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Multivariate analysis of operational...

Ceric, Damir.

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Multivariate analysis of operational errors in air traffic control.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Multivariate analysis of operational errors in air traffic control./
Author:	Ceric, Damir.
Description:	38 p.
Notes:	Adviser: Kevin Jordan.
Contained By:	Masters Abstracts International46-02.
Subject:	Engineering, Aerospace. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1448878
ISBN:	9780549277095

Multivariate analysis of operational errors in air traffic control.
Ceric, Damir.

Multivariate analysis of operational errors in air traffic control. - 38 p.

Adviser: Kevin Jordan.

Thesis (M.A.)--San Jose State University, 2007.

Improving safety by reducing the frequency of operational errors in an air traffic control environment has long been the goal of the FAA. Complexity embedded in air traffic control operations, configuration of airspace, and human information processing capacity limitations allow for multiple factors to influence incidents, creating several categories of operational error. This study examines several predictors of operational errors, and is tailored towards recognizing error patterns. A single operational error may have multiple categories. Identifying unique contributions of any of them is essential, because it leads to a better human error prediction model. Results in this study revealed the influence of a number of contextual factors in prediction of error type frequency. Furthermore, the severity conformance metric (an aircraft proximity index) predicted the frequency of error categories to some extent. The number of aircraft in a sector did not contribute significantly towards the prediction of error categories.

ISBN: 9780549277095Subjects--Topical Terms:

1018395
Engineering, Aerospace.

Multivariate analysis of operational errors in air traffic control.
LDR:01915nam 2200301 a 45 001 948678
005 20110524
008 110524s2007 ||||||||||||||||| ||eng d
020 $a 9780549277095
035 $a (UMI)AAI1448878
035 $a AAI1448878
040 $a UMI $c UMI
100 1 $a Ceric, Damir. $3 1272129
245 1 0 $a Multivariate analysis of operational errors in air traffic control.
300 $a 38 p.
500 $a Adviser: Kevin Jordan.
500 $a Source: Masters Abstracts International, Volume: 46-02, page: 1152.
502 $a Thesis (M.A.)--San Jose State University, 2007.
520 $a Improving safety by reducing the frequency of operational errors in an air traffic control environment has long been the goal of the FAA. Complexity embedded in air traffic control operations, configuration of airspace, and human information processing capacity limitations allow for multiple factors to influence incidents, creating several categories of operational error. This study examines several predictors of operational errors, and is tailored towards recognizing error patterns. A single operational error may have multiple categories. Identifying unique contributions of any of them is essential, because it leads to a better human error prediction model. Results in this study revealed the influence of a number of contextual factors in prediction of error type frequency. Furthermore, the severity conformance metric (an aircraft proximity index) predicted the frequency of error categories to some extent. The number of aircraft in a sector did not contribute significantly towards the prediction of error categories.
590 $a School code: 6265.
650 4 $a Engineering, Aerospace. $3 1018395
650 4 $a Engineering, System Science. $3 1018128
650 4 $a Psychology, Experimental. $3 517106
650 4 $a Psychology, Industrial. $3 520063
690 $a 0538
690 $a 0623
690 $a 0624
690 $a 0790
710 2 $a San Jose State University. $3 1020800
773 0 $t Masters Abstracts International $g 46-02.
790 $a 6265
790 1 0 $a Jordan, Kevin, $e advisor
791 $a M.A.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1448878