Artificial Intelligence Systems in Aviation

2019 ◽  
pp. 1-26 ◽  
Author(s):  
Ramgopal Kashyap
Keyword(s):  
Artificial Intelligence ◽  
Traffic Management ◽  
Aircraft Engine ◽  
Air Traffic Management ◽  
Transit System ◽  
Agent Based ◽  
Knowledge Based ◽  
Control Framework ◽  
Knowledge Based Engineering ◽  
Artificial Intelligence Systems

The aim of this chapter is to research and fundamentally evaluate counterfeit shrewd frameworks to recognize for outperforming human insight in the flights and its conceivable ramifications. How artificial intelligence (AI) makes current airship framework incorporates an assortment of programmed control framework that guides the flight team in route, flight administration and enlarging the security qualities of the plane, and how building aircraft engine diagnostics ontology, air traffic management, and constraint programming (CP) is useful in ATM setting. How flight security can be enhanced through the advancement and usage of mining, utilizing its outcomes and knowledge-based engineering (KBE) approach in an all-encompassing methodology for use in airship reasonable outline, is discussed. The early recognizable proof and finding of mistakes, the study of huge information and its effect on the transportation business and enhanced transit system, the agent-based mobile airline search, and booking framework using AI are shown.

scholarly journals Heading Toward Trusted ATCO-AI Systems: A Literature Review

2021 ◽  
Author(s):  
Jimmy Y. Zhong
Keyword(s):  
Artificial Intelligence ◽  
Traffic Management ◽  
Human Performance ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Air Traffic Controller ◽  
Current Review ◽  
Explainable Ai ◽  
Emerging Issues ◽  
Shed Light

The current review addresses emerging issues that arise from the creation of safe, beneficial, and trusted artificial intelligence–air traffic controller (AI-ATCO) systems for air traffic management (ATM). These issues concern trust between the human user and automated or AI tools of interest, resilience, safety, and transparency. To tackle these issues, we advocate the development of practical AI ATCO teaming frameworks by bringing together concepts and theories from neuroscience and explainable AI (XAI). By pooling together knowledge from both ATCO and AI perspectives, we seek to establish confidence in AI-enabled technologies for ATCOs. In this review, we present an overview of the extant studies that shed light on the research and development of trusted human-AI systems, and discuss the prospects of extending such works to building better trusted ATCO-AI systems. This paper contains three sections elucidating trust-related human performance, AI and explainable AI (XAI), and human-AI teaming.

scholarly journals ATM change management: An evolutionary and agent-based approach

2019 ◽  
Vol 259 ◽  
pp. 02005
Author(s):  
Gabriella Gigante ◽  
Domenico Pascarella ◽  
Marta Sánchez Cidoncha ◽  
Miquel Angel Piera ◽  
Gabriella Duca ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Change Management ◽  
Traffic Management ◽  
Air Traffic Management ◽  
Technical System ◽  
Management Process ◽  
New Approach ◽  
Agent Based ◽  
Computing Paradigm ◽  
The Impact

Air Traffic Management (ATM) is a complex socio-technical system, whose behaviour depends on a combination of various subsystems of different nature: societal, technical, and human. Due to such aspects, it is difficult to understand which could be the part to be changed in order to improve performances, or which is the impact of a change on the overall performances. Such tasks are though issues, and cannot be easily performed. In this work, a new approach for the ATM change management process is proposed. It aims to introduce an innovative multidisciplinary process by combining the following different paradigms: the agent-based paradigm for the modelling of a change solution and the assessment of the achieved performances; the evolutionary computing paradigm for the tuning of the change: the sensitivity analysis to understand which part of the ATM system should be changed in order to match the targeted performance levels.

A Multisecret Value Access Control Framework for Airliner in Multinational Air Traffic Management

2017 ◽  
Vol 4 (6) ◽  
pp. 1853-1867 ◽  
Author(s):  
Depeng Li ◽  
Rui Zhang ◽  
Yingfei Dong ◽  
Fangjin Zhu ◽  
Dusko Pavlovic
Keyword(s):  
Access Control ◽  
Traffic Management ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Control Framework
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