Program overview | Projects Maintenance Cost Prediction for Roads [Kumar, RMIT] 2003-029-C Project participants and team members | Arun Kumar | | Qld Dept of Main Roads | Neil Robertson, John Spathonis | | Qld Dept of Public Works | Dale Gilbert | | Queensland University of Technology | Andreas Nata-Atmadja | | RMIT | Saman De Silva,Richard Heaney, Arun Kumar- Project Leader, Anthony Piyatrapoomi |
Road agencies, like all public infrastructure agencies, face many challenges in the short to long-term. These include:
the issues that surround ageing infrastructure
the increasing demand for resourcing maintenance and restoration needs for the infrastructure, at the expense of the development of new or upgraded infrastructure
the public demand for greater accountability for the use of public funds
the need for sophisticated risk management approaches that will consider both financial and non-financial impacts. Currently life cycle budget predictions (primarily maintenance and rehabilitation) are generally based on "representative" or "average" estimates of many input variables. The budget predictions therefore approximate to a 50% probability of being exceeded. With this research outcome, the life cycle budget estimates can be refined to 80% to 90% certainty. The project will develop a method for determining the budget prediction, having an estimated probability of not being exceeded, for managing the maintenance and rehabilitation of a chosen road network over a chosen analysis period (say 10, 20 or 30 years). This capability will be used by Main Roads and can be marketed to other road authorities in Australia and in other countries to allow better understand risk exposure. The risk exposure is a balance between a number of factors such as the needs to upkeep of the current network, fund new project and commitment allocation of resources to meet those needs amongst competing pressures. The concepts embodied in this project will also be applicable to other forms of assets management. |
