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http://dx.doi.org/10.5394/KINPR.2019.43.4.237

Analysis of Seafarers' Behavioral Error on Collision Accidents  

Yim, Jeong-Bin (Division of Navigation Science, Korea Maritime & Ocean University)
Publication Information
Journal of Navigation and Port Research / v.43, no.4, 2019 , pp. 237-242 More about this Journal
Abstract
Behavioral errors of the seafarers are one of the major causes of collisions and are usually corrected through education and training. To correct this behavioral error, the structure in which the behavioral error occurs needs to be identified and analyzed. For this purpose, behavior observation data were obtained through ship maneuvering simulation for collision encounters. The 9-state behavior classification frame proposed by Reason was used for the behavior observation and 50 university students were involved in the experiment. Behavioral analysis used the behavioral model of collision avoidance success and failure, which was developed from the 9-state Left-to-Right Hidden Markov modeling technique. As a result of the experiment, the difference between behaviors of success and failure of collision avoidance was clearly identified, and the linkage between 9-state behaviors, required to prevent collision, was derived.
Keywords
Collision Accidents; Collision Avoidance; Seafarer; Behavioral Errors; Hidden Markov Models;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 Allianz(2018), Safety and Shipping Review 2018, Allianz Global Corporate & Specialty(AGCS), 10.
2 Forney, G. D.(1973), The viterbi algorithm, Proceedings of the IEEE, 61(3), 268-278.   DOI
3 Konsberg(2019), K-SIM NAVIGATION, https://www.kongsberg.com/digital/products/maritime-simulation/k-sim-navigation(accessed on 27 May 2019).
4 McCallum, A.(2004), Hidden Markov Models Baum Welch Algorithm.
5 Park, D. J., Yang, H. S. and Yim, J. B.(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.
6 Phan, M. T., Fremont, V., Thouvenin, I., Sallak, M. and Cherfaoui, V.(2015), Estimation of driver awareness of pedestrian based on Hidden Markov Model. IEEE Intelligent Vehicles Symposium(IV), pp. 970-975.
7 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, (3), pp. 257-266.
8 Rasmussen, J. and Vicente, K. J.(1989), Coping with human errors through system design: implications for ecological interface design, International Journal of Man-Machine Studies, 31(5), pp. 517-534.   DOI
9 Rabiner, L. R. and Juang, B. H.(1986), An introduction to hidden Markov models. ieee assp magazine, 3(1), pp. 4-16.   DOI
10 Rabiner, L. R.(1989), A tutorial on hidden Markov models and selected applications in speech recognition, Proceedings of the IEEE, 77(2), pp. 257-286.   DOI
11 Reason, J.(2000), Human error: Models and management, BMJ, 320, pp. 768-770.   DOI
12 Viterbi, A.(1967), Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE transactions on Information Theory, 13(2), pp. 260-269.   DOI
13 Yim, J. B.(2012), Probability Based Risk Evaluation Techniques for the Small-Sizes Sea Floater, Journal of Korean Navigation and Port Research, Vol. 36, No. 10, pp. 795-801.   DOI
14 Yim, J. B. and Yang, Y. J.(2013), Estimating Cumulative Distribution Functions with Maximum Likelihood to Sample Data Sets of a Sea Floater Model, Journal of Korean Navigation and Port Research, Vol. 37, No. 5, pp. 453-462.   DOI
15 Yim, J. B., Kim, D. S. and Park, D. J.(2018), Modeling perceived collision risk in vessel encounter situations, Ocean Engineering, 166, pp. 64-75.   DOI
16 Youn, I. H., Park, D. J. and Yim, J. B.(2019), Analysis of Lookout Activity in a Simulated Environment to Investigate Maritime Accidents Caused by Human Error, Applied Sciences, 9(1), 4, pp. 1-10.   DOI