Automated air traffic control for non-towered airports

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Abstract/Contents

Abstract
The majority of midair collisions involve general aviation aircraft, and these accidents tend to occur in the vicinity of airports. This work proposes a concept for an autonomous air traffic control system for non-towered airports. The system is envisioned to be advisory in nature and would rely on observations from a ground-based surveillance system to issue alerts over the common traffic advisory frequency. The behavior of aircraft in the airport pattern is modeled as a hidden Markov Model (HMM) whose parameters are learned from real-world radar observations. To determine the optimal advisories that reduce the risk of collision, the problem is formulated as a partially observable semi-Markov decision process (POSMDP). In order to address the computational complexity of solving the problem, different approximation methods including exponential sojourn times, phase-type distributions, online algorithms, and particle filters for belief estimation are investigated. Simulation results are presented for both nominal and learned airport models.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2016
Issuance monographic
Language English

Creators/Contributors

Associated with Mahboubi, Zouhair
Associated with Stanford University, Department of Aeronautics and Astronautics.
Primary advisor Kochenderfer, Mykel J, 1980-
Thesis advisor Kochenderfer, Mykel J, 1980-
Thesis advisor Erzberger, Heinz
Thesis advisor Kroo, Ilan
Thesis advisor Pavone, Marco, 1980-
Advisor Erzberger, Heinz
Advisor Kroo, Ilan
Advisor Pavone, Marco, 1980-

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Zouhair Mahboubi.
Note Submitted to the Department of Aeronautics and Astronautics.
Thesis Thesis (Ph.D.)--Stanford University, 2016.
Location electronic resource

Access conditions

Copyright
© 2016 by Zouhair Mahboubi
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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