Sensitivity of flexible pavement design to Michigan's climatic inputs using pavement ME design

Climate condition is an important factor that affects the performance of pavements and distress predictions using mechanistic-empirical analyses. This study aims to analyse the sensitivity of flexible pavement distress predictions to climatic inputs using the AASHTOWare Pavement ME Design software in the state of Michigan. Typical traffic parameters, pavement structures and material properties for the state of Michigan were used as inputs for the analysis of flexible pavement performance. Six representative sites geographically distributed throughout Michigan and two typical traffic levels (high and medium) were incorporated in a comprehensive analysis of the effects of climate on flexible pavement performance predictions. A normalised sensitivity index was adopted to quantitatively evaluate the sensitivity of distress predictions to the five individual climatic variables: temperature, wind speed, precipitation, percent sunshine and relative humidity. The results of this study showed that the prediction of flexible pavement performance in Michigan is most sensitive to changes in temperature with other climatic factors such as wind speed, percent sunshine, precipitation and relative humidity impacting predictions to a lesser extent. Higher temperature and percent sunshine at a given location increased rutting and International Roughness Index (IRI) predictions, but reduced the likelihood of fatigue cracking. An increase in wind speed or precipitation reduced rutting and IRI predictions, but increased fatigue cracking predictions. Ambient relative humidity had a negligible effect on all flexible pavement distress predictions. These findings provide insights into the sensitivity of flexible pavement designs under different climate conditions. The sensitivity results are also beneficial for the Michigan Department of Transportation as they seek to improve the existing climatic files in PMED through evaluation of new climatic data sources.