Skip to main content

Research on Emergency Evacuation Route Choice in the Campus

  • Conference paper
  • First Online:
  • 967 Accesses

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 503))

Abstract

In order to explore the optimal route choice for emergency evacuation in the campus, we propose a novel route choice method based on brittle characteristics of campus system and improved ant colony algorithm. Both optimal and worst-case emergency evacuation routes are simulated in the campus of Ningbo University of Technology. From the simulation, the length of optimal and worse-case evacuation routes between the starting point and eight exits can be obtained by adjusting the importance value of trip distance and the degree of conformity, under the condition of static relative importance of pheromone concentration to graph G. The optimal route of emergency evacuation in the campus can be obtained when the importance of trip distance is above 5 and the degree of conformity is above 0.3; while the worse-case route is obtained with the importance of trip distance above 5 and the degree of conformity below 0.5.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Guo R-Y, Huang H-J, Wong SC (2012) Route choice in pedestrian evacuation under conditions of good and zero visibility: Experimental and simulation results. Transp Res Part B: Methodol 46(6):669–686

    Article  Google Scholar 

  2. Pan X, Han CS, Dauber K et al (2007) A multi-agent based framework for the simulation of human and social behaviors during emergency evacuations. AI & Soc 22(2):113–132

    Article  Google Scholar 

  3. Wang A, Dong B, Yin B et al (2012) Model and simulation on passenger behaviors in comprehensive railway passenger hubs. J Transp Syst Eng Inf Technol 5(1):026–035

    Google Scholar 

  4. Zhang Q, Han B, Li D (2008) Modeling and simulation of passenger alighting and boarding movement in Beijing metro stations. Transp Res Part C: Emerg Technol 16(5):635–649

    Article  Google Scholar 

  5. Syed AT, Hassanain MA (2013) A simulation model for emergency evacuation time of a library facility using evacnet. Struct Surv 31(2):75–92

    Article  Google Scholar 

  6. Helbing D, Molnar P (1995) Social force model for pedestrian dynamics. Phys Rev E 51(5):4282–4297

    Article  Google Scholar 

  7. Seyfried A, Steffen B, Lippert T (2006) Basics of modelling the pedestrian flow. Phys A 368(1):232–238

    Article  Google Scholar 

  8. Li Q, Jin H, Lin D (2005) The model and analyzing method for complex system’s brittleness. Syst Eng 23(1):9–12

    Google Scholar 

  9. Wang S, Wang Y (2011) Causation analysis of complex system safety accident based on brittle structure collapse. China Saf Sci J 21(5):138–142

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jibiao Zhou .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Guo, L., Zhou, J., Dong, S., Zhang, S., Xu, F. (2019). Research on Emergency Evacuation Route Choice in the Campus. In: Wang, W., Bengler, K., Jiang, X. (eds) Green Intelligent Transportation Systems. GITSS 2017. Lecture Notes in Electrical Engineering, vol 503. Springer, Singapore. https://doi.org/10.1007/978-981-13-0302-9_27

Download citation

  • DOI: https://doi.org/10.1007/978-981-13-0302-9_27

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-0301-2

  • Online ISBN: 978-981-13-0302-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics