AbstractFatigue cracking due to repeated truck traffic loads is the leading cause of failure of asphalt concrete pavement in many locations. Rest periods, referring to the time intervals between successive trucks, may allow for partial or full recovery from fatigue damage and in turn extend pavement fatigue life. This paper delves into the characteristics of rest periods between highway truck traffic loads using traffic data from 40 weigh-in-motion (WIM) stations installed on California state highways and evaluates their effects on pavement performance using mechanistic-empirical incremental-recursive damage and cracking simulation (CalME software). Toward this purpose, truck traffic data were extracted from these WIM stations at selected periods throughout the year 2015 to calculate rest periods. The probability distribution of rest periods and quantiles of cumulative rest periods were calculated, respectively. Regression and statistical analysis for 0.5 quantiles (median) of cumulative rest periods were also performed for different spectra groups and seasons. It was found that rest periods are strongly correlated with the truck traffic volume regardless of the WIM station location and seasons of the year. The actual rest periods based on the nonuniform truck traffic measured from the WIM data were found to be slightly shorter than the corresponding theoretical average rest periods for uniform traffic (ARP-UT) currently assumed in CalME, likely due to truck-following. This theoretical value assumes an equal time interval between trucks all the time. After comparing pavement performance with and without rest periods, it was found that rest periods have a significant influence (30% in difference) on pavement cracking performance in the modeling. Based on this preliminary analysis, the difference in pavement performance caused by the difference between the actual rest periods and ARP-UT is minimal. It is therefore recommended to continue to use ARP-UT to account for the effect of rest periods in pavement design.