IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v430y2015icp171-183.html
   My bibliography  Save this article

Analysis of dynamic road risk for pedestrian evacuation

Author

Listed:
  • Zhang, Nan
  • Huang, Hong
  • Su, Boni
  • Zhao, Jinlong

Abstract

Knowing the dynamic road risk for pedestrian evacuation and having an efficient evacuation plan play a very important role in the serious disasters such as earthquake, tsunami and hurricane. In this paper, the dynamic road risk for pedestrian evacuation in a densely populated area of Beijing was studied with consideration of different influencing factors. Firstly, the eight influencing factors including road width, node degree, safety betweenness, road resistor coefficient, building threat, pedestrian counterflow, illegal vehicle parking and traffic flow were considered to assess the road risk for pedestrian evacuation. Secondly, based on complex network theory, electric circuit theory and real situation of the roads, the comprehensive assessment function for road risk was developed quantitatively based on the eight influencing factors. Thirdly, we analyzed road risk for pedestrian evacuation considering different situations: current condition, regular condition, and optimal condition; the risk distribution maps were drawn to directly show the risk level. Through assessments, the roads with high risk for pedestrian evacuation were found, and an optimized evacuation plan was obtained and analyzed. This mathematical model can guide the emergency evacuation in real time. The process and the results are essential for improving the efficiency of evacuations which should considerably reduce the possibility of injuries, deaths and other losses in the disaster.

Suggested Citation

  • Zhang, Nan & Huang, Hong & Su, Boni & Zhao, Jinlong, 2015. "Analysis of dynamic road risk for pedestrian evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 171-183.
  • Handle: RePEc:eee:phsmap:v:430:y:2015:i:c:p:171-183
    DOI: 10.1016/j.physa.2015.02.082
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437115002058
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2015.02.082?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chen, Bi Yu & Lam, William H.K. & Sumalee, Agachai & Li, Qingquan & Li, Zhi-Chun, 2012. "Vulnerability analysis for large-scale and congested road networks with demand uncertainty," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 501-516.
    2. Hoogendoorn, Serge P. & van Wageningen-Kessels, Femke L.M. & Daamen, Winnie & Duives, Dorine C., 2014. "Continuum modelling of pedestrian flows: From microscopic principles to self-organised macroscopic phenomena," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 684-694.
    3. Cova, Thomas J. & Johnson, Justin P., 2003. "A network flow model for lane-based evacuation routing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(7), pages 579-604, August.
    4. Jenelius, Erik & Petersen, Tom & Mattsson, Lars-Göran, 2006. "Importance and exposure in road network vulnerability analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 537-560, August.
    5. Andrew A. Lovett & Julian P. Parfitt & Julii S. Brainard, 1997. "Using GIS in Risk Analysis: A Case Study of Hazardous Waste Transport," Risk Analysis, John Wiley & Sons, vol. 17(5), pages 625-633, October.
    6. Nan Zhang & Hong Huang & Boni Su & Hui Zhang, 2013. "Population evacuation analysis: considering dynamic population vulnerability distribution and disaster information dissemination," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 69(3), pages 1629-1646, December.
    7. Kirchner, Ansgar & Schadschneider, Andreas, 2002. "Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(1), pages 260-276.
    8. Widener, Michael J. & Horner, Mark W., 2011. "A hierarchical approach to modeling hurricane disaster relief goods distribution," Journal of Transport Geography, Elsevier, vol. 19(4), pages 821-828.
    9. Mark Horner & Michael Widener, 2011. "The effects of transportation network failure on people’s accessibility to hurricane disaster relief goods: a modeling approach and application to a Florida case study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 59(3), pages 1619-1634, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. N. Zhang & X. Ni & H. Huang & J. Zhao & M. Duarte & J. Zhang, 2016. "The impact of interpersonal pre-warning information dissemination on regional emergency evacuation," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(3), pages 2081-2103, February.
    2. N. Zhang & X. Y. Ni & H. Huang & J. L. Zhao & M. Duarte & J. Zhang, 2016. "The impact of interpersonal pre-warning information dissemination on regional emergency evacuation," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(3), pages 2081-2103, February.
    3. Zhang, N. & Ni, X.Y. & Huang, H. & Duarte, M., 2017. "Risk-based personal emergency response plan under hazardous gas leakage: Optimal information dissemination and regional evacuation in metropolises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 237-250.
    4. Zhang, N. & Huang, H. & Su, Boni, 2016. "Comprehensive analysis of information dissemination in disasters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 846-857.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Blake Walker & Cameron Taylor-Noonan & Alan Tabbernor & T’Brenn McKinnon & Harsimran Bal & Dan Bradley & Nadine Schuurman & John Clague, 2014. "A multi-criteria evaluation model of earthquake vulnerability in Victoria, British Columbia," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(2), pages 1209-1222, November.
    2. Dilsu Binnaz Ozkapici & Mustafa Alp Ertem & Haluk Aygüneş, 2016. "Intermodal humanitarian logistics model based on maritime transportation in Istanbul," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(1), pages 345-364, August.
    3. Kurmankhojayev, Daniyar & Li, Guoyuan & Chen, Anthony, 2024. "Link criticality index: Refinement, framework extension, and a case study," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    4. Korbmacher, Raphael & Dang, Huu-Tu & Tordeux, Antoine, 2024. "Predicting pedestrian trajectories at different densities: A multi-criteria empirical analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
    5. Bell, Michael G.H. & Kurauchi, Fumitaka & Perera, Supun & Wong, Walter, 2017. "Investigating transport network vulnerability by capacity weighted spectral analysis," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 251-266.
    6. Ling Zhang & Jingjing Hao & Xiaofeng Ji & Lan Liu, 2019. "Research on the Complex Characteristics of Freight Transportation from a Multiscale Perspective Using Freight Vehicle Trip Data," Sustainability, MDPI, vol. 11(7), pages 1-20, March.
    7. Rodríguez-Núñez, Eduardo & García-Palomares, Juan Carlos, 2014. "Measuring the vulnerability of public transport networks," Journal of Transport Geography, Elsevier, vol. 35(C), pages 50-63.
    8. Lindell, Michael K., 2008. "EMBLEM2: An empirically based large scale evacuation time estimate model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(1), pages 140-154, January.
    9. Xu, Qiancheng & Chraibi, Mohcine & Tordeux, Antoine & Zhang, Jun, 2019. "Generalized collision-free velocity model for pedestrian dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    10. Khademi, Navid & Babaei, Mohsen & Schmöcker, Jan-Dirk & Fani, Amirhossein, 2018. "Analysis of incident costs in a vulnerable sparse rail network – Description and Iran case study," Research in Transportation Economics, Elsevier, vol. 70(C), pages 9-27.
    11. Ahmadi, Morteza & Seifi, Abbas & Tootooni, Behnam, 2015. "A humanitarian logistics model for disaster relief operation considering network failure and standard relief time: A case study on San Francisco district," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 145-163.
    12. Baskaya, Serhat & Ertem, Mustafa Alp & Duran, Serhan, 2017. "Pre-positioning of relief items in humanitarian logistics considering lateral transhipment opportunities," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 50-60.
    13. Balijepalli, Chandra & Oppong, Olivia, 2014. "Measuring vulnerability of road network considering the extent of serviceability of critical road links in urban areas," Journal of Transport Geography, Elsevier, vol. 39(C), pages 145-155.
    14. Yamada, Takashi, 2022. "Generalizing the probability of reaching a destination in case of route blockage," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    15. Ahmad Mohamad El-Maissi & Sotirios A. Argyroudis & Fadzli Mohamed Nazri, 2020. "Seismic Vulnerability Assessment Methodologies for Roadway Assets and Networks: A State-of-the-Art Review," Sustainability, MDPI, vol. 13(1), pages 1-31, December.
    16. Milad Zamanifar & Timo Hartmann, 2020. "Optimization-based decision-making models for disaster recovery and reconstruction planning of transportation networks," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(1), pages 1-25, October.
    17. Hsieh, Cheng-Hsien & Feng, Cheng-Min, 2020. "The highway resilience and vulnerability in Taiwan," Transport Policy, Elsevier, vol. 87(C), pages 1-9.
    18. Özdamar, Linet & Ertem, Mustafa Alp, 2015. "Models, solutions and enabling technologies in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 244(1), pages 55-65.
    19. Gu, Yu & Chen, Anthony & Xu, Xiangdong, 2023. "Measurement and ranking of important link combinations in the analysis of transportation network vulnerability envelope buffers under multiple-link disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 118-144.
    20. Almotahari, Amirmasoud & Yazici, M. Anil, 2019. "A link criticality index embedded in the convex combinations solution of user equilibrium traffic assignment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 67-82.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:430:y:2015:i:c:p:171-183. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.