To investigate the impact of changes in pavement roughness on speed, this study developed a linear regression model to estimate free-flow speed on freeways in California. The explanatory variables include lane number, total number of lanes, day of the week, region (district), gasoline price, and pavement roughness as measured by the international roughness index (IRI). Data on the California freeway network from 2000 to 2011 were used to build the model. The results showed that pavement roughness has a very small effect on free-flow speed within the range of this study. For the IRI coverage in this study (90% of the records have an IRI of three or lower and 90% of the records have an IRI change of two or lower), a change of IRI of one () results in a change of average free-flow speed of approximately (0.3–0.4 mph). This result indicated that making a rough segment of pavement smoother through application of a maintenance or rehabilitation treatment will not result in substantially faster vehicle operating speeds, and therefore the energy and emission reductions gained from the reduced rolling resistance will not be offset by increased fuel consumption from faster speeds. However, developing a good model to predict the free-flow speed was not fully successful. The southern California interstate freeway model yielded the best result with an adjusted R-squared of 0.72. For the rest of the regions in the state, the selected explanatory variables can only explain approximately half of the total variance, indicating there are still other variables with more substantial effects on free-flow speed that were not covered in this study.
Impact of Pavement Roughness on Vehicle Free-Flow Speed
Journal of Transportation Engineering ; 140 , 9
2014-05-13
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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