Methods for Universal Beacon Code Assignment
| dc.contributor.advisor | Sherry, Lance | |
| dc.contributor.author | Kumar, Vivek | |
| dc.creator | Kumar, Vivek | |
| dc.date | 2011-07-28 | |
| dc.date.accessioned | 2011-08-22T17:43:57Z | |
| dc.date.available | NO_RESTRICTION | |
| dc.date.available | 2011-08-22T17:43:57Z | |
| dc.date.issued | 2011-08-22 | |
| dc.description.abstract | The primary responsibility of Air Traffic Control (ATC) is to expedite the flow of traffic while maintaining safe separation. Positive identification of the primary radar returns for individual aircraft is achieved through a system of interrogation and identification known as Air Traffic Control Radar Beacon System (ATCRBS). Each flight is identified by a unique "Beacon Code" assigned by the ATC before departure. Due to installed equipment limitations, and reservation of a few codes for special usage, only 3,348 Beacon Codes are available for use by non-military flights. ATC must "reassign" Beacon Codes to flights when they enter an ARTCC (Air Route Traffic Control Center) in which their current code is already in use. Each instance of Beacon Code reassignment requires human intervention and this process is therefore vulnerable to human-errors. An undetected error may lead to misidentification of flights which results in reduced safety margin. For this reason, Beacon Code reassignments are undesirable. On a typical day (04/11/2007) including 48,721 flights (non-military), 62,805 handoffs occurred, when flights crossed ARTCC boundaries. With the current distributed code allocation scheme and the existing route structure, 6,730 (10.7%) code reassignments were required. The current allocation method is also subject to code shortages as the volume of air-traffic grows. The objective of this research was to develop a detailed understanding of the problem and enumerate and evaluate alternative methods to eliminate (or minimize) code "reassignments" and potential shortages. The methods were required to be robust in the face of routing variations necessitated by weather and also to the evolution of airline networks. This dissertation describes and evaluates three new alternate methods for centralized Beacon Code assignment that assign codes by exploiting the temporal and spatial opportunities available in the NAS: 1. A Mixed-Integer Linear Progam (MILP) optimization model, 2. A Space-Time Adjacency (STA) heuristic algorithm, and 3. A hybrid approach combining MILP optimization and STA heuristic algorithm. The results of this research demonstrate the feasibility of implementing a code assignment system that eliminates need for reassignment and is scalable to future traffic growth. | |
| dc.identifier.uri | https://hdl.handle.net/1920/6600 | |
| dc.language.iso | en_US | |
| dc.subject | Beacon Codes | |
| dc.subject | Air traffic control | |
| dc.subject | Squawk Codes | |
| dc.subject | Air Traffic Control Radar Beacon System (ATCRBS) | |
| dc.subject | Optimization | |
| dc.subject | Secondary Radar | |
| dc.title | Methods for Universal Beacon Code Assignment | |
| dc.type | Dissertation | |
| thesis.degree.discipline | Systems Engineering and Operations Research | |
| thesis.degree.grantor | George Mason University | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | PhD in Systems Engineering and Operations Research |