one fatal accident per 2.520.000 flights. Since 1997 the average number of aircraft accidents has shown a steady and persistent decline due to the continuing flight safety-driven efforts by international aviation organizations.

Despite the improvements in aircrafts control systems and air traffic control systems, the human factors still have a significant impact on flight safety – nearly 80% of aviation events are due to the fault of people (Friedman, Carterette, Wiener, & Nagel, 2014). The theory of human factor is gradually developing, tested and institutionalized. The evolution of the aviation system in the direction of a complex socio-technical system with gradual changes and additions to the well-known model of the human factor SHEL (1972) to date is given in documents of International Civil Aviation Organization (International Civil Aviation Organization [ICAO], 2002, 2003, 2009, 2012, 2013, 2014).

The authors distinguish five stages of the evolution of human factors models in aviation, related to the emergence of new components of the aviation system and to improve the diagnosis of Air Navigation System's (ANS’s) human-operators (H-O) errors (Table 1):

  • Stage 1: Professional Skills / Interaction / Errors.

  • Stage 2: Cooperation in team / Interaction in team / Error detection.

  • Stage 3: Culture / Safety / Errors prevention.

  • Stage 4: Safety / Efficiency / Minimization of errors.

  • Stage 5: Artificial Intelligence Systems / Analyze, detection, prevention, and minimization of errors.

Key Terms in this Chapter

Collaborative Decision Making (CDM): Is a joint government/industry initiative aimed at improving air traffic flow management through increased information exchange among aviation community stakeholders.

Air Navigation System (ANS): Is a complex of organizations, personnel, infrastructure, technical equipment, procedures, rules and information that is used to provide of airspace users of safe, regular and efficient air navigation service.

Air Navigation Service Provider: ( ANSP ): Is a public or a private legal entity providing Air Navigation Services. It manages air traffic on behalf of a company, region or country. Depending on the specific mandate an ANSP provides one or more of the following services to airspace users: Air Traffic Management (ATM), Communications, Navigation and Surveillance Systems (CNS), Meteorological Service for Air Navigation (MET), Search And Rescue (SAR), Aeronautical Information Services/Aeronautical Information Management (AIS/AIM).

Intelligent Automated System (IAS): Streamline decision making typically use tools for aggregating, extracting, and analyzing information - often, complex information such as human speech or unstructured text. Artificial Intelligence was a distributed computing project undertaken by Intelligence Realm, Inc. with the long-term goal of simulating the human brain in real time, complete with artificial consciousness and artificial general intelligence.

System-Wide Information Sharing and Management (SWIM): Is a Federal Aviation Administration advanced technology program designed to facilitate greater sharing of Air Traffic Management system information, such as airport operational status, weather information, flight data, the status of special use airspace, and National Airspace System restrictions.

Flight & Flow Information for a Collaborative Environment (FF-ICE): A product of the ICAO Global ATM Concept, that defines information requirements for flight planning, flow management, and trajectory management and aims to be a cornerstone of the performance-based air navigation system.

Decision Making (DM): Is the cognitive process resulting in the selection of a belief or a course of action among several alternative possibilities.

Air Traffic Management (ATM): The dynamic, integrated management of air traffic and airspace including air traffic services, airspace management, and air traffic flow management — safely, economically and efficiently – through the provision of facilities and seamless services in collaboration with all parties and involving airborne and ground-based functions.

Decision Support System (DSS): Is the interactive computer system intended to support different types of activity during the decision making including poorly-structured and unstructured problems.

Flight Emergency (FLEM): Is one in which the safety of the aircraft or of persons on board or on the ground is endangered for any reason.

Human-Operator (H-O): Is a person who interacts with a complex technique through information processes.

Expert system (ES): Is a computer system that emulates the decision making ability of a human expert.

Air Traffic Controllers (ATCOs): Are the coordinators of the movement of aircraft to maintain safe distances between them. Air traffic controllers typically do the following: monitor and direct the movement of aircraft on the ground and in the air, control all ground traffic at airport runways and taxiways, issue landing and takeoff instructions to pilots, transfer control of departing flights to other traffic control centers and accept control of arriving flights, inform pilots about weather, runway closures and other critical information, alert airport response staff in the event of an aircraft emergency.

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