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Comparisons of Seafarers' Perception of Maritime and Onshore Traffic Conditions

  • Park, Deuk-Jin (Graduated School of Mokpo National Maritime University) ;
  • Kim, Hong-Tae (Korea Research Institute of Ships and Ocean Engineering) ;
  • Yang, Hyeong-Sun (Division of Navigation Science, Mokpo National Maritime University) ;
  • Yim, Jeong-Bin (Division of Navigation Science, Korea Maritime and Ocean University)
  • Received : 2019.05.08
  • Accepted : 2019.05.28
  • Published : 2019.05.31

Abstract

The purpose of this paper is to compare seafarers' behavior according to traffic conditions of a road and an onshore locations. Behaviors are classified into three categories: Skill-, Rule- and knowledge-based mode. Experimental data were collected using the questionnaires for navigators, working in a merchant ship. To compare the behaviors, we used the four analysis method; the degree of frequency, reliability test, correlation and linear regression. As a result of the study, it was found that Skill-based behavior shows more higher in the road traffic than the maritime traffic, and rule-based behavior shows more higher in the maritime traffic than the road traffic. Also, the behavior in the navigation situation showed statistical significance. Especially, in the case of Rule-based behavior, a high correlation between road and maritime was found. This study can be expected to apply to complementary system utilization between error management system of onshore and maritime traffic.

Keywords

References

  1. Banks, V. A., K. L. Plant and Stanton, N. A(2019), Driving aviation forward; contrasting driving automation and aviation automation, Theoretical Issues in Ergonomics Science, pp. 1-15.
  2. Chauvin C., J. P. Clostermann and Jean-Michel Hoc(2008), Situation Awareness and the Decision-Making Process in a Dynamic situation: Avoiding collisions at sea, Journal of cognitive engineering and decision making, Vol. 2, pp. 1-23. https://doi.org/10.1518/155534308X284345
  3. Drivalou, S. and N. Marmaras(2009), Supporting skill-, rule-, and knowledge-based behaviour through an ecological interface: An industry-scale application, International Journal of Industrial Ergonomics, Vol. 39(6), pp. 947-965. https://doi.org/10.1016/j.ergon.2009.08.012
  4. Embrey, D.(2005), Understanding human behaviour and error. Human Reliability Associates, Vol. 1(2005), pp. 1-10.
  5. Imbert, J. P., G. Granger, R. Benhacene, A. Golfetti, S. Bonelli and S. Pozzi(2015), Skill, Rule and Knowledge-based Behaviors Detection during Realistic ATM Simulations by Means of ATCOs' Brain Activity, SESARWPE.
  6. KMST(2018), Web site for the Investigation and Judgement Information Portal of Maritime Causalities, http://data.kmst.go.kr/kmst/verdict/verdictAbstract/selectVerdictabstract.do.
  7. Lee, J. G.(2012), MATLAB Recipes for statistical analysis, A-Jin, pp. 1-500.
  8. Lin, C. J., W. J. Shiang, C. Y. Chuang and J. L. Liou(2014), Applying the Skill-Rule-Knowledge Framework to Understanding Operator's Behaviors and Workload in Advanced Main Control Rooms, Nuclear Engineering and Design, Vol. 270, pp. 176-184. https://doi.org/10.1016/j.nucengdes.2013.12.051
  9. Norman, D. A.(1983), Some observations on mental models, Mental models, Vol. 7(112), pp. 7-14.
  10. Park, D. J., J. B. Yim and H. S. Yang(2018), A Study on Collision Avoidance Action in the Situation of Encountering Multiple Ships by the Reserve Officer, Journal of the Korean Society of Marine Environment & Safety, Vol. 23, No. 3, pp. 346-351. https://doi.org/10.7837/kosomes.2018.24.3.346
  11. Park, D. J., H. S. Yang and J. B. Yim(2019), A Study on the Estimation of Optimal Probability Distribution Function for Seafarers' Behavior Error, Journal of Korean Navigation and Port Research, Vol. 49, No. 1, pp. 1-8.
  12. Petridou, E. and M. Moustaki(2000), Human factors in the causation of road traffic crashes, European journal of epidemiology, Vol. 16(9), pp. 819-826. https://doi.org/10.1023/A:1007649804201
  13. Rasmussen, J.(1982), Human errors. A taxonomy for describing human malfunction in industrial installations, Journal of occupational accidents, Vol. 4(2-4), pp. 311-333. https://doi.org/10.1016/0376-6349(82)90041-4
  14. Rasmussen, J.(1983), Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models, IEEE transactions on systems, man, and cybernetics, Vol. 3, pp. 257-266. https://doi.org/10.1109/TSMC.1973.4309214
  15. Reason, J.(1990), Human Error, Cambridge University, New York, USA.
  16. Reason, J., A. Manstead, S. Stradling, J. Baxter and K. Campbell(1990), Errors and violations on the roads: a real distinction?. Ergonomics, Vol 33(10-11), pp. 1315-1332. https://doi.org/10.1080/00140139008925335
  17. Reason, J.(2016), Managing the risks of organizational accidents, Routledge.
  18. Stanton, N. A. and P. M. Salmon(2009), Human error taxonomies applied to driving: A generic driver error taxonomy and its implications for intelligent transport systems, Safety Science, Vol. 47(2), pp. 227-237. https://doi.org/10.1016/j.ssci.2008.03.006
  19. Shirmohammadi, H., F. Hadadi and M. Saeedian(2019). Clustering Analysis of Drivers Based on Behavioral Characteristics Regarding Road Safety, International Journal of Civil Engineering, pp. 1-14. https://doi.org/10.1007/s40999-019-00473-8
  20. Salmon, P. M., M. G. Lenne, N. A. Stanton, D. P. Jenkins and G. H. Walker(2010), Managing error on the open road: The contribution of human error models and methods, Safety science, Vol. 48(10), pp. 1225-1235. https://doi.org/10.1016/j.ssci.2010.04.004
  21. Yim, J. B., W. J. Yang and H. T. Kim(2014), Marine Accident Analysis - A Guiide to Analysis, Evaluation, Prediction and Management of Marine Accidents in the Maritime Transportation -, Jeilgihyok, ISBN 978-89-97005-42-0, pp. 1-392.
  22. Yim, J. B.(2017a), A Study on the Reduction of Common Words to Classify causes of Marine Accidents, Korean Institute of Navigation and Port Research, Vol. 41(3), pp. 109-117. https://doi.org/10.5394/KINPR.2017.41.3.109
  23. Yim, J. B.(2017b), A Study on the Analysis and Identification of Seafarers' Skill-Rule-Knowledge Inherent in Maritime Accidents, Journal of the Korean Society of Marine Environment & Safety, Vol. 23(3), pp. 224-230. https://doi.org/10.7837/kosomes.2017.23.3.224
  24. Yim, J. B., D. S. Kim and D. J. Park(2018), Modeling perceived collision risk in vessel encounter situations, Ocean Engineering, Vol. 166, pp. 64-75. https://doi.org/10.1016/j.oceaneng.2018.08.003
  25. Youn, I. H., D. J. Park and J. B. Yim(2019), Analysis of Lookout Activity in a Simulated Environment to Investigate Maritime Accidents Caused by Human Error, Applied Sciences, Vol. 9(1), pp. 1-10. https://doi.org/10.3390/app9010001

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