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Pavement performance prediction is a crucial issue in big data maintenance. This paper develops a hybrid grey relation analysis (GRA) and support vector machine regression (SVR) technique to predict pavement performance. The prediction model can solve the shortcomings of the traditional model including a single consideration factor, a short prediction period, and easy overfitting. GAR is employed in selecting the main factors affecting the performance of asphalt pavement. The SVR is performed to predict the performance. Finally, the data collected from the weather station installed on Guangyun Expressway were adopted to verify the validity of the GRA-SVR model. Meanwhile, the contrast with the grey model (GM (1, 1)), genetic algorithm optimization BP[[parms resize(1),pos(50,50),size(200,200),bgcol(156)]]081%, −0.823%, 1.270%, and −4.569%, respectively. The study concluded that the nonlinear and multivariate prediction model established by GRA-SVR has higher precision and operability, which can be used in long-period pavement performance prediction.

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Unlike other road materials, aeolian sand has some compaction characteristics that are key factors in construction qualities of highway in the desert. In order to study the characteristics, a series of laboratory and field tests were performed, including sieve analysis, standard modified compaction, vibrating compaction and field test. By analyzing the sieve analysis test data, it was found that the gradation of aeolian sand was bad, with fine grains whose diameters mostly ranged from 0.25 mm to 0.074 mm. Then, from the laboratory compaction test results, a compaction curve similar to the horizontallywritten letter S was obtained. That was quite different from the other kinds of road materials. There were two peak values in the curve with the increase of water content, which was the special characteristic of aeolian sand: to be well compacted whether it was dry or wet. Also, according to laboratory vibrating test results, the best vibrating frequency range was proposed. It was from 45 Hz to 50 Hz. Moreover, some field compaction tests were carried out. On the construction site of the highway, the aeolian sand subgrade was compacted in the condition of natural water content with optimizing construction machines. Its compaction degree reached 96%, meeting the current specifications. At last, comparative studies were carried through with electron microscope. It was shown that the microstructure of compacted dry aeolian sand is much denser than that of the natural one in the field test.