Applications of Decision Support Systems in Aviation

Applications of Decision Support Systems in Aviation

Tetiana Shmelova, Yuliya Sikirda
Copyright: © 2021 |Pages: 17
DOI: 10.4018/978-1-7998-3479-3.ch046
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Abstract

In this chapter, the authors have made an analysis of the International Civil Aviation Organization (ICAO) documents on risk assessment and the impact of the social environment on the aviation system. The conceptual models of decision support systems (DSS) for human-operator (H-O) of air navigation system (ANS) have been presented, such as air traffic control (ATC) operators, flight dispatcher, unmanned aerial vehicles (UAV) operator. The chapter presents some cases of DSSs that have been developed by the authors and students at National Aviation University, Ukraine. These researches are designed for operators such as pilots of manned and unmanned aircraft, flight dispatchers, ATC operators, aviation managers, as well for scientists, engineers, air crash investigators, teachers, academicians, researchers, and students seeking current research on the application of DSS in the field of aviation.
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Introduction

The air transport industry plays a major role in world economic activity and to maintain the safe and efficient operation of aviation enterprises that allows maximum use to be made of enhanced capabilities provided by technical advances. Nowadays the International Civil Aviation Organization (ICAO) has added in its documents new approaches for achieving the main goals of the organization, which are: to enhancing the effectiveness of global aviation security and to improve the practical and sustainable implementation of preventive aviation security measures. These new approaches include the development of progressive technology and human capability, the improvement of technological resources to improve the quality of decision making of aviation personal (pilots of manned and unmanned aircraft, air traffic controllers, engineers, etc. (ICAO, 2017; ICAO, 2018). The quality of decision dependences is using innovative technology in aviation such as Artificial Intelligence (AI). The AI document “White paper” of IATA (International Air Transport Association) presents the results of IATA research and development activities on AI in collaboration with airlines. The new technologies of AI can be clustered in the following capabilities, such as Machine learning (ML), Natural Language Processing (NLP), Expert Systems, Vision, Speech, Planning, Robotics (IATA, 2016; ICAO, 2018). To increase the productivity of work at each stage of the life cycle (LC) of aviation systems, different AI technologies and methods can be effectively applied (Figure 1).

Figure 1.

The synergetic effect - LC of aviation technique with using AI capability

978-1-7998-3479-3.ch046.f01

Artificial Intelligence is the simulation of human intelligence processes by modeling, computer systems, and machines. These processes include learning (the acquisition of information and rules for using the information); reasoning, estimation, and modeling (using rules to reach conclusions (approximate or definite results)); self-correction (estimation of obtained models). Particular applications of AI include Expert System (ES); Decision Support System (DSS); Automated systems; systems of pattern recognition, speech recognition, and machine vision, etc. (ICAO, 2017; IATA, 2016). AI (and DSS) are effective for minimization risks and improve the quality of decisions in the aviation system.

Key Terms in this Chapter

SARPs: Standards and recommended practices.

IFR: Instrument flight rules.

VFR: Visual flight rules.

H-O: Human-operator.

VLOS: Visual line of sight.

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.

ASSSIST: Acknowledge, separate, synergetic (coordinated, cooperation, consolidation), silence, inform, support, time.

BVLOS: Beyond visual line of sight.

ANS: Air navigation system.

Smart: Is a best practice framework for setting goals. A SMART goal should be specific, measurable, achievable, relevant and time-bound.

Air Traffic Management (ATM): Is an aviation term encompassing all systems that assist aircraft to depart from an aerodrome, transit airspace, and land at a destination aerodrome, including Air Traffic Services (ATS), Airspace Management (ASM), and Air Traffic Flow and Capacity Management (ATFCM).

Global Navigation Satellite Systems (GNSS): Is the common name of global satellite-based systems for navigation, positioning and time transfer. The most well-known system is the American system GPS (Global Positioning System) which got its operational status in 1994. Russia also has a similar system since the beginning of the 1990's called GLONASS (GLObal NAvigation Satellite System).

Command and Control (C2): Denotes the set of organizational and technical attributes and processes by which an enterprise marshals and employs human, physical, and information resources to solve problems and accomplish missions.

PANS: Procedures for air navigation services.

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, status of special use airspace, and National Airspace System restrictions.

RPS: Remote pilot station.

CNS/ATM: Communication, navigation, surveillance/air traffic management.

Distributed Decision Support System (DDSS): Is a decision support system which supports distributed organizational decision making.

Remotely Piloted Aircraft (RPA)/Remotely Piloted Aircraft System (RPAS)/Unmanned Aerial Vehicle (UAV)/Drone: Is a system that based on cutting-edge developments in aerospace technologies, offering advancements which are opening new and enhanced civil-commercial applications as well as improvements to the safety and efficiency of the entire civil aviation. The terms RPA or UAV are used to describe the aircraft itself, whereas the term RPAS is generally used to describe the entire operating equipment including the aircraft, the control station from where the aircraft is operated and the wireless data link.

Safety Management System (SMS): Is the formal, top-down, organization-wide approach to managing safety risk and assuring the effectiveness of safety risk controls. It includes systematic procedures, practices, and policies for the management of safety risk.

AC: Aircraft.

ICAO: International Civil Aviation Organization.

Communication, Navigation, and Surveillance (CNS): Are the main functions that form the infrastructure for Air Traffic Management, and ensure that air traffic is safe and efficient.

TTC: Tactical and technical characteristics.

Performance-Based Approach (PBA): Is a decision-making method based on three principles: strong focus on desired/required results; informed decision making driven by those desired/required results and reliance on facts and data for decision making. The PBA is a way of organizing the performance management process.

ASSIST: Acknowledge, separate, silence, inform, support, time.

AS PIP: Automated system of pre-flight information preparation.

ADS-B: Automatic dependent surveillance-broadcast AU62: Hidden text detected. Text reads: "Automatic Dependent Surveillance-Broadcast". .

Flight and 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.

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.

NoSQL (Originally Referring to “Non-SQL” or “Non-Relational”) Database: Provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases.

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