Study On Image-based Texture Analysis Method And Prediction Of Skid-resistance & Tire/pavement Noise Reduction Of HMA

Traffic safety considerably depends on available pavement surface friction. It is also well known that tire/pavement noise, especially with cars at high speeds, is a predominant source of traffic noise with respect to other traffic noise generation mechanisms. The level and distribution characteristics of pavement surface texture greatly affect the performance of skidresistance and tire/pavement noise reduction of pavement. However, the testing methods provided by the current specifications cannot obtain the distribution characteristics of pavement surface texture although they can accurately obtain the whole level of pavement texture. At the same time, most of the current specifications of design of Hot Mix Asphalt(HMA) mainly are methods which are designed to reach the desired air voids. The road performance of HMA(i.e. high temperature stability, low temperature cracking resistance, and water stability) need to be verified while the air voids of HMA meet the standard requirments. However, none of them pay attention to the performance of skid resistance and tire/pavement noise reduction of HMA.In order to supplement the shortage of current specifications of pavement surface texture testing and design of HMA, this dissertation is focused on providing a theoretical foundation for developing a comprehensive and scientific optimized design method of HMA based on its performance of skid resistance and tire/pavement noise reduction. A two dimension surface texture testing method of HMA was developed based on the image and spectrum analysis techniques. A predicted model of level and distribution of surface texture was built with the analysis of design parameters of HMA. At the same time, predicted models of surface coefficient of friction and tire/pavement noise of HMA were proposed based on the characteristics of the surface texture.This dissertation developed a 2 Dimension Image-based Texture Analysis Method(2DITAM) to obtain the whole level and distribution charateristics of pavement surface texture. 2D-ITAM can extract the profile of pavement surface texture based on the iamge analysis techniques, and obtain indexes representing the whole level and distribution charactersistcs of pavement surface texture with the spectral analysis method. At the same time, the accuracy of 2D-ITAM was tested with the comparsion of testing results between 2D-ITAM and traditional testing methods. The results indicated that this method was a promising and powerful tool for future application in mixture designs to estimate texture as related to noise and friction.In order to predict the level and distribution of surface texture of HMA, the design parameters of HMA, greatly affecting the surface texture, were obtained based on the analysis of characteristics of constituents of HMA(i.e. air voids, aggregate, and asphalt mastic). Firstly, the parameters of internal structure of HMA were obtained with section image analysis method. Secondly, the distribution characteristic of aggregate gradation was quantitatively descriped by the fractal dimension. The sieve size with 90% passing ratio, representing the size level of aggregate was decided by regressing aggregate gradation with Weibull distribution model. Thirdly, characteristic wavelength and level of spectrum of HMA surface texture were proposed to represent the comprehensive propertites of surface texture. And then, reasonable design paramters of HMA were formed to predict the texture levels according to the relationship between the characteristic level of spectrum of HMA surface texture and the characteristics of air voids, aggregate, and asphalt mastic. Finally, a model was proposed for predicting the level and distribution of surface texture of HMA.It is significant to predict the coefficient of friction during the braking process for vehicles equipped with Anti-lock Brake Systems(ABS). This dissertation tested the coefficient of friction of HMA with different design parameters and texture characteristics using the Dynamic Friction Tester(DFT) at different testing speeds. At the same time, the maximum coefficient of friction during the braking process of vehicles equipped with ABS was predicted based on the Rado model. The enveloped profile of HMA which actually interacted with the tire was obtained by applying the Hilbert Huang Transform(HHT) on the surface profile of HMA. The octave indexes of surface texture used to predict the skid resistance performance of HMA were selected based on the theoretical analysis of producing mechanisms of friction. A predicted model of the maximum coefficient of friction during the braking process for vehicles equipped with ABS, was ultimately developed based on the levels and distribution characteristics of surface texture of HMA.In order to predict the tire/pavement noise of HMA, this dissertation studied the relationship between the tire/pavement noise and the characteristics of surface texture and noise absorption of HMA. Fist of all, the tire/pavement noise of HMA with different design parameters and texture characteristics, were tested by using the Tire Accelerated Down-rolling Tester(TADT). And then, a noise absorption model of porous HMA was developed based on the Neithalath model and scanning image analysis techniques of HMA. At the same time, the octave indexes of surface texture used to predict the tire/pavement noise were selected based on the theoretical analysis of producing mechanisms of tire/pavement nosie. Finally, predicted models of tire/pavement noise of dense and porous HMA were developed based on the texture levels and coefficient of noise absorption, respectively.