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Decision Support to Masters, Mates on Watch, and Pilots: The Piloting Expert System

Published online by Cambridge University Press:  21 October 2009

Martha Grabowski
Martha Grabowski
Affiliation:
(Department of Decision Sciences and Engineering Systems Rensselaer Polytechnic Institute Troy, NY and Department of Business LeMoyne College Syracuse, NY.)
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Abstract

Piloting large vessels in increasingly congested waterways is no simple task. As in many ‘decision-making under uncertainty’ scenarios, masters, mates and pilots engaged in piloting are inundated with much information and required to make crucial decisions in real time. Piloting is also an inherently judgmental activity. Pilots and ships' captains invariably develop heuristics for transiting particular waterways. As vessels become larger, cargoes more hazardous, and the waterways more congested, decision aid technology is being considered to improve piloting decision-making. This paper describes one approach to providing improved on-board decision support to masters, mates on watch, and pilots navigating in restricted waters. We discuss (1) the use of cognitive decision aids in piloting, (2) the design of such a decision aid developed for New York harbour, (3) simulator experiments evaluating the expert system, and (4) plans to apply the approach and ‘lessons learned’ to the development of an expert system for tankers transiting the Gulf of Alaska.

Keywords

1. Pilotage.2. Expert systems3. Computers.
Type
Research Article
Information
The Journal of Navigation , Volume 43 , Issue 3 , September 1990 , pp. 364 - 384
Copyright
Copyright © The Royal Institute of Navigation 1990

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References

REFERENCES

1Huffner, J. R. (1976). Pilotage in confined waterways of the US: a preliminary study of pilot decision-making. Report no. CG-D-96-76. US Department of Transportation, US Coastguard, Office of Research and Development.Google Scholar
2Smith, M. W. and Bertsche, W. R. (1981). Aids to navigation principal findings report on the channel width experiment: the effects of channel width and related variables on piloting performance. Report No. CG-D-54-81, US Department of Transportation, US Coast Guard, Office of Research and Development.Google Scholar
3Grove, T. W. (1989). US flag of the future: concepts, features and issues. Proc. of the Ship Technology and Research Symposium. Society of Naval Architects and Marine Engineers, April, New Orleans.Google Scholar
4Vail, B. (1988). Crew cuts please ship lines but take toll on seafarers. Journal of Commerce, 28 Nov.Google Scholar
5Beetham, E. H. (1989). Bridge manning. Seaways, p. 3, February. Nautical Institute, London.Google Scholar
6Schuffel, H., Boer, J. P. A. and van Breda, L. (1989). The ship's wheelhouse of the nineties: the navigation performance and mental workload of the officer of the watch. This Journal, 42, 60.Google Scholar
7Kristiansen, S., Rensvik, E. and Mathisen, L. (1989). Integrated total control of the bridge. Proc. of Annual Meeting. Society of Naval Architects and Marine Engineers. November. New York.Google Scholar
8Grabowski, M. R. (1989). Decision aiding technology and integrated bridge design. Proc. of Ship Technology and Research Symposium. Society of Naval Architects and Marine Engineers, April, New Orleans.Google Scholar
9Coenen, F. P., Smeaton, G. P. and Bole, A. G. (1989). Knowledge-based collision avoidance. This Journal, 42, 107.Google Scholar
10Grabowski, M. R. (1987). Prototyping as a design strategy and as means of knowledge acquisition : an assessment using the ‘Piloting Expert System‘. PhD Thesis, Rensselaer Polytechnic Institute, NY.Google Scholar
11Grabowski, M. R. (1989). A mixed knowledge acquisition strategy reconsidered. Management Science (Forthcoming).Google Scholar
12Farnsworth, B. A. and Young, L. C. (1983). Nautical Rules of the Road: The International and United Inland Rules, Second Edition, Cornell Maritime Press, Centreville, MD.Google Scholar
13Davis, G. B. and Olson, M. H. (1985). Management Information Systems. 2nd Ed. McGrawHill, New York.Google Scholar
14 Panel on human error in merchant marine safety (1976). Human Error in Merchant Marine Safety. Maritime Transportation Research Board, National Academy of Sciences.Google Scholar
15Taylor, R. N. (1975). Psychological determinants of bounded rationality – implications for decision-making strategies. Decision Sciences, 6, 409.CrossRefGoogle Scholar
16Wallace, W. A., Gueutal, H. G., Lee, J. and Triscari, T. (1982). An evolutionary strategy for the assessment of individual decision aids in tactical command and control. Research Report 37-82-P13. School of Management, Rensselaer Polytechnic Institute, Troy, NY.Google Scholar
17Schilling, S., Kaufman, E. J., Schryver, J. V. and D'Amico, A. (1985). The applications of performance feedback in simulator training: its effects on the acquisition of shiphandling skills in unfamiliar waterways. Report No. CAORF-52-8204-02. Computer-Aided Operations Center, Kings Point, NY.Google Scholar
18Goldberg, J., D'Amico, A., Gilder, M. and Williams, K. (1980). The effectiveness of active vs. passive trainee participation, and segmented vs. integrated training. Structure on the acquisition of shiphandling skills. Report No. CAORF-50-7918-02. National Maritime Research Center, Kings Point, NY.Google Scholar
19Smart, C. and Vertinsky, I. (1977). Designs for crisis decision units, Administrative Sciences Quarterly, 22, 640.CrossRefGoogle ScholarPubMed
20Belardo, S., Karvvan, K. R. and Wallace, W. A. (1982). DSS component design through field experimentation: an application to emergency management. Proc. of Third International Conference on Information Systems, pp. 93–106, December, Ann Arbor, Michigan.Google Scholar
21Goldberg, J., D'Amico, A. and Williams, K. (1980). Transfer of training from low to high fidelity simulators. Report No. CAORF-50-7919-02. National Maritime Research Center, Kings Point, NY.Google Scholar
22Gotebiowski, P. and Mcllroy, W. (1983). Experimental identification of human control functions on simulated tankers in restricted waterways. Report No. CAORF-26-jgi I-Ol. National Maritime Research Center, Kings Point, NY.Google Scholar
23Simon, H. A. (1981). The Sciences of the Artificial, 2nd Edition. MIT Press, Cambridge, MA.Google Scholar
24Card, S. K., Moran, T. P. and Newell, A. (1983). The Psychology of Human -Computer Interaction. Lawrence Erlbaum Associates, Hillsdale, NJ.Google Scholar
25Veldhuyzen, W. and Stassen, H. G. (1977). The internal model concept: an application to modeling human control of large ships. Human Factors, 19, no. 4.CrossRefGoogle Scholar
26van Amerogen, J., van Nauta Lemke, H. R. and van der Veen, J. C. T. (1978). Optimum steering of ships with an adaptive autopilot. Proceedings of the 5th Ship Control Systems Conference, Annapolis, MD.Google Scholar
27Hwang, W., Guest, E., Pizzariello, E. and Brown, W. (1989). Factors to consider in developing a knowledge-based autopilot for ship manoeuvring simulation. Proceedings of the Society of Naval Architects and Marine Engineers Ship Technology and Research Conference. New Orleans.Google Scholar
28Barr, A. and Feigenbaum, E. (eds) (1983). The Handbook of Artificial Intelligence, Vol. 3. Stanford University Press, Stanford, CA.Google Scholar
29Hayes-Roth, F., Waterman, D. A. and Lenat, D. B. (1983). An overview of expert systems. In Hayes-Roth, , Waterman, and Lenat, (eds), Building Expert Systems, pp. 3–29.AddisonWesley Publishing Company, Reading, Massachusetts.Google Scholar
30Fikes, R. and Kehler, T. (1985). The role of frame-based representation in reasoning. Communications of the ACM, 28, 904.CrossRefGoogle Scholar
31Grabowski, M. R. (1988). Knowledge acquisition methodologies: survey and assessment. Proceedings of the 9th International Conference on Information systems. Minneapolis.Google Scholar
32O'Keefe, R. M., Balci, O. and Smith, E. P. (1987). Validating expert system performance. IEEE Expert, 2, 81.CrossRefGoogle Scholar
33Belardo, S., Karwan, R. and Wallace, W. A. (1984). Managing the response to disasters using microcomputers. Interfaces, 14, March-April.Google Scholar