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QRA Model‐Based Risk Impact Analysis of Traffic Flow in Urban Road Tunnels

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  • Qiang Meng
  • Xiaobo Qu
  • Kum Thong Yong
  • Yoke Heng Wong

Abstract

Road tunnels are vital infrastructures providing underground vehicular passageways for commuters and motorists. Various quantitative risk assessment (QRA) models have recently been developed and employed to evaluate the safety levels of road tunnels in terms of societal risk (as measured by the F/N curve). For a particular road tunnel, traffic volume and proportion of heavy goods vehicles (HGVs) are two adjustable parameters that may significantly affect the societal risk, and are thus very useful in implementing risk reduction solutions. To evaluate the impact the two contributing factors have on the risk, this article first presents an approach that employs a QRA model to generate societal risk for a series of possible combinations of the two factors. Some combinations may result in F/N curves that do not fulfill a predetermined safety target. This article thus proposes an “excess risk index” in order to quantify the road tunnel risk magnitudes that do not pass the safety target. The two‐factor impact analysis can be illustrated by a contour chart based on the excess risk. Finally, the methodology has been applied to Singapore's KPE road tunnel and the results show that in terms of meeting the test safety target for societal risk, the traffic capacity of the tunnel should be no more than 1,200 vehs/h/lane, with a maximum proportion of 18% HGVs.

Suggested Citation

  • Qiang Meng & Xiaobo Qu & Kum Thong Yong & Yoke Heng Wong, 2011. "QRA Model‐Based Risk Impact Analysis of Traffic Flow in Urban Road Tunnels," Risk Analysis, John Wiley & Sons, vol. 31(12), pages 1872-1882, December.
  • Handle: RePEc:wly:riskan:v:31:y:2011:i:12:p:1872-1882
    DOI: 10.1111/j.1539-6924.2011.01624.x
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    References listed on IDEAS

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    6. Qiang Meng & Xiaobo Qu & Xinchang Wang & Vivi Yuanita & Siew Chee Wong, 2011. "Quantitative Risk Assessment Modeling for Nonhomogeneous Urban Road Tunnels," Risk Analysis, John Wiley & Sons, vol. 31(3), pages 382-403, March.
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    Cited by:

    1. Can Chen & Tienan Li & Jian Sun & Feng Chen, 2016. "Hotspot Identification for Shanghai Expressways Using the Quantitative Risk Assessment Method," IJERPH, MDPI, vol. 14(1), pages 1-15, December.

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