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2023 Journal Impact Factor - 0.7
2023 CiteScore - 1.4
ISSN 2083-6473
ISSN 2083-6481 (electronic version)
Editor-in-Chief
Associate Editor
Prof. Tomasz Neumann
Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
e-mail transnav@umg.edu.pl
Collision Scenario-based Cognitive Performance Assessment for Marine Officers
1 Marine Transportation & Pollution Response Research Dept., MOERI/KORDI, Daejeon, Korea
2 Korea National University of Transportation, Chungju, South Korea
2 Korea National University of Transportation, Chungju, South Korea
ABSTRACT: The overall aim of this paper is to determine a fatigue factor that can be applied to human performance data as a part of a software program that calculates total cognitive performance. This program enables us to establish the levels of cognitive performance in a group of marine pilots in order to test a decision-making task based on radar information.?This paper addresses one of the factors that may contribute to the determination of various fatigue factors: the effects of different work patterns on the cognitive performance of a marine pilot.
KEYWORDS: Anti-Collision, Radar, ARPA, Collision Avoidance, Decision Making Task, Performance Assessment, Collision Scenario, Cognitive Performance
REFERENCES
Andreassi, J.L., 2000. Psychophysiology: Human behav-iour and physiological response (4th edition), Lawrence Erlbaum Associates.
Kim, H., Yang, C.S., Park, J.H. and Lee, J.K., 2004. Reduc-tion of maritime risk relating human factors, Proceedings of the Society of Naval Architecture of Korea(Spring Confer-ence), pp. 816-821.
Hart, S.G. and Staveland, L.E., 1988. Development of NASA-TLX (Task Load Index): results of empirical and theoretical research in: Hancock, P.A. and Meshkati, N.(eds.), Human Mental Workload. Amsterdam: North-Holland.
Mitchell, D.K., 2000. Mental Workload and ARL Workload Modeling Tools, Army Research Laboratory, Report No ARL-TN-161.
Lee, J.D., and Sanquist, T.F., 2000. Augmenting the opera-tor function model with cognitive operations: assessing the cognitive demands of technological innovation in ship nav-igation, IEEE Transactions on Systems, Man and Cyber-netics – Part A: Systems and Humans. 30 (3), 273-285.
Lee, J.K., 2005. Development of Fundamental Technolo-gies for Total Risk Management, KORDI Project Report, UCE00940-05043.
Wickens, C.D., 1992. Virtual reality and education, Pro-ceedings of the 1992 IEEE International Conference on Systems, Man and Cybernetics, 1, 842-847.
Wierwille, W.W. and Casali, J.G., 1983. A validated rating scale for global mental workload measurement application, Proceedings of the Human Factors Society 27th Annual Meeting. Santa Monica, CA: Human Factors Society
Citation note:
Kim H., Kim H.J., Hong S.: Collision Scenario-based Cognitive Performance Assessment for Marine Officers. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 4, No. 1, pp. 73-77, 2010
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