Collaborative Decision Making in Emergencies by the Integration of Deterministic, Stochastic, and Non-Stochastic Models

Background

Every year aircraft are becoming more reliable and secure; however, it is not possible to completely eliminate the human factor, which is one of the most common causes of accidents. One of the primary reasons for the accidents is an 80% deviation in the actions of aviation personnel in the organization and operations of flights; only 20% are due to failures of the aviation equipment (International Civil Aviation Organization (ICAO), 2004; Interstate Aviation Committee (IAC), 2016). The effective interaction of aircraft crew and the Air Traffic Control Operator is, therefore, a prerequisite for ensuring flight safety in standard conditions and in emergencies. Of particular importance is the coherence of communication between the crew and the controller in situations that arise in flight due to the influence of dangerous factors, i.e., emergencies (ICAO, 2007). Several common characteristics in emergencies are an acute shortage in time for Decision-Making (DM), incompleteness in communication, a lack of information, and the significant psychophysiological load on the aircraft crew.

The human factor remains the primary cause of aviation accidents (ICAO, 2004). People are the most flexible, adaptable, and important element in the aviation system, but they are also vulnerable to circumstantial impact on the quality of operations. At the initial stage in the development of aviation, many problems were caused by mechanics and emerging or evolving technologies, ecology, and ergonomic conditions (e.g., the design and configuration displays, controls, and cockpit equipment, and the layout of the cabin) in operational conditions such as exposure to noise, vibration, heat and cold, as well acceleration forces. The optimization of the human role in complex systems is related to all aspects of human activity, such as decision-making processes and obtaining knowledge; the communication opportunities, psychological, and the psycho-emotional states of the operators, as well as the interaction between operators; the technical opportunities of maintaining communications and new software; the preparation of flight plans and maps; and more recently improving development in the application of Artificial Intelligence (AI) (ICAO, 2018, 2019; International Air Transport Association (IATA), 2019).

The effects of the human factor on safety performance has continued to evolve through the development and testing of models that can be tested and applied in practice. Since the 1970s, ICAO has pursued a systematic approach to aviation safety using conceptual safety models such as the SHEL (S-Software, H-Hardware, E-Environment, L-Liveware) model. New components have been developed and added, such as SHELL (L-L), SHELL-T (L-L- Team), SHCHELL 's models (C- Culture), Reason’s model of latent conditions; the Threat and Error Management (TEM) model, and other models of human factors (ICAO, 1998, 2002, 2004, 2013a, 2013b, 2014, 2017, 2018). At the center of the SHEL model is a human individual—the most critical and most flexible component in the system—to which other components of the system must be carefully matched if stress and eventual breakdown in the system are to be avoided.

In order to achieve this matching, an understanding of the characteristics of this central component (i.e., the human-operator (H-O)) is essential. People are subject to considerable variations in decision making and behavior in the complex systems and suffer many limitations, most of which are now predictable, at least in general terms (Campbell, Bagshaw, 2002; ICAO, 2017). ICAO addresses the application of innovative technologies in the continuing development of aviation systems, such as the inclusion of AI methods, with modern information technology (ICAO, 2018; 2019; IATA, 2018).