Skip to main content
Intended for healthcare professionals
Restricted access
Research article
First published January 2007

Methodology for Identifying Vulnerable Sections in a National Road Network

Abstract

Under the authority of the Flemish Traffic Centre, a study was carried out to identify road sections that are vulnerable to major incidents. The primary objective of the study was to develop a methodology capable of rapidly scanning a large network for the most vulnerable sections. The methodology builds on a number of vulnerability indicators based on an analysis of the typical stages of an incident. With these indicators, the most important bottlenecks in the network can be selected and subjected to a closer examination. The methodology developed in the project was tested on a study area comprising the network in the corridor between the two large cities of Brussels and Ghent, Belgium. For this network, an analysis of empirical data was performed to gain insight into the extent of the reliability problems on the Flemish road network.

Get full access to this article

View all access and purchase options for this article.

References

1. Bliemer M. C. J. Versteegt H. H. and Castenmiller R. J. INDY: A New Analytical Multiclass Dynamic Traffic Assignment Model. Proc., TRISTAN V Conference, Guadeloupe, French West Indies, 2004.
2. Westerman M. Hoogendoorn-Lanser S. and van der Vlist M. Reistijd-schatter: beschrijving en functionele specificaties. Rapport INRO/VVG/1997-10, TNO Inro Delft, Delft, Netherlands.
3. Coifman B. Estimating Travel Times and Vehicle Trajectories on Freeways Using Dual Loop Detectors. Transportation Research A, Vol. 36A, No. 4, 2002, pp. 351–364.
4. Minderhoud M. Botma H. and Bovy P. H. The Product Limit Method to Estimate Roadway Capacity. In Motorway Traffic Flow Analysis. New Methodologies and Recent Empirical Findings (Bovy P. H. and Thijs R., eds.), Delft University Press, Netherlands, 1998, pp. 121–142.
5. Clark S. and Watling D. Modelling Network Travel Time Reliability Under Stochastic Demand. Transportation Research Part B, Vol. 39, No. 2 2005, pp. 119–140.
6. Bell M. G. H. and Iida Y. Transportation Network Analysis. Wiley and Sons, Chichester, England, 1997.
7. Chen A. Ji Z. and Recker W. Effect of Route Choice Models on Estimation of Travel Time Reliability Under Demand and Supply Variations. In The Network Reliability of Transport, Proc., 1st International Symposium on Transportation Network Reliability (INSTR) (Bell M. G. H. and Iida Y., eds.), Kyoto, Japan, Elsevier Science, 2003, pp. 93–118.
8. Yang H. Lo K. and Tang W. H. Travel Time Versus Capacity Reliability of a Road Network. In Reliability of Transport Networks (Bell M. G. H. and Cassir C., eds.), Research Studies Press, Ltd., Baldock, Hertfordshire, England, 2000, pp. 119–138.
9. Chen A. Yang H. Lo H. K. and Tang W. H. Capacity Reliability of a Road Network: An Assessment Methodology and Numerical Results. Transportation Research Part B, Vol. 36, No. 3 2002, pp. 225–252.
10. Wakabayashi H. Snowfall Weather Forecast and Expressway Network Reliability Assessment. In Reliability of Transport Networks (Bell M. G. H. and Cassir C., eds.), Research Studies Press Ltd., Baldock, Hertfordshire, England, 2000, pp. 103–118.
11. Lo H. K. and Tung Y. K. A Chance Constrained Network Capacity Model. In Reliability of Transport Networks (Bell M. G. H. and Cassir C., eds.), Research Studies Press Ltd., Baldock, Hertfordshire, England, 2000, pp. 159–172.
12. Berdica K. Vulnerability—A Model-Based Case Study of the Road Network in the City of Stockholm. In Papers Presented at the 1st International Symposium on Transportation Network Reliability (INSTR), Kyoto, Japan, 2001.
13. Berdica K. An Introduction to Road Vulnerability: What Has Been Done, Is Done and Should Be Done. Transport Policy, Vol. 9, No. 2 2002, pp. 117–127.
14. Cassir C. and Bell M. G. H. The N + M Person Game Approach to Network Reliability. In Reliability of Transport Networks (Bell M. G. H. and Cassir C., eds.), Research Studies Press Ltd., Baldock, Hertfordshire, England, 2000, pp. 91–102.
15. Tamminga G. F. Maton J. C. Poorterman R. and Zee J. De Robuustheidscanner. Robuustheid van netwerken: een modelmatige verkenning. Rapport I&M-99366053-GT/mk Grontmij Nederland, i.o.v. Adviesdienst Verkeer and Vervoer, Amsterdam, Netherlands, 2005.

Cite article

Cite article

Cite article

OR

Download to reference manager

If you have citation software installed, you can download article citation data to the citation manager of your choice

Share options

Share

Share this article

Share with email
EMAIL ARTICLE LINK
Share on social media

Share access to this article

Sharing links are not relevant where the article is open access and not available if you do not have a subscription.

For more information view the Sage Journals article sharing page.

Information, rights and permissions

Information

Published In

Article first published: January 2007
Issue published: January 2007

Rights and permissions

© 2007 National Academy of Sciences.
Request permissions for this article.

Authors

Affiliations

Chris M. J. Tampère
Katholieke Universiteit Leuven, Traffic and Infrastructure, Kasteelpark Arenberg 40, 3001 Leuven, Belgium T +32 16 321673, F +32 16 321976.
Jim Stada
Katholieke Universiteit Leuven, Traffic and Infrastructure, Kasteelpark Arenberg 40, 3001 Leuven, Belgium T +32 16 321673, F +32 16 321976.
Ben Immers
Katholieke Universiteit Leuven, Traffic and Infrastructure, Kasteelpark Arenberg 40, 3001 Leuven, Belgium T +32 16 321673, F +32 16 321976.
Els Peetermans
Flemish Traffic Centre, Vuurkruisenplein 20, 2020 Antwerpen, Belgium T +32 3 443 63 35.
Katia Organe
Flemish Traffic Centre, Vuurkruisenplein 20, 2020 Antwerpen, Belgium T +32 3 443 63 35.

Notes

Metrics and citations

Metrics

Journals metrics

This article was published in Transportation Research Record: Journal of the Transportation Research Board.

VIEW ALL JOURNAL METRICS

Article usage*

Total views and downloads: 60

*Article usage tracking started in December 2016


Altmetric

See the impact this article is making through the number of times it’s been read, and the Altmetric Score.
Learn more about the Altmetric Scores



Articles citing this one

Receive email alerts when this article is cited

Web of Science: 0

Crossref: 33

  1. A Method for the Identification of Critical Interstop Sections in Term...
    Go to citation Crossref Google Scholar
  2. Vulnerability assessment of freeway network considering the probabilit...
    Go to citation Crossref Google Scholar
  3. Road network vulnerability analysis considering the probability and co...
    Go to citation Crossref Google Scholar
  4. Predicting disruptions and their passenger delay impacts for public tr...
    Go to citation Crossref Google Scholar
  5. Flooding and mobility: a polish analysis
    Go to citation Crossref Google Scholar
  6. A Novel Algorithm of Identification Theory of Complex Network for Publ...
    Go to citation Crossref Google Scholar
  7. Resilience metrics and measurement methods for transportation infrastr...
    Go to citation Crossref Google Scholar
  8. Identifying Critical Regions in Industry Infrastructure: A Case Study ...
    Go to citation Crossref Google Scholar
  9. Vulnerability analysis and critical area identification of public tran...
    Go to citation Crossref Google Scholar
  10. Detecting critical links of urban networks using cluster detection met...
    Go to citation Crossref Google Scholar
  11. Accounting for greenhouse gas emissions from traffic rearrangement: a ...
    Go to citation Crossref Google Scholar
  12. Increasing the resilience level of a vulnerable rail network: The stra...
    Go to citation Crossref Google Scholar
  13. Accessibility analysis of risk severity
    Go to citation Crossref Google Scholar
  14. Identification and quantification of link vulnerability in multi-level...
    Go to citation Crossref Google Scholar
  15. Identifying Critical Links in Transportation Networks Based on Route D...
    Go to citation Crossref Google Scholar
  16. Using an AHP-ISM Based Method to Study the Vulnerability Factors of Ur...
    Go to citation Crossref Google Scholar
  17. Analysis of transportation networks subject to natural hazards – Insig...
    Go to citation Crossref Google Scholar
  18. Vulnerability of road networks
    Go to citation Crossref Google Scholar
  19. Recent Advances in Modeling the Vulnerability of Transportation Networ...
    Go to citation Crossref Google Scholar
  20. Measuring the Performance of Transportation Infrastructure Systems in ...
    Go to citation Crossref Google Scholar
  21. Application of advanced sampling for efficient probabilistic traffic m...
    Go to citation Crossref Google Scholar
  22. Improving the efficiency of repeated dynamic network loading through m...
    Go to citation Crossref Google Scholar
  23. Traffic performance on quasi-grid urban structures
    Go to citation Crossref Google Scholar
  24. An assessment method for highway network vulnerability
    Go to citation Crossref Google Scholar
  25. Delays Caused by Incidents: Data-Driven Approach
    Go to citation Crossref Google Scholar
  26. Access and monitor vulnerability of urban metro network system in Chin...
    Go to citation Crossref Google Scholar
  27. Link-level vulnerability indicators for real-world networks
    Go to citation Crossref Google Scholar
  28. A framework for robustness analysis of road networks for short term va...
    Go to citation Crossref Google Scholar
  29. Evaluation of Link Criticality for Day-to-Day Degradable Transportatio...
    Go to citation Crossref Google Scholar
  30. Methodology for Evaluating and Improving Road Network Topology Vulnera...
    Go to citation Crossref Google Scholar
  31. Evaluation of the consequences of road system failure on other critica...
    Go to citation Crossref Google Scholar
  32. Marginal Incident Computation...
    Go to citation Crossref Google Scholar
  33. The importance of alternative routes for the robustness of a road netw...
    Go to citation Crossref Google Scholar

Figures and tables

Figures & Media

Tables

View Options

Get access

Access options

If you have access to journal content via a personal subscription, university, library, employer or society, select from the options below:


Alternatively, view purchase options below:

Purchase 24 hour online access to view and download content.

Access journal content via a DeepDyve subscription or find out more about this option.

View options

PDF/ePub

View PDF/ePub