This paper introduces a rapid evaluation method for optimizing the meso cracks in asphalt mixtures.Firstly,the preparation of meso cracks in asphalt mixture and its evaluation method is designed through indoor experiments,and the line laser is used to scan the specimens and collect the infrared images.Then,by analyzing the infrared image dataest,the temperature interval feature tracking method based on time series is established,and the temperature interval feature area and its diffusion rate are calculated in relation to the changes in the thermal characteristics of the line laser displacements.Finally,the location and width of meso cracks in the specimens are quantitatively analyzed.The study shows that the diffusion rate based on the thermal effect of the temperature interval can enhance the spatial resolution of the meso cracks in the specimen,and at the same time,the temperature characteristic area diffusion rate obviously shows a trend of decreasing and then increasing as the line laser gradually approaches the cracks,indicating that the thermal diffusion energy at the cracks of the specimen gradually decreases and tends to be close to zero.When the line laser is far away from the crack,the heat diffusion rate on the surface of the specimen increases gradually,reflecting the strong thermal barrier phenomenon of the meso cracks.The results show that the characteristic area of temperature interval B and C at the crack are always located in the lowest trough position of the characteristic curve,and the crack localization error of temperature interval B is less than 5.61%；meanwhile,the correlation between the crack characteristic area width and the crack width calculated by the sub pixel algorithm reaches 0.9952 at the reliability level of 95%,and the relative error of predicting the crack width is no more than 4.13%.This evaluation method shows that the temperature interval based on the temporal characteristics has significant sensitivity to different meso cracks widths,which can provide a theoretical basis and reference for the application of automated detection of asphalt pavement cracks by vehicle mobile thermal imaging technology.