Technical Papers
Jan 18, 2023

Identifying the Most Critical Evacuation Links Based on Road User Vulnerabilities

Publication: Natural Hazards Review
Volume 24, Issue 2

Abstract

As one of the principal lifeline systems, transportation networks are crucial for evacuation during extreme weather events like hurricanes, and critical network links must remain intact. The conventional evaluation measures prioritize to achieve the maximum system efficiencies, and therefore they estimate the functional criticality of a road network using measures such as travel time increase or throughput reduction caused by a link disruption. This study asks a fundamental question on equity achievement of such measures and develops a new framework to incorporate road users’ vulnerabilities in identifying critical network links. This study introduces new evaluation measures that integrate the most vulnerable zones for evacuation prioritization based on social, environmental, and economic vulnerabilities. Results show that the critical links for the vulnerable population during an evacuation are not always identified by conventional link-based measures that emphasize overall system efficiencies. Among the links selected as critical using the throughput measure, only 25% serve socially vulnerable communities and 38% serve environmentally vulnerable populations. This highlights the importance of considering road users’ vulnerability when prioritizing resources to strengthen the links since a link disruption may cause more significant consequences for vulnerable road users. Decision-making to identify critical links and minimize the impact of disruptions remains critical to distribute resources more effectively during an emergency and support the timely and safe evacuation of vulnerable populations that should be prioritized to achieve more equitable evacuation and disaster responses. An online interactive map is developed based on the results of this study to show the exact location of the critical links and other important metrics.

Practical Applications

In general, network links that carry higher traffic volume and ensure connectivity to isolated subnetworks represent critical links because disruptions on the links would impact more people, with a greater magnitude of travel time increase from rerouting or rescheduling. However, the individuals and communities that use the infrastructure determine the importance of the road links during extreme weather events. If a certain link serves at-risk communities (e.g., lower income or older population) for hurricane evacuation, the link should be considered critical regardless of its total traffic volume or impact on travel time if disrupted. These links must be resilient to save lives within the neighborhood, facilitate the evacuation of vulnerable groups, and strengthen the region’s overall resiliency. The proposed research identifies the criticality of network links by identifying the community impacts of network disruption. In particular, this study focuses on developing a framework to determine the critical network links based on the vulnerability or importance of communities in a hurricane-prone area using three vulnerability measures and compares the results with the outputs of traditional measures.

Get full access to this article

View all available purchase options and get full access to this article.

Data Availability Statement

The following data that support the findings of this study are available from the corresponding author upon reasonable request, including socioeconomic and demographic data of census tracts in the study area, Hurricane Harvey disruption data, estimated evacuation rates for the census tracts in the study area, and trip generation and distribution data.

Acknowledgments

This project was funded by the TranSET (20PUTA28), a USDOT University Transportation Center.

References

Alawadi, R., P. Murray-Tuite, and R. Bian. 2022. “Determinants of departure timing for Hurricane Matthew and anticipated consistency in future evacuation departures.” Nat. Hazard. Rev. 23 (2): 4022005. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000553.
Arce, R. S. C., M. Onuki, M. Esteban, and T. Shibayama. 2017. “Risk awareness and intended tsunami evacuation behaviour of international tourists in Kamakura City, Japan.” Int. J. Disaster Risk Reduct. 23 (Jun): 178–192. https://doi.org/10.1016/j.ijdrr.2017.04.005.
Arctur, D. 2018. “Harvey flood data collections.” Accessed May 23, 2021. https://www.hydroshare.org/resource/12e69ee668124fdf833b29b5167e03c3/.
Berdica, K., and L.-G. Mattsson. 2007. “Vulnerability: A model-based case study of the road network in Stockholm.” In Critical infrastructure, 81–106. Berlin: Springer.
Bian, R., P. Murray-Tuite, P. Edara, and K. Triantis. 2022. “Household hurricane evacuation plan adaptation in response to estimated travel delay provided prior to departure.” Nat. Hazard. Rev. 23 (3): 4022010. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000557.
Bian, R., C. G. Wilmot, R. Gudishala, and E. J. Baker. 2019. “Modeling household-level hurricane evacuation mode and destination type joint choice using data from multiple post-storm behavioral surveys.” Transp. Res. Part C Emerging Technol. 99 (Jan): 130–143. https://doi.org/10.1016/j.trc.2019.01.009.
Bish, D. R. 2011. “Planning for a bus-based evacuation.” OR Spectrum 33 (3): 629–654.https://doi.org/10.1007/s00291-011-0256-1.
Bowser, G. 2013. Determining the differences in hurricane perception and evacuation behavior in the elderly of South Carolina. Columbia, SC: Univ. of South Carolina.
Burnside, R. 2006. “Leaving the big easy: An examination of the hurricane evacuation behavior of New Orleans residents before Hurricane Katrina.” J. Public Manage. Soc. Policy 12 (2): 49–61.
Burnside, R., D. S. Miller, and J. D. Rivera. 2007. “The impact of information and risk perception on the hurricane evacuation decision-making of greater New Orleans residents.” Sociol. Spectrum 27 (6): 727–740. https://doi.org/10.1080/02732170701534226.
CDC (Centers for Disease Control and Prevention). 2022. “CDC/ATSDR SVI data and documentation download.” Accessed May 23, 2021. https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html.
Cheng, G., C. G. Wilmot, and E. J. Baker. 2008. “A destination choice model for hurricane evacuation.” In Proc., 87th Annual Meeting Transportation Research Board, 13–17. Washington, DC: Transportation Research Board.
Cheng, G., C. G. Wilmot, and E. J. Baker. 2011. “Dynamic gravity model for hurricane evacuation planning.” Transp. Res. Rec. 2234 (1): 125–134. https://doi.org/10.3141/2234-14.
DeYoung, S. E., T. Wachtendorf, R. A. Davidson, K. Xu, L. Nozick, A. K. Farmer, and L. Zelewicz. 2016. “A mixed method study of hurricane evacuation: Demographic predictors for stated compliance to voluntary and mandatory orders.” Environ. Hazard. 15 (2): 95–112. https://doi.org/10.1080/17477891.2016.1140630.
Dow, K., and S. L. Cutter. 2002. “Emerging hurricane evacuation issues: Hurricane Floyd and South Carolina.” Nat. Hazard. Rev. 3 (1): 12–18. https://doi.org/10.1061/(asce)1527-6988(2002)3:1(12).
Filabadi, M. D., and P. Bagheri. 2021. “Robust-and-cheap framework for network resilience: A novel mixed-integer formulation and solution method.” Preprint, submitted April 24, 2015. https://doi.org/10.48550/arXiv.2110.09694.
Flanagan, B. E., E. W. Gregory, E. J. Hallisey, J. L. Heitgerd, and B. Lewis. 2011. “A social vulnerability index for disaster management.” J. Homeland Security Emerging Manage. 8 (1): 11. https://doi.org/10.2202/1547-7355.1792.
Geophysical Fluid Dynamics Laboratory. 2022. Global warming and hurricanes: An overview of current research results. Princeton, NJ: Geophysical Fluid Dynamics Laboratory.
Goodie, A. S., A. R. Sankar, and P. Doshi. 2019. “Experience, risk, warnings, and demographics: Predictors of evacuation decisions in Hurricanes Harvey and Irma.” Int. J. Disaster Risk Reduct. 41 (Dec): 101320. https://doi.org/10.1016/j.ijdrr.2019.101320.
Hasan, S., S. Ukkusuri, H. Gladwin, and P. Murray-Tuite. 2010. “Behavioral model to understand household-level hurricane evacuation decision making.” J. Transp. Eng. 137 (5): 341–348. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000223.
Helderop, E., and T. H. Grubesic. 2019. “Flood evacuation and rescue: The identification of critical road segments using whole-landscape features.” Transp. Res. Interdiscip. Perspect. 3 (Mar): 100022. https://doi.org/10.1016/j.trip.2019.100022.
Hong, B., B. J. Bonczak, A. Gupta, and C. E. Kontokosta. 2021. “Measuring inequality in community resilience to natural disasters using large-scale mobility data.” Nat. Commun. 12 (1): 1–9. https://doi.org/10.1038/s41467-021-22160-w.
Horney, J. A. 2009. Hurricane evacuation failure: The role of social cohesion, social capital, and social control. Chapel Hill, NC: Univ. of North Carolina.
Huang, S.-K., M. K. Lindell, and C. S. Prater. 2016. “Who leaves and who stays? A review and statistical meta-analysis of hurricane evacuation studies.” Environ. Behav. 48 (8): 991–1029. https://doi.org/10.1177/0013916515578485.
Huang, S.-K., M. K. Lindell, C. S. Prater, H.-C. Wu, and L. K. Siebeneck. 2012. “Household evacuation decision making in response to Hurricane Ike.” Nat. Hazard. Rev. 13 (4): 283–296. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000074.
Jenelius, E., T. Petersen, and L. G. Mattsson. 2006. “Importance and exposure in road network vulnerability analysis.” Transp. Res. Part A Policy Pract. 40 (7): 537–560. https://doi.org/10.1016/J.TRA.2005.11.003.
Jiang, Y., Z. Li, and S. L. Cutter. 2021. “Social distance integrated gravity model for evacuation destination choice.” Int. J. Digital Earth 14 (8): 1004–1018. https://doi.org/10.1080/17538947.2021.1915396.
Kaisar, E. I., L. Hess, and A. B. P. Palomo. 2012. “An emergency evacuation planning model for special needs populations using public transit systems.” J. Public Transp. 15 (2): 45–69. https://doi.org/10.5038/2375-0901.15.2.3.
Kharazi, B. A., and A. H. Behzadan. 2021. “Flood depth mapping in street photos with image processing and deep neural networks.” Comput. Environ. Urban Syst. 88 (12): 101628. https://doi.org/10.1016/j.compenvurbsys.2021.101628.
Kim, S., and H. Yeo. 2016. “A flow-based vulnerability measure for the resilience of urban road network.” Proc. Soc. Behav. Sci. 218 (May): 13–23. https://doi.org/10.1016/j.sbspro.2016.04.006.
Land Parcels. 2019. Strategic mapping program (StratMap). Austin, TX: Texas Natural Resources Information System.
Lim, G. J., M. Rungta, and M. R. Baharnemati. 2015. “Reliability analysis of evacuation routes under capacity uncertainty of road links.” IIE Trans. 47 (1): 50–63. https://doi.org/10.1080/0740817X.2014.905736.
Lindell, M. K., J. E. Kang, and C. S. Prater. 2011. “The logistics of household hurricane evacuation.” Nat. Hazard. 58 (3): 1093–1109. https://doi.org/10.1007/s11069-011-9715-x.
Lindell, M. K., P. Murray-Tuite, B. Wolshon, and E. J. Baker. 2018. Large-scale evacuation: The analysis, modeling, and management of emergency relocation from hazardous areas. London: CRC Press.
Lindell, M. K., and C. S. Prater. 2007. “Critical behavioral assumptions in evacuation time estimate analysis for private vehicles: Examples from hurricane research and planning.” J. Urban Plann. Dev. 133 (1): 18–29. https://doi.org/10.1061/(ASCE)0733-9488(2007)133:1(18).
Lu, Q.-C., Z.-R. Peng, and J. Zhang. 2015. “Identification and prioritization of critical transportation infrastructure: Case study of coastal flooding.” J. Transp. Eng. 141 (3): 4014082. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000743.
Maiwald, M. 2019. “Robust evacuation planning for urban areas.” In Operations research proceedings 2018, 23–28. Berlin: Springer.
Mesa-Arango, R., S. Hasan, S. V. Ukkusuri, and P. Murray-Tuite. 2013. “Household-level model for hurricane evacuation destination type choice using Hurricane Ivan data.” Nat. Hazard. Rev. 14 (1): 11–20. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000083.
Meyer, M. A., B. Mitchell, J. C. Purdum, K. Breen, and R. L. Iles. 2018. “Previous hurricane evacuation decisions and future evacuation intentions among residents of southeast Louisiana.” Int. J. Disaster Risk Reduct. 31 (5): 1231–1244. https://doi.org/10.1016/j.ijdrr.2018.01.003.
Morss, R. E., J. L. Demuth, J. K. Lazo, K. Dickinson, H. Lazrus, and B. H. Morrow. 2016. “Understanding public hurricane evacuation decisions and responses to forecast and warning messages.” Weather Forecasting 31 (2): 395–417. https://doi.org/10.1175/WAF-D-15-0066.1.
Nagurney, A., and Q. Qiang. 2007. “A transportation network efficiency measure that captures flows, behavior, and costs with applications to network component importance identification and vulnerability.” In Proc., POMS 18th Annual Conf. Miami: Production and Operations Management Society.
Sadri, A. M., S. V. Ukkusuri, and H. Gladwin. 2017. “The role of social networks and information sources on hurricane evacuation decision making.” Nat. Hazard. Rev. 18 (3): 4017005. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000244.
Sadri, A. M., S. V. Ukkusuri, P. Murray-Tuite, and H. Gladwin. 2014a. “Analysis of hurricane evacuee mode choice behavior.” Transp. Res. Part C Emerging Technol. 48 (Aug): 37–46. https://doi.org/10.1016/j.trc.2014.08.008.
Sadri, A. M., S. V. Ukkusuri, P. Murray-Tuite, and H. Gladwin. 2014b. “How to evacuate: Model for understanding the routing strategies during hurricane evacuation.” J. Transp. Eng. 140 (1): 61–69. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000613.
Scott, D. M., D. C. Novak, L. Aultman-Hall, and F. Guo. 2006. “Network robustness index: A new method for identifying critical links and evaluating the performance of transportation networks.” J. Transp. Geogr. 14 (3): 215–227. https://doi.org/10.1016/j.jtrangeo.2005.10.003.
Smith, S. K., and C. McCarty. 2009. “Fleeing the storm(s): An examination of evacuation behavior during Florida’s 2004 hurricane season.” Demography 46 (1): 127–145. https://doi.org/10.1353/DEM.0.0048.
Solis, D., M. Thomas, and D. Letson. 2010. “An empirical evaluation of the determinants of household hurricane evacuation choice.” J. Dev. Agric. Econ. 2 (5): 188–196. https://doi.org/10.5897/JDAE.9000010.
Stamos, I., J. M. S. Grau, E. Mitsakis, G. Aifadopoulou, and Y.-C. Chiu. 2013. “On criticality assessment based evacuation modeling: Empirical findings.” J. Traffic Logis. Eng. 1 (2): 153–158. https://doi.org/10.12720/jtle.1.2.153-158.
Sullivan, J. L., D. C. Novak, L. Aultman-Hall, and D. M. Scott. 2010. “Identifying critical road segments and measuring system-wide robustness in transportation networks with isolating links: A link-based capacity-reduction approach.” Transp. Res. Part A Policy Pract. 44 (5): 323–336. https://doi.org/10.1016/J.TRA.2010.02.003.
Taylor, M. A. P., S. V. C. Sekhar, and G. M. D’Este. 2006. “Application of accessibility based methods for vulnerability analysis of strategic road networks.” Networks Spatial Econ. 6 (3): 267–291. https://doi.org/10.1007/s11067-006-9284-9.
Thiede, B. C., and D. L. Brown. 2013. “Hurricane Katrina: Who stayed and why?” Population Res. Policy Rev. 32 (6): 803–824. https://doi.org/10.1007/S11113-013-9302-9.
Thompson, R. R., D. R. Garfin, and R. C. Silver. 2017. “Evacuation from natural disasters: A systematic review of the literature.” Risk Anal. 37 (4): 812–839. https://doi.org/10.1111/risa.12654.
Urbanik, T. 2000. “Evacuation time estimates for nuclear power plants.” J. Hazard. Mater. 75 (2–3): 165–180. https://doi.org/10.1016/S0304-3894(00)00178-3.
Wang, D. Z. W., H. Liu, W. Y. Szeto, and A. H. F. Chow. 2016. “Identification of critical combination of vulnerable links in transportation networks—A global optimisation approach.” Transp. Transp. Sci. 12 (4): 346–365. https://doi.org/10.1080/23249935.2015.1137373.
Whitehead, J. C., B. Edwards, M. Van Willigen, J. R. Maiolo, K. Wilson, and K. T. Smith. 2000. “Heading for higher ground: Factors affecting real and hypothetical hurricane evacuation behavior.” Global Environ. Change Part B: Environ. Hazards 2 (4): 133–142. https://doi.org/10.1016/S1464-2867(01)00013-4.
Zachry, B. C., W. J. Booth, J. R. Rhome, and T. M. Sharon. 2015. “A national view of storm surge risk and inundation.” Weather Clim. Soc. 7 (2): 109–117. https://doi.org/10.1175/WCAS-D-14-00049.1.

Information & Authors

Information

Published In

Go to Natural Hazards Review
Natural Hazards Review
Volume 24Issue 2May 2023

History

Received: May 2, 2022
Accepted: Nov 22, 2022
Published online: Jan 18, 2023
Published in print: May 1, 2023
Discussion open until: Jun 18, 2023

Permissions

Request permissions for this article.

Authors

Affiliations

Ph.D. Student, Dept. of Civil Engineering, Univ. of Texas at Arlington, 425 Nedderman Hall, Arlington, TX 76019 (corresponding author). ORCID: https://orcid.org/0000-0003-3267-1362. Email: [email protected]
Kate Kyung Hyun, Ph.D. [email protected]
Assistant Professor, Dept. of Civil Engineering, Univ. of Texas at Arlington, 425 Nedderman Hall, Arlington, TX 76019. Email: [email protected]
Stephen P. Mattingly, Ph.D. [email protected]
Professor, Dept. of Civil Engineering, Univ. of Texas at Arlington, 425 Nedderman Hall, Arlington, TX 76019. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share