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Identifying critical elements of road infrastructure using cascading impact assessment

    David Rehak Affiliation
    ; David Patrman Affiliation
    ; Veronika Brabcová Affiliation
    ; Zdeněk Dvořák Affiliation

Abstract

Road transport is a key means of transporting people and cargo on land. Its particular advantages are speed and operability, which are balanced, however, by dependence on road infrastructure. Road infrastructure reliability is an important factor in its functioning. If some elements of road infrastructure are disrupted or fail, the function of dependent infrastructures, such as the integrated rescue system or industry, are also impaired and may fail. These important elements of road infrastructure should be identified as critical and be given greater attention when identifying weaknesses and implementing subsequent security measures. This article introduces the Identifying Critical Elements of Road Infrastructure  (ICERI) method, which was designed to make use of Cascading Impact Assessments (CIA). The use of CIA allows critical elements to be identified through impact escalation analysis. These impacts can therefore be monitored not only in road transport infrastructure but also across the entire critical infrastructure system.


First published online 4 May 2020

Keyword : critical infrastructure, road infrastructure, critical elements, cascade effects, identification, ICERI method

How to Cite
Rehak, D., Patrman, D., Brabcová, V., & Dvořák, Z. (2020). Identifying critical elements of road infrastructure using cascading impact assessment. Transport, 35(3), 300-314. https://doi.org/10.3846/transport.2020.12414
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Jul 9, 2020
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References

Ambros, J.; Turek, R.; Brich, M.; Kubeček, J. 2019. Safety assessment of Czech motorways and national roads, European Transport Research Review 11: 1. https://doi.org/10.1186/s12544-018-0328-2

Bertocchi, G.; Bologna, S.; Carducci, G.; Carrozzi, L.; Cavallini, S.; Lazari, A.; Oliva, G.; Traballesi, A. 2016. Guidelines for Critical Infrastructures Resilience Evaluation. Italian Association of Critical Infrastructures Experts (AIIC). 101 p. Available from Internet: http://www.infrastrutturecritiche.it/new/media-files/2016/04/Guidelines_Critical_Infrastructures_Resilience_Evaluation.pdf

Bie, W.; Wang, X. 2002. Evaluation of power system cascading outages, in Proceedings. International Conference on Power System Technology, 13–17 October 2002, Kunming, China, 415–419. https://doi.org/10.1109/ICPST.2002.1053577

Chen, B. Y.; Lam, W. H. K.; Sumalee, A.; Li, Q.; Li, Z.-C. 2012. Vulnerability analysis for large-scale and congested road networks with demand uncertainty, Transportation Research Part A: Policy and Practice 46(3): 501–516. https://doi.org/10.1016/j.tra.2011.11.018

Chen, Y.; Milanović, J. V. 2017. Critical appraisal of tools and methodologies for studies of cascading failures in coupled critical infrastructure systems, in IEEE EUROCON 2017: 17th International Conference on Smart Technologies, 6–8 July 2017, Ohrid, Macedonia, 599–604. https://doi.org/10.1109/EUROCON.2017.8011182

David, H. A. 1988. The Method of Paired Comparisons. Hodder Arnold. 200 p.

Dong, W.; Wang, Y.; Yu, H. 2017. An identification model of urban critical links with macroscopic fundamental diagram theory, Frontiers of Computer Science 11(1): 27–37. https://doi.org/10.1007/s11704-016-6080-7

Dvořák, Z.; Sventeková, E.; Řehák, D.; Čekerevac, Z. 2017. Assessment of critical infrastructure elements in transport, Procedia Engineering 187: 548–555. https://doi.org/10.1016/j.proeng.2017.04.413

EC. 2008. Council Directive 2008/114/EC of 8 December 2008 on the Identification and Designation of European Critical Infrastructures and the Assessment of the Need to Improve their Protection. Available from Internet: http://data.europa.eu/eli/dir/2008/114/oj

EC. 2006. Commission Regulation (EC) No 851/2006 of 9 June 2006 Specifying the Items to be Included under the Various Headings in the Forms of Accounts Shown in Annex I to Council Regulation (EEC) No 1108/70. Available from Internet: http://data.europa.eu/eli/reg/2006/851/oj

Eurostat. 2018. Road Freight Transport Statistics – Cabotage. Statistical Office of the European Union (Eurostat). Available from Internet: https://ec.europa.eu/eurostat/statistics-explained/index.php/Road_freight_transport_statistics_-_cabotage

Giannopoulos, G.; Filippini, R.; Schimmer, M. 2012. Risk assessment methodologies for Critical Infrastructure Protection. Part I: A state of the Art. Joint Research Centre (JRC), European Commission. 53 p. https://doi.org/10.2788/22260

Gonzva, M.; Barroca, B.; Gautier, P.-E.; Diab, Y. 2016. Analysis of disruptions cascade effect within and between urban sociotechnical systems in a context of risks, E3S Web of Conferences 7: 07008. https://doi.org/10.1051/e3sconf/20160707008

Hassel, H.; Johansson, J.; Cedergren, A.; Svegrup, L.; Arvidsson, B. 2014. Method to Study Cascading Effects. CascEff Project: Deliverable No D2.1. Lund University, Sweden. 40 p. Available from Internet: http://casceff.eu/media2/2016/02/D2.1-Deliverable_Final_Ver2_PU.pdf

Hromada, M.; Lukas, L. 2012. Multicriterial evaluation of critical infrastructure element protection in Czech Republic, Communications in Computer and Information Science 340: 361–368. https://doi.org/10.1007/978-3-642-35267-6_48

IEC 60812:2006. Analysis Techniques for System Reliability – Procedure for Failure Mode and Effects Analysis (FMEA).

IEC 61025:2006. Fault Tree Analysis (FTA).

IEC 62502:2010. Analysis Techniques for Dependability – Event Tree Analysis (ETA).

IEC 31010:2019. Risk Management – Risk Assessment Techniques.

IRDR. 2014. Peril Classification and Hazard Glossary. Data Project Report No 1. Integrated Research on Disaster Risk (IRDR), Beijing, China. 28 p. Available from Internet: http://www.irdrinternational.org/2014/03/28/irdr-peril-classification-and-hazard-glossary

Jenelius, E. 2007. Approaches to Road Network Vulnerability Analysis. Department of Transport and Economics, Royal Institute of Technology (KTH), Stockholm, Sweden. 29 p.

Jenelius, E.; Petersen, T.; Mattsson, L.-G. 2006. Importance and exposure in road network vulnerability analysis, Transportation Research Part A: Policy and Practice 40(7): 537–560. https://doi.org/10.1016/j.tra.2005.11.003

Klein, P.; Hutter, R. 2017. Qualitative criteria in the assessment of security measures for critical infrastructure protection – a new approach, International Journal of Critical Infrastructures 13(1): 29–45. https://doi.org/10.1504/IJCIS.2017.083637

Kotzanikolaou, P.; Theoharidou, M.; Gritzalis, D. 2013. Cascading effects of common-cause failures in critical infrastructures, IFIP Advances in Information and Communication Technology 417: 171–182. https://doi.org/10.1007/978-3-642-45330-4_12

Labaka, L.; Hernantes, J.; Sarriegi, J. M. 2015. A framework to improve the resilience of critical infrastructures, International Journal of Disaster Resilience in the Built Environment 6(4): 409–423. https://doi.org/10.1108/IJDRBE-07-2014-0048

Leitner, B.; Decký, M.; Kováč, M. 2019. Road pavement longitudinal evenness quantification as stationary stochastic process, Transport 34(2): 195–203. https://doi.org/10.3846/transport.2019.8577

Leitner, B.; Môcová, L.; Hromada, M. 2017. A New approach to identification of critical elements in railway infrastructure, Procedia Engineering 187: 143–149. https://doi.org/10.1016/j.proeng.2017.04.360

Leitner, B.; Rehak, D.; Keršys, R. 2018. The new procedure for identification of infrastructure elements significance in subsector railway transport, Komunikácie / Communications 20(2): 41–48.

Liao, H.; Apt, J.; Talukdar, S. 2004. Phase Transitions in the Probability of Cascading Failures. Working Paper. Carnegie Mellon University, Pittsburgh, PA, US. 4 p. Available from Internet: https://www.cmu.edu/ceic/assets/docs/publications/working-papers/ceic-04-08.pdf

Min, H.-S. J.; Beyeler, W.; Brown, T.; Son, Y. J.; Jones, A. T. 2007. Toward modeling and simulation of critical national infrastructure interdependencies, IIE Transactions 39(1): 57–71. https://doi.org/10.1080/07408170600940005

Nan, C.; Sansavini, G. 2017. A quantitative method for assessing resilience of interdependent infrastructures, Reliability Engineering & System Safety 157: 35–53. https://doi.org/10.1016/j.ress.2016.08.013

NIAC. 2009. National Infrastructure Advisory Council Critical Infrastructure Resilience: Final Report and Recommendations. National Infrastructure Advisory Council (NIAC), US Department of Homeland Security, Washington, DC, US. 54 p. Available from Internet: https://www.cisa.gov/publication/niac-critical-infrastructure-resilience-final-report

Oliveira, E. L.; Portugal, L. da S.; Porto Junior, W. 2014. Determining critical links in a road network: vulnerability and congestion indicators, Procedia – Social and Behavioral Sciences 162: 158–167. https://doi.org/10.1016/j.sbspro.2014.12.196

Pant, R.; Hall, J. W.; Blainey, S. P. 2016. Vulnerability assessment framework for interdependent critical infrastructures: case-study for Great Britain’s rail network, European Journal of Transport and Infrastructure Research 16(1): 174–194. https://doi.org/10.18757/ejtir.2016.16.1.3120

Patrman, D.; Splichalova, A.; Rehak, D.; Onderkova, V. 2019. Factors influencing the performance of critical land transport infrastructure elements, Transportation Research Procedia 40: 1518–1524. https://doi.org/10.1016/j.trpro.2019.07.210

Public Safety Canada. 2018. National Cross Sector Forum: 2018–2020 Action Plan for Critical Infrastructure. Public Safety Canada, Ottawa, Canada. 25 p. Available from Internet: https://www.publicsafety.gc.ca/cnt/rsrcs/pblctns/pln-crtcl-nfrstrctr-2018-20

Rehak, D.; Markuci, J.; Hromada, M.; Barcova, K. 2016. Quantitative evaluation of the synergistic effects of failures in a critical infrastructure system, International Journal of Critical Infrastructure Protection 14: 3–17. https://doi.org/10.1016/j.ijcip.2016.06.002

Rehak, D.; Novotny, P. 2016. Bases for modelling the impacts of the critical infrastructure failure, Chemical Engineering Transactions 53: 91–96. https://doi.org/10.3303/CET1653016

Rehak, D.; Senovsky, P.; Hromada, M.; Lovecek, T.; Novotny, P. 2018. Cascading impact assessment in a critical infrastructure system, International Journal of Critical Infrastructure Protection 22: 125–138. https://doi.org/10.1016/j.ijcip.2018.06.004

Rehak, D.; Senovsky, P.; Hromada, M.; Lovecek, T. 2019a. Complex approach to assessing resilience of critical infrastructure elements, International Journal of Critical Infrastructure Protection 25: 125–138. https://doi.org/10.1016/j.ijcip.2019.03.003

Rehak, D.; Radimsky, M.; Hromada, M.; Dvorak, Z. 2019b. Dynamic impact modeling as a road transport crisis management support tool, Administrative Sciences 9(2): 29. https://doi.org/10.3390/admsci9020029

Renger, R.; Foltysova, J.; Ienuso, S.; Renger, J.; Booze, W. 2017. Evaluating system cascading failures, Evaluation Journal of Australasia 17(2): 29–36. https://doi.org/10.1177/1035719X1701700205

Rinaldi, S. M.; Peerenboom, J. P.; Kelly, T. K. 2001. Identifying, understanding, and analyzing critical infrastructure interdependencies, IEEE Control Systems Magazine 21(6): 11–25. https://doi.org/10.1109/37.969131

Ristvej, J.; Zagorecki, A.; Hollá, K.; Šimák, L.; Titko, M. 2013. Modelling, simulation and information systems as a tool to support decision making process in crisis management, in 27th European Simulation and Modelling Conference – ESM’2013, 23–25 October 2013, Lancaster, UK, 71–76.

RSD. 2012. Zvlněná dálnice u Ostravy má rekordních 901 vad. Ředitelství silnic a dálnic (RSD) ČR. Česká Republika. Available from Internet: https://www.rsd.cz (in Czech).

Rupi, F.; Angelini, S.; Bernardi, S.; Danesi, A.; Rossi, G. 2015. Ranking links in a road transport network: a practical method for the calculation of link importance, Transportation Research Procedia 5: 221–232. https://doi.org/10.1016/j.trpro.2015.01.003

Scott, D. M.; Novak, D. C.; Aultman-Hall, L.; Guo, F. 2006. Network robustness index: a new method for identifying critical links and evaluating the performance of transportation networks, Journal of Transport Geography 14(3): 215–227. https://doi.org/10.1016/j.jtrangeo.2005.10.003

Seppänen, H.; Luokkala, P.; Zhang, Z.; Torkki, P.; Virrantaus, K. 2018. Critical infrastructure vulnerability – a method for identifying the infrastructure service failure interdependencies, International Journal of Critical Infrastructure Protection 22: 25–38. https://doi.org/10.1016/j.ijcip.2018.05.002

Slivková, S. 2018. Určování kritických prvků v oblasti železniční dopravy. Disertační práce pro získání akademického titulu „doktor“, ve zkratce „Ph.D.“. Technická univerzita Ostrava, Česká republika. 123 s. (in Czech). Available from Internet: https://dspace.vsb.cz/bitstream/handle/10084/133108/SLI0006_FBI_P3908_3908V009_2018.pdf

Slivkova, S.; Rehak, D.; Novotny, P. 2018. Critical element designation system in rail transport in the Czech Republic, Chemical Engineering Transactions 67: 775–780. https://doi.org/10.3303/CET1867130

Slivková, S.; Tašlová, J.; Novotný, P. 2015. Návrh kritérií kritičnosti prvků železniční dopravní infrastruktury, in Požární ochrana 2015: Sborník přednášek XXIV. ročníku mezinárodní konference, 9.–10. září 2015, Ostrava, Česká Republika, 3: 291–294. (in Czech).

Štoller, J.; Dvořák, P.; Túró, T.; Zezulová, E. 2018. Basic principles of critical infrastructure protection, in Transport Means 2018: Proceedings of the 22nd International Scientific Conference, 3–5 October 2018, Kaunas, Lithuania, 1: 267–271.

Taylor, M. A. P.; D’Este, G. M. 2007. Transport network vulnerability: a method for diagnosis of critical locations in transport infrastructure systems, in A. T. Murray, T. H. Grubesic (Eds.). Critical Infrastructure. Advances in Spatial Science, 9–30. https://doi.org/10.1007/978-3-540-68056-7_2

Taylor, M. A. P.; Sekhar, S. V. C.; D’Este, G. M. 2006. Application of accessibility based methods for vulnerability analysis of strategic road networks, Networks & Spatial Economics 6(3–4): 267–291. https://doi.org/10.1007/s11067-006-9284-9

The White House. 2013. Critical Infrastructure Security and Resilience. Presidential Policy Directive PPD-21. The White House, Washington, DC, US. Available from Internet: https://obamawhitehouse.archives.gov/the-press-office/2013/02/12/presidential-policy-directive-critical-infrastructure-security-and-resil

UNECE. 2018. 2018 Inland Transport Statistics for Europe and North America. Volume LIX. United Nations Economic Commission for Europe (UNECE). 189 p. Available from Internet: https://www.unece.org/fileadmin/DAM/trans/main/wp6/publications/2018_INLAND_TRANSPORT_STATISTICS.pdf

Weihrich, H. 1982. The TOWS matrix – a tool for situational analysis, Long Range Planning 15(2): 54–66. https://doi.org/10.1016/0024-6301(82)90120-0

Yang, X.; Liu, L.; Li, Y.; He, R. 2016. Identifying critical links in urban traffic networks: a partial network scan algorithm, Kybernetes 45(6): 915–930. https://doi.org/10.1108/K-05-2015-0144

Yu, C.; Yang, X.; Yun, M. 2014. Method of Searching for Critical Links in Traffic Network Based on Link Redundancy, in Transportation Research Board 93rd Annual Meeting, 12–16 January 2014, Washington, DC, US, 1–17.

Zimmerman, R.; Restrepo, C. E. 2009. Analyzing cascading effects within infrastructure sectors for consequence reduction, in 2009 IEEE Conference on Technologies for Homeland Security, 11–12 May 2009, Boston, MA, US 165–170. https://doi.org/10.1109/THS.2009.5168029

Zuccaro, G.; De Gregorio, D.; Leone, M. F. 2018. Theoretical model for cascading effects analyses, International Journal of Disaster Risk Reduction 30: 199–215. https://doi.org/10.1016/j.ijdrr.2018.04.019