Abstract
Modeling and simulation of a system, such as maritime traffic, with high complexity and a wide range of requirements including ships, navigators, control centers, shipping companies, meteorological systems, and geographic information systems requires human involvement. For maritime traffic simulation in a digital environment, modeling of human factors, a major element, is necessary, and for the reproduction and prediction of realistic maritime traffic situations, it is reasonable to model and reflect the navigator’s cognitive processes, behavior patterns, navigational expertise, navigational errors, etc. To develop an intelligent ship agent for maritime traffic analysis, we will analyze the navigator’s ship navigation-related cognition and behavior, and introduce the status of the development of an agent-based cognitive and behavioral model as similar to the navigator’s behavior.
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References
Lee, J.D., Sanquist, T.F.: Augmenting the operator function model with cognitive operations: assessing the cognitive demands of technological innovation in ship navigation. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 30(3), 273–285 (2000)
Sanquist, T.F., Lee, J.D., Rothblum, A.M.: Cognitive analysis of navigation tasks: a tool for training assessment and equipment design. CG-D-19-94, U.S. Coast Guard Research and Development Center (1994)
Lee, J.D., McCallum, M.C., Maloney, A.L., Jamieson, G.A.: Validation and sensitivity analysis of a crew size evaluation method. ADA331589, Battle Seattle Research Center (1997)
Itoh, K., Yamaguchil, T., Hansen, J.P., Nielsen, F.R.: Risk analysis of ship navigation by use of cognitive simulation cognition. Technol. Work 3, 4–21 (2001)
Kim, B.A., et al.: The effect of navigation officer’s expertise on situation awareness. Korea J. Ind. Organ. Psychol. 20(4), 497–509 (2007)
Kim, H.T., Hong, S.K.: Situation awareness and maritime accident. J. Maritime Saf. Aut. (2013)
Hong, S.K.: Development of a cognitive work analysis method for safe ship navigation and a case study. J. Navig. Port Res. 37(3), 231–237 (2013)
Park, Y.S., Park, S.W., Cho, I.S.: A basic study on prediction module development of collision risk based on ship’s operator’s consciousness. J. Navig. Port Res. 39(3), 199–207 (2015)
Kim, Y.J., et al.: Development of a methodology for detecting intentional aggressive driving events using multi-agent driving simulations. J. Korean Soc. Transp. 36(1), 51–65 (2018)
Shin, S.H.: Agent-based SAF modeling tool for DEVS M&S. J. Korean Soc. Simul. 22(4), 49–55 (2013)
ICS. Bridge Procedures Guide, 5th Edition (2016)
IMO. Resolutions A.285 (VIII) Recommendation on Basic Principles and Operational Guidance Relating to Navigational Watchkeeping (2016)
MOF. Statistics of Maritime Accidents, Korean Maritime Safety Tribunal (2020)
Acknowledgments
This work was funded by grants from Korea Research Institute of Ships and Ocean Engineering (Grant – PES3600).
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Kim, H., Yang, Y., Hong, SK. (2020). Agent-Based Approach to Ship Officer’s Navigational Behavior Modeling for Maritime Traffic Analysis. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1212. Springer, Cham. https://doi.org/10.1007/978-3-030-50943-9_61
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DOI: https://doi.org/10.1007/978-3-030-50943-9_61
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