Risk-based approach for managing road surface friction of road assets

  • Noppadol Piyatrapoomi
  • Justin Weligamage
Conference paper


In Australia, road crash trauma costs the nation approximately A$18 billion annually whilst the United States estimates an economic impact of around US$230 billion on its network. Worldwide, the economic cost of road crashes is estimated to be around US$518 billion each year. It is therefore in both the sociological and economic interests of society that attempts are made to reduce, as much as possible, the level and severity of crashes. There are many factors that contribute to road crashes on a road network. The complex manner in which human behaviour, environmental and vehicle failure factors can interact in many critical driving situations, making the task of identifying and managing road crash risk within a road network quite difficult. While road authorities have limited control over external factors such as driver behaviour and vehicle related issues, some environmental factors can be managed such as road surface friction (or skid resistance of road surface). A riskbased method for managing road surface friction (i.e. skid resistance) is presented in this paper. The risk-based method incorporates ‘risk’ into the analysis of skid resistance and crash rate, by linking the statistical properties of skid resistance to the risk of a crash. By examining the variation of skid resistance values throughout the network, the proposed methodology can establish an optimal ‘investigatory level’ for a given level of crash risk, along with a set of statistical ‘tolerance’ bounds in which measured skid resistance values can be found. The investigatory level is a threshold level for triggering a detailed investigation of a road site to identify whether a remedial treatment should be made. A road category of normal demand, spray sealed surface, speed zone greater than 80 km and annual average daily traffic less than 5,000 vehicles was used in demonstrating the application of the method.


Road Network Road Segment Road Surface Road Section Cumulative Probability Distribution 
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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Noppadol Piyatrapoomi
    • 1
  • Justin Weligamage
    • 1
  1. 1.Queensland Department of Main RoadsRoad Asset Management BranchBrisbaneAustralia

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