Skip to main content
Log in

Simulation and Assessment of Fire Evacuation Modes for Long Underwater Vehicle Tunnels

  • Published:
Fire Technology Aims and scope Submit manuscript

Abstract

The objective of this study is to propose a new method to evaluate the performance of different evacuation modes, and to find a rational evacuation mode for long underwater vehicle tunnels. In this study, a combined evacuation model (TPES) incorporating both a traffic flow module and a crowd evacuation module is proposed to simulate the integrated crowd evacuation with the effects of traffic flow, and the model is partially validated by a field evacuation test and a verified model Simulex. A vehicle tunnel was modeled to simulate fire-related traffic congestion and passenger evacuation, and then the evacuation performance index Im of three evacuation modes in different fire situations were calculated. The results revealed that the hybrid evacuation mode performs best among the three modes, with Im superior to other two modes by up to 26%. The transversal evacuation passage mode performs better than the longitudinal mode under the same conditions. However, the transversal and longitudinal modes can be equivalent when the passage spacing difference is within a range of 150–200 m. The critical spacing of the evacuation passage in a simple evacuation process lies in between 100 m and 350 m at confidence level of 90% for the transversal evacuation mode.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16

Similar content being viewed by others

References

  1. Zhao JW, Peng FL, Wang TQ, Zhang XY, Jiang BN (2016) Advances in master planning of urban underground space (UUS) in China. Tunn Undergr Space Technol 55:290–307

    Article  Google Scholar 

  2. Peng J, Peng FL (2018) A GIS-based evaluation method of underground space resources for urban spatial planning: part 1 methodology. Tunn Undergr Space Technol 74:82–95

    Article  Google Scholar 

  3. Peng J, Peng FL (2018) A GIS-based evaluation method of underground space resources for urban spatial planning: part 2 application. Tunn Undergr Space Technol 77:142–165

    Article  Google Scholar 

  4. Yao C-P (2008) Risk-based design research of escape channels in Shanghai Yangtze River Tunnel. Doctoral dissertation, Tongji University, Shanghai

  5. Shanghai Construction and Communications Commission (2008) Road Tunnel Design Code. 2008-07-01

  6. Yamada N, Ota Y (1999) Safety systems for the Trans-Tokyo Bay Highway tunnel project. Tunn Undergr Space Technol 14(1):3–12

    Article  Google Scholar 

  7. Gwynne S, Galea ER, Owen M, Lawrence PJ, Filippidis L (1999) A review of the methodologies used in evacuation modelling. Fire Mater 23(6):383–388

    Article  Google Scholar 

  8. Yang GS, Peng LM, Zhang JH, An YL (2006) Simulation of people’s evacuation in tunnel fire. J Cent South Univ Technol 13(3):307–312

    Article  Google Scholar 

  9. Ronchi E, Colonna P, Capote J, Alvear D, Berloco N, Cuesta A (2012) The evaluation of different evacuation models for assessing road tunnel safety analysis. Tunn Undergr Space Technol 30:74–84

    Article  Google Scholar 

  10. Caliendo C, Ciambelli P, De Guglielmo ML, Meo MG, Russo P (2012) Simulation of people evacuation in the event of a road tunnel fire. Proc Soc Behav Sci 53:178–188

    Article  Google Scholar 

  11. Valasek L, Glasa J (2013) Simulation of the course of evacuation in tunnel fire conditions by FDS + Evac. In: Proceedings of the 2013 international conference on applied mathematics and computational methods in engineering, pp 288–295

  12. Boer LC (2002). Behaviour by motorists on evacuation of a tunnel. Rapport TNO Human Factors

  13. Norén A, Winér J (2003) Modelling crowd evacuation from road and train tunnels-data and design for faster evacuations. LUTVDG/TVBB–5127–SE

  14. Zhang Y-C, Xiang Y, He C, et al (2016) Experimental study on pedestrian behavior and traffic capacity of cross passage in highway tunnel. J Southwest Jiaotiong Univ 4:615–620

    Google Scholar 

  15. Papageorgiou M, Schmidt G (1984) Freeway traffic modelling and control. In: Control in transportation systems, pp 195–202

  16. Yu L, Shi Z K (2007) Density waves in traffic flow model with relative velocity. Eur Phys J B 57(1):115–120

    Article  Google Scholar 

  17. Canter D, Breaux J, Sime J (1980) Domestic, multiple occupancy and hospital fires. In: Canter D (ed) Fires and Human Behaviour, chap 8. John Wiley & Sons, New York, pp 117–136

    Google Scholar 

  18. Sime JD (1985) Movement toward the familiar: person and place affiliation in a fire entrapment setting. Environ Behav 17(6):697–724

    Article  Google Scholar 

  19. Nilsson D, Johansson A (2009) Social influence during the initial phase of a fire evacuation—analysis of evacuation experiments in a cinema theatre. Fire Saf J 44(1):71–79

    Article  Google Scholar 

  20. Fridolf K, Nilsson D, Frantzich H (2013) Fire evacuation in underground transportation systems: a review of accidents and empirical research. Fire Technol 49(2):451–475

    Article  Google Scholar 

  21. Gehandler J (2015) Road tunnel fire safety and risk: a review. Fire Sci Rev 4(1):2

    Article  Google Scholar 

  22. Burstedde C, Klauck K, Schadschneider A, & Zittartz J (2001) Simulation of pedestrian dynamics using a two-dimensional cellular automaton. Phys A Stat Mech Appl 295(3):507–525

    Article  MATH  Google Scholar 

  23. Varas A, Cornejo MD, Mainemer D, Toledo B, Rogan J, Munoz V, Valdivia JA (2007) Cellular automaton model for evacuation process with obstacles. Phys A Stat Mech Appl 382(2):631–642

    Article  Google Scholar 

  24. Ezaki T, Yanagisawa D, Ohtsuka K, Nishinari K (2012) Simulation of space acquisition process of pedestrians using proxemic floor field model. Phys A Stat Mech Appl 391(1):291–299

    Article  Google Scholar 

  25. Wolfram S (2002) A new kind of science, vol 5. Wolfram Media, Champaign

    MATH  Google Scholar 

  26. Nagel K, Schreckenberg M (1992) A cellular automaton model for freeway traffic. J Phys I 2(12):2221–2229

    Google Scholar 

  27. Nagel K, Paczuski M (1995) Emergent traffic jams. Phys Rev E 51(4): 2909

    Article  Google Scholar 

  28. Takayasu M, Takayasu H (1993) 1/f noise in a traffic model. Fractals 1(04):860–866

    Article  MATH  Google Scholar 

  29. Benjamin SC, Johnson NF, Hui PM (1996) Cellular automata models of traffic flow along a highway containing a junction. J Phys A Math Gen 29(12):3119

    Article  MATH  Google Scholar 

  30. Helbing D, Molnar P (1995) Social force model for pedestrian dynamics. Phys Rev E 51(5):4282

    Article  Google Scholar 

  31. Helbing D, Molnar P (1998) Self-organization phenomena in pedestrian crowds. arXiv preprint arXiv:cond-mat/9806152

  32. Helbing D, Johansson A (2009) Pedestrian, crowd and evacuation dynamics. In: Meyers RA (ed) Encyclopedia of complexity and systems science. Springer, New York, pp 6476–6495

    Chapter  Google Scholar 

  33. Kuligowski ED, Peacock RD, Hoskins BL (2005) A review of building evacuation models. US Department of Commerce, National Institute of Standards and Technology, Gaithersburg

    Book  Google Scholar 

  34. Ronchi E, Kuligowski ED, Reneke PA, Peacock RD, Nilsson D (2013) The process of verification and validation of building fire evacuation models. US Department of Commerce, National Institute of Standards and Technology, Gaithersburg

    Book  Google Scholar 

  35. Guide, S. U. 6.0 (2012) Integrated environmental solutions limited

  36. Li W-P, Xu Y, Liao S-M (2012) Discussion and modification of RSET calculation method in road tunnel fire. China Saf Sci J 22(9):43–50

    Google Scholar 

  37. Xiang Y, Cao Y-L, Chen S-M, et al (2015) Research on the equivalent spacing for horizontal and vertical evacuation channel of underwater road tunnel. In: Proceedings of the 2015 international symposium on fire engineering technology. Science and Technology Information Bureau of Ministry of Public Security

  38. Cao Y-L (2016) Research on experiment for vertical evacuation of underwater highway tunnel with large cross-section. Master’s thesis, Southwest Jiao Tong University

  39. Zhang X, Xu Z-S, Ni T-X, et al (2011) Research on evacuation mode of underwater highway tunnel during fire. In: Proceedings of 2011 annual meeting of science and technology of China Fire Protection Association

  40. Xu Y, Liao S-M, Li W-P, et al (2012) Risk assessment on escape distance in road tunnel fire. China Civ Eng J 45(12):155–161

    Google Scholar 

Download references

Acknowledgements

The financial support from the National Basic Research Program Project (No. 2015CB057806) and Research Projects (Nos. 16DZ1200202, 17DZ1203804) from Shanghai Committee of Science and Technology are gratefully appreciated.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shaoming Liao.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xu, Y., Liao, S. & Liu, M. Simulation and Assessment of Fire Evacuation Modes for Long Underwater Vehicle Tunnels. Fire Technol 55, 729–754 (2019). https://doi.org/10.1007/s10694-018-0798-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10694-018-0798-8

Keywords

Navigation