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Intelligent agent for aircraft collision avoidance
dc.creator | Shandy, Surya Utama | |
dc.date.accessioned | 2012-06-07T23:18:32Z | |
dc.date.available | 2012-06-07T23:18:32Z | |
dc.date.created | 2002 | |
dc.date.issued | 2002 | |
dc.identifier.uri | https://hdl.handle.net/1969.1/ETD-TAMU-2002-THESIS-S534 | |
dc.description | Due to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to digital@library.tamu.edu, referencing the URI of the item. | en |
dc.description | Includes bibliographical references (leaves 153-164). | en |
dc.description | Issued also on microfiche from Lange Micrographics. | en |
dc.description.abstract | The trend of the air traffic system is toward a free flight environment. Free flight offers greater flexibility in planning for flights than the current air traffic control and management system. In free flight, operators are allowed to fly under instrument flight rules and choose their own flight path and speed in real time. One of the requirements to make the free flight environment feasible is an aircraft collision avoidance agent, also known as a traffic agent. One widely accepted concept of aircraft to aircraft communication for free flight environment is Automatic Dependent Surveillance Broadcast. In this research, the focus is on constructing a traffic agent, utilizing aircraft to aircraft information for flight management system. The agent includes a traffic conflict detection module and collision avoidance module. The method used by the modules is a combination of knowledge based expert system and optimal control. The expert system is the primary decision-maker and determines the appropriate actions required for conflict detection and avoidance. Optimal control is used to generate the optimum avoidance trajectory that adheres to the criteria assigned by the expert system. Results of various test cases presented in the research demonstrate that the combination of the two methods provides an efficient and effective way to obtain optimal traffic avoidance trajectories. | en |
dc.format.medium | electronic | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | en_US | |
dc.publisher | Texas A&M University | |
dc.rights | This thesis was part of a retrospective digitization project authorized by the Texas A&M University Libraries in 2008. Copyright remains vested with the author(s). It is the user's responsibility to secure permission from the copyright holder(s) for re-use of the work beyond the provision of Fair Use. | en |
dc.subject | aerospace engineering). | en |
dc.subject | Major aerospace engineering). | en |
dc.title | Intelligent agent for aircraft collision avoidance | en |
dc.type | Thesis | en |
thesis.degree.discipline | aerospace engineering) | en |
thesis.degree.name | M.S. | en |
thesis.degree.level | Masters | en |
dc.type.genre | thesis | en |
dc.type.material | text | en |
dc.format.digitalOrigin | reformatted digital | en |
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