MECHANISTIC MODEL FOR PREDICTING SEASONAL VARIATIONS IN SKID RESISTANCE

Some of the findings of a 3-year research program to develop a basic mechanistic model for predicting seasonal and short-term variations in skid resistance as a function of environmental and traffic conditions are described. The model treats seasonal and short-term variations separately. Data from 21 test surfaces in State College, Pennsylvania, and 10 surfaces in Tennessee and North Carolina were analyzed. For the seasonal trend, an exponential curve was fitted to the skid number data for the asphalt pavements whereas a linear relationship best fit the data for portland cement concrete surfaces. The coefficients of the resulting seasonal variation curves were related to pavement and traffic parameters to provide predictors for long-term effects. Significant predictors were found to be British pendulum number (BPN) and average daily traffic. Other predictors for pavement polishing are suggested in place of BPN to predict the rate of decrease in skid resistance over an annual cycle. After the data for seasonal variations were adjusted, the remaining short-term variations were regressed against rainfall, temperature, and macrotexture parameters. The short-term variations can be predicted by dry spell factor and pavement temperature, but the introduction of the measured percentage normalized gradient was found to improve the regressions. Although good agreement was observed for the test data from the two locations, it is suggested that similar investigations be conducted in other geographic areas. (Author)

Media Info

  • Media Type: Print
  • Features: Figures; References; Tables;
  • Pagination: pp 29-38
  • Monograph Title: INTERACTION OF VEHICLES AND PAVEMENTS
  • Serial:

Subject/Index Terms

Filing Info

  • Accession Number: 00389579
  • Record Type: Publication
  • ISBN: 0309036674
  • Report/Paper Numbers: HS-037 871
  • Files: HSL, TRIS, TRB
  • Created Date: Oct 30 1985 12:00AM