Research article summary:

Fuzzy signal detection theory: analysis of human and machine performance in air traffic control, and analytic considerations.

Abstract Extract:
This paper applies fuzzy SDT (signal detection theory) techniques, which combine fuzzy logic and conventional SDT, to empirical data. Two studies involving detection of aircraft conflicts in air traffic control (ATC) were analysed using both conventional ... (Full abstract text below)

Published 2003Sep in Journal: Ergonomics (Language : eng)

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1. Ergonomics. 2003 Sep;46(11):1045-74

Fuzzy signal detection theory: analysis of human and machine performance in air traffic control, and analytic considerations.

Masalonis AJ, Parasuraman R

Center for Advanced Aviation System Development, The MITRE Corportation, Mclean, VA 22101-7508, USA. tonym@mitre.org

This paper applies fuzzy SDT (signal detection theory) techniques, which combine fuzzy logic and conventional SDT, to empirical data. Two studies involving detection of aircraft conflicts in air traffic control (ATC) were analysed using both conventional and fuzzy SDT. Study 1 used data from a preliminary field evaluation of an automated conflict probe system, the User Request Evaluation Tool (URET). The second study used data from a laboratory controller-in-the-loop simulation of Free Flight conditions. Instead of assigning each potential conflict event as a signal (conflict) or non-signal, each event was defined as a signal (conflict) to some fuzzy degree between 0 and 1 by mapping distance into the range [0, 1]. Each event was also given a fuzzy membership, [0, 1], in the set 'response', based on the perceived probability of a conflict or on the colour-coded alert severity. Fuzzy SDT generally reduced the computed false alarm rate for both the human and machine conflict systems, partly because conflicts just outside the conflict criterion used in conventional SDT, were defined by fuzzy SDT as a signal worthy of some attention. The results illustrate the potential of fuzzy SDT to provide, especially in exploratory data analysis, a more complete picture of performance in aircraft conflict detection and many other applications. Alternative analytic methods also using fuzzy SDT concepts are discussed.

PMID : 12850931 [PubMed - Indexed for MEDLINE]

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Full Author Information

First Name	LastName	Initials
Anthony J	Masalonis	AJ
Raja	Parasuraman	R

Affiliation: Center for Advanced Aviation System Development, The MITRE Corportation, Mclean, VA 22101-7508, USA. tonym@mitre.org

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Aircraft
Aviation - methods, standards, statistics & numerical data
Computer Simulation
Fuzzy Logic
Humans
Man-Machine Systems
Occupations
Task Performance and Analysis
Telecommunications - standards
United States

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