A method for real-time condition monitoring of haul roads based on Bayesian parameter estimation

Current haul road management techniques, such as routine, periodic and urgent maintenance have shortcomings in many complex haul road environments. Real-time road condition monitoring may significantly reduce maintenance costs, both to the road and to the vehicles. A recent idea is that vehicle on-board data collection systems could be used to monitor haul roads on a real-time basis by means of vibration signature analysis. This paper proposes a methodology based on Bayesian regression to isolate the effect of varying vehicle speed on the measured vehicle response metric. A key feature of the proposed methodology is that it avoids the costly need to generate analytical or empirical vehicle models.

► Automated real time road condition monitoring based on vehicle response measurements. ► Bayesian parameter estimation used to standardise vehicle response. ► Renders robust, cost effective framework for general monitoring of haul roads.