Towards Intelligent System Wide Information Management for Air Traffic Management

Autor:	Li Weigang, Ítalo Romani de Oliveira, Alessandro Ferreira Leite, Jose A. Fregnani, Vitor Filincowsky Ribeiro
Rok vydání:	2017
Předmět:	Computer science business.industry System Wide Information Management Air traffic management Big data Probabilistic logic Web Ontology Language Ontology (information science) Simulated annealing Reinforcement learning Software engineering business computer computer.programming_language
Zdroj:	Security, Privacy, and Anonymity in Computation, Communication, and Storage ISBN: 9783319723884 SpaCCS
DOI:	10.1007/978-3-319-72389-1_46
Popis:	This paper briefly reviews the state-of-the-art in Artificial Intelligence (AI) applied to Air Traffic Management (ATM). The research topics include the application of semantic ontology, multi-agent systems, reinforcement learning (RL), and game theory in ATM. Likewise, this paper also highlights our research advances in this area. In this case, we describe a new Probabilistic Web Ontology Language (PR-OWL) algorithm to enable the reasoning on big datasets in polynomial time. Then, we present the use of both Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithms in 4D trajectory management. Next, we describe the usage of Multi-agent Planning (MAP) theory on airport ground handling management. Finally, this paper envisions some research and development directions of AI applied to ATM. It includes: (a) mapping and reducing the gaps between advanced AI technologies and ATM; (b) considering uncertainty in Semantic Ontology for SWIM data exchanging models in ATM; (c) using big data analytics in SWIM; and (d) integrating collaborative ATM technologies towards intelligent SWIM (I-SWIM).
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::77ef1104d7ed9eb883ea401cef067fcf https://doi.org/10.1007/978-3-319-72389-1_46 Zobrazit plný text záznamu