###### Abstract  
Asphalt pavements are damaged by traffic load repetitions. Conventionally, the allowed number of load repetitions until pavement failure is calculated based on empirical transfer functions from deterministic pavement mechanical responses to performance. However, the mechanical responses and damage to the pavement are uncertain under a random realistic traffic load and pavement temperature. Therefore, the non-deterministic problem--that is, the probability distributions of asphalt pavement responses and performance under random moving loads and pavement temperatures--was investigated in this study. Random factors include the load pressure, vehicle wandering, speed, and temperature inside the asphalt layer. A combination of the response surface and first-order reliability methodologies was recommended to calculate the probability of mechanical responses at any point within the pavement, for reasons of computational efficiency. The accuracy of this method was verified by a Monte-Carlo simulation. Then, the effects of the mean values and standard deviations of the random factors on the probability distributions of the mechanical responses were discussed. Finally, probability distributions of pavement performance (i.e., probability density distributions of cumulative damage for fatigue failure and rutting after repeated random loads) were calculated using transfer functions and the probability distributions of the mechanical responses; thereby, the failure probability of the pavement after a given number of load repetitions was obtained. The results show that the previous deterministic analysis could not fully reflect the random characteristics of pavement mechanical responses under realistic random moving loads, and the mean values and standard deviations of the random factors have significant effects on the probability distributions of mechanical responses and performance. The failure probability of the pavement after a given number of load repetitions can be used as a guide to reliability-based pavement design. This study on the probability distributions of asphalt pavement responses and performance exhibits the potential to understand pavement behavior and could be beneficial as a complement during reliability-based pavement design. asphalt pavement responses; pavement performance; probability distribution; random moving loads; response surface methodology 2020202023131 December 202223131 December 20  
Currently, the most prevalent asphalt pavement design method is the Mechanistic-Empirical Pavement Design Guide (MEPDG). The MEPDG provides a state-of-the-art practice tool for designing new and rehabilitated pavement structures based on mechanistic-empirical principles [4]. In the MEPDG, mechanical responses can be calculated by multilayered system theory or finite element simulation in the mechanistic part, and pavement performance can be evaluated by using empirical transfer functions with the calculated mechanical responses in the empirical part. This pavement design method also provides the option to perform reliability concepts. Pavement reliability can be captured in the MEPDG by comparing predicted and measured distress models. Many researchers believe that the current reliability framework in the MEPDG is insufficient for implementing the complete concept of reliability-based pavement design. Researchers have discussed three main reasons that cause the uncertainty of pavement performance: the variability in traffic, as well as structural and material parameters; the uncertainty of constants in design equations; and the uncertainty of model error [5]. The influence of the uncertainty of constants in design equations and model error can be eliminated by modifying the MEPDG through long-term in situ pavement testing and monitoring [6]. However, the variability in traffic, as well as structural and material parameters, which are inherent properties and cannot be ignored, should be discussed in reliability-based pavement design.