Maritime Emergency Simulation System (MESS) - A Virtual Decision Support Platform for Emergency Response of Maritime Accidents

Bing Wu, Xinping Yan, Yang Wang, Xiaoyang Wei

Abstract

This paper presents a maritime emergency simulation system (MESS) for the improvement of emergency response skills of participants of search and rescue (SAR). Firstly, the system architecture, software and hardware system are proposed, and the components and function are also introduced. Thus the virtual environment based on virtual reality is established with the distinguishing advantages of immersive, intuitiveness, low-cost and interactive. Four main types of accident are implemented in this system, to accomplish this, five key technologies which have been introduced in MESS are also proposed, among these technologies, some could enhance the immersive such as the traffic flow simulation and accident logic, while some advanced technologies could improve the efficiency and feasibility if being applied to the actual SAR. Moreover, the application domain including skills improvement of participants in SAR, accident investigation, adaptive decision-making based on scenario analysis, human reliability in emergency response are also discussed. Finally, the conclusions and further research are remarked.

References

  1. AbuBakar A, Dow R.S. 2013. Simulation of ship grounding damage using the finite element method[J]. International Journal of Solids and Structures, 50(5): 623-636.
  2. Antão P, Almeida T, Jacinto C, et al. 2008a.Causes of occupational accidents in the fishing sector in Portugal[J]. Safety Science, 46(6): 885-899.
  3. Antão P, Guedes Soares C. 2008b.Causal factors in accidents of high-speed craft and conventional oceangoing vessels[J].Reliability Engineering & System Safety, 93(9): 1292-1304.
  4. Besnard D, Hollnagel E. 2014. I want to believe: some myths about the management of industrial safety [J]. Cognition, Technology & Work, 16(1): 13-23.
  5. Breivik Ø, Allen A.A. 2008.An operational search and rescue model for the Norwegian Sea and the North Sea [J]. Journal of Marine Systems, 69(1): 99-113.
  6. De Oliveira L.B., Camponogara E. 2010.Multi-agent model predictive control of signaling split in urban traffic networks [J]. Transportation Research Part C: Emerging Technologies, 18(1): 120-139.
  7. Ehlers S, Tabri K. 2012. A combined numerical and semianalytical collision damage assessment procedure [J]. Marine Structures, 28(1): 101-119.
  8. Feng M, Li Y. 2012.Ship intelligent collision avoidance based on Maritime Police Warships Simulation System[C]//Electrical & Electronics Engineering (EEESYM), 2012 IEEE Symposium on. IEEE,:293-296.
  9. Goerlandt F, Kujala P. 2011. Traffic simulation based ship collision probability modeling [J].Reliability Engineering & System Safety, 96(1): 91-107.
  10. Jakob M, Vanek O, Pechoucek M. 2011.Using agents to improve international maritime transport security [J]. Intelligent Systems, IEEE, 26(1): 90-96.
  11. Jin, D., Thunberg, E., 2005.An analysis of fishing vessel accidents in fishing areas off the northeastern United States. Safety Science ,43( 8) ,523-540.
  12. Knapp S, Bijwaard G, Heij C. 2011.Estimated incident cost savings in shipping due to inspections [J]. Accident Analysis & Prevention, 43(4): 1532-1539.
  13. Kurowski M, Lampe B. 2014. AGaPaS: A new approach for search-and-rescue-operations at sea[J]. Journal of Engineering for the Maritime Environment: 1-9.
  14. Li S, Meng Q, Qu X. 2012.An overview of maritime waterway quantitative risk assessment models[J]. Risk Analysis, 32(3): 496-512.
  15. Mazaheri A, Montewka J, Kujala P. 2013.Modeling the risk of ship grounding-a literature review from a risk management perspective [J]. WMU Journal of Maritime Affairs: 1-29.
  16. Montewka J, Hinz T, Kujala P, et al. 2010.Probability modelling of vessel collisions [J].Reliability Engineering & System Safety, 95(5): 573-589.
  17. Montewka J, Ehlers S, Goerlandt F, et al. 2014. A framework for risk assessment for maritime transportation systems-A case study for open sea collisions involving RoPax vessels [J]. Reliability Engineering & System Safety, 124: 142-157.
  18. Mou J.M., Tak C, Ligteringen H. 2010.Study on collision avoidance in busy waterways by using AIS data [J]. Ocean Engineering, 37(5): 483-490.
  19. Ni Z, Qiu Z, Su T C. 2010. On predicting boat drift for search and rescue [J].Ocean Engineering, 37(13): 1169-1179.
  20. Pedersen P.T. 2010. Review and application of ship collision and grounding analysis procedures [J]. Marine Structures, 23(3): 241-262.
  21. Prabhu Gaonkar R.S., Xie M, Ng K.M., et al. 2011.Subjective operational reliability assessment of maritime transportation system[J]. Expert Systems with Applications, 38(11): 13835-13846.
  22. Rizzo A, Parsons T.D., Lange B, et al. 2011.Virtual reality goes to war: a brief review of the future of military behavioral healthcare [J].Journal of clinical psychology in medical settings, 18(2): 176-187.
  23. Salimifard K, Wright M. 2001.Petri net-based modelling of workflow systems: An overview [J].European journal of operational research, 134(3): 664-676.
  24. Shichuan S, Liang W, Yuhong N, et al. 2012. Numerical computation and characteristic analysis on the center shift of fire whirls in a ship engine room fire[J]. Safety science, 50(1): 12-18.
  25. Sormunen O.V.E., Ehlers S, Kujala P. 2013. Collision consequence estimation model for chemical tankers[J]. Journal of Engineering for the Maritime Environment, 227(2): 98-106.
  26. Svensson H. 2009.Protection of bridge piers against ship collision [J]. Steel Construction, 2(1): 21-32.
  27. Vanek O, Jakob M, Hrstka O, et al. 2013.Agent-based model of maritime traffic in piracy-affected waters [J].Transportation Research Part C: Emerging Technologies, 36: 157-176.
  28. Varela J.M., Soares C.G. 2007. A virtual environment for decision support in ship damage control [J]. Computer Graphics and Applications, IEEE, 27(4): 58-69.
  29. Wang J. 2001. The current status and future aspects in formal ship safety assessment [J]. Safety Science, 38(1): 19-30.
  30. Wang, J. Rosca, D. Tepfenhart, W. et al. 2008. Dynamic workflow modeling and analysis in incident command systems [J]. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 38(5): 1041-1055.
  31. Wang, J. Tepfenhart, W. & Rosca, D. 2009. Emergency response workflow resource requirements modeling and analysis [J]. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 39(3): 270-283.
  32. Wang, J. 2012. Emergency Healthcare Workflow Modeling and Timeliness Analysis [J]. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 42(6): 1323-1331.
  33. Wang J, Chu G, Li K. 2013. Study on the uncertainty of the available time under ship fire based on Monte Carlo sampling method [J]. China Ocean Engineering, 27: 131-140.
  34. Wang Y, Zhang J, Chen X, et al. 2013. A spatial-temporal forensic analysis for inland water ship collisions using AIS data [J]. Safety science, 57: 187-202.
  35. Watanabe N, Maki Y, Shimomura T, et al. 2011. Hardware-in-the-loop simulation system for duplication of actual running conditions of a multiple-car train consist[J]. Quarterly Report of RTRI, 52(1):1-6.
  36. Xu Z. 2007. A method for multiple attribute decision making with incomplete weight information in linguistic setting[J].Knowledge-Based Systems, 20(8): 719-725.
  37. Yang J.B., Singh Madan G. 1994. An evidential reasoning approach for multiple-attribute decision making with uncertainty[J]. Systems, Man and Cybernetics, IEEE Transactions on, 24(1): 1-18.
  38. Yu Y, Kamel A.E., Gong G. 2013. Modeling intelligent vehicle agent in virtual reality traffic simulation system[C]//Systems and Computer Science (ICSCS), 2013 2nd International Conference on. IEEE, 274- 279.
  39. Zhang D, Yan X. P., Yang Z.L., et al. 2013.Incorporation of formal safety assessment and Bayesian network in navigational risk estimation of the Yangtze River[J]. Reliability Engineering & System Safety, 118: 93- 105.
Download


Paper Citation


in Harvard Style

Wu B., Yan X., Wang Y. and Wei X. (2014). Maritime Emergency Simulation System (MESS) - A Virtual Decision Support Platform for Emergency Response of Maritime Accidents . In Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-758-038-3, pages 155-162. DOI: 10.5220/0005039401550162


in Bibtex Style

@conference{simultech14,
author={Bing Wu and Xinping Yan and Yang Wang and Xiaoyang Wei},
title={Maritime Emergency Simulation System (MESS) - A Virtual Decision Support Platform for Emergency Response of Maritime Accidents},
booktitle={Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2014},
pages={155-162},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005039401550162},
isbn={978-989-758-038-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Maritime Emergency Simulation System (MESS) - A Virtual Decision Support Platform for Emergency Response of Maritime Accidents
SN - 978-989-758-038-3
AU - Wu B.
AU - Yan X.
AU - Wang Y.
AU - Wei X.
PY - 2014
SP - 155
EP - 162
DO - 10.5220/0005039401550162