摘要: |
TxDOT’s Maintenance Division has recently implemented a comprehensive and more powerful pavement management system known as Pavement Analyst (PA). The new system is capable of prioritizing maintenance and rehabilitation (M&R) activities for different time horizons based on a series of decision trees that account for current distress levels, scores, traffic, location, environment, etc. The decision trees incorporate new variables, such as skid and texture which are correlated to the number of wet weather crashes. Controlling these variables shall significantly improve the safety of the Texas highway network. There are no current models for the prediction of skid or texture that can be used on Pavement Analyst. The existing models are based on laboratory characterization and the exponential decay rate is estimated from laboratory performance. The objective of this research project is to develop a performance model to predict pavement skid number as a function of time, for use in TxDOT’s pavement management system, i.e. Pavement Analyst. The research team shall develop models that account for field prediction of skid and texture, to be incorporated into Pavement Analyst and to aid in the selection of optimal M&R activities. These models shall also account for treatment type: PM, LRhb, MRhb, and HRhb. |