Risk Assessment of Road Tunnels using Bayesian Networks

This paper introduces a methodology for the assessment of risks due to traffic in roadway tunnels. The proposed methodology utilizes Bayesian Probabilistic Networks for the risk assessment. The methodology is based on two hypotheses, i.e. that the roadway tunnel can be represented by a number of homogeneous segments and that the risks associated with a given segment can be represented through a set of Key Performance Indicators (KPI). The KPIs are the observable characteristics of the tunnel and the traffic such as the annual average daily traffic, the number of lanes, possible traffic separation, width, curvature and gradients. The risk is calculated in terms of expected number of accidents, injuries, fatalities and tunnel fires over the entire tunnel length for both, normal traffic events and dangerous goods events. The dependencies and the conditional probabilities in the Bayesian Probabilistic Networks are based on three general pillars, i.e. data, models published in literature and expert opinion. This new approach allows taking into account different specific characteristics of the tunnel and thus the risk of a complex tunnel system can easily be calculated. The Bayesian Probabilistic Networks are embedded into a Microsoft Excel Environment, so that the risk analysis can easily be performed. The methodology is generic, represents the best practice in the field of risk assessment and tunnel research, is realizable and easy to use, is transparent, supports the decision making process, and is modular so that it can be adopted to future findings.

• Record URL:
  https://doi.org/10.1016/j.sbspro.2012.06.1239
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1877042812029825
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/18770428
• Supplemental Notes:
  • Abstract reprinted with permission from Elsevier.
• Authors:
  • Schubert, Matthias
  • Høj, Niels Peter
  • Ragnøy, Arild
  • Buvik, Harald
• Conference:
  • Transport Research Arena 2012
  • Location: Athens , Greece
  • Date: 2012-4-23 to 2012-4-26
• Publication Date: 2012

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References;
• Pagination: pp 2697-2706
• Serial:
  • Procedia - Social and Behavioral Sciences
  • Volume: 48
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1877-0428
  • Serial URL: http://www.sciencedirect.com/science/journal/18770428/53
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Bayes' theorem; Fatalities; Fires; High risk locations; Highway safety; Risk assessment; Traffic flow; Tunnels
• Uncontrolled Terms: Performance indicators
• Subject Areas: Bridges and other structures; Highways; Safety and Human Factors; I82: Accidents and Transport Infrastructure;

Filing Info

• Accession Number: 01487572
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 9 2013 9:13AM