To uniform the evaluation indicators of Styrene-Butadiene-Styrene (SBS) modified asphalt, the SK70# and SK90# matrix asphalt were modified by different SBS modifier dosage in this study. The test methods in China and Superpave were used to test the performance of each SBS-modified asphalt respectively, from which the appropriate evaluation index of SBS-modified asphalt was determined. The results showed that the addition of SBS modifier improved the high temperature performance and lowered the temperature sensitivity of asphalt binder, while it increased the viscosity of asphalt binder in high temperatures. Due to the variability that appeared in the results of the penetration test by the swelling of SBS-modified asphalt, the penetration test was not recommended to evaluate the performances of SBS-modified asphalt. The softening point of SBS-modified asphalt with the modifier dosages of 4.5%, 5%, 5.5% and 6% increased 5.7%, 12.8%, 22.5% and 26.4% respectively compared to the matrix asphalt for SK70# matrix asphalt, and increased 21.2%, 26.3%, 33.6% and 46.6% respectively compared to the matrix asphalt for SK90# matrix asphalt. The effect of SBS-modifier on the softening point of SK90# matrix asphalt is significantly better than that of SK70# matrix asphalt. The improvement effect of SBS modifier on low temperature performance of matrix asphalt decreased with a decrease in test temperature. When studying the influence of the SBS modifier on the low temperature performance of asphalt binder, it was recommended to use the bending beam rheometer (BBR) test to evaluate the low temperature performance of SBS-modified asphalt.

In order to provide a new method to study the migration behavior of coarse aggregates in the compaction process of asphalt mixtures, the “Intelligent Aggregate Attitude Acquisition System (IAS)” is developed based on 3D printing technology and wireless intelligent sensing technology, and the “Intelligent Attitude Aggregate (IAA)” is prepared as the acquisition terminal. The Superpave Gyratory Compaction (SGC) test and the Internet of Things (IOT) wireless sensor technology are combined to collect and analyze the attitude data of an SMA-20 asphalt mixture built in IAA at different compaction stages, and the migration behavior of coarse aggregate in the compaction process is quantitatively characterized. The result shows that the IAA is suitable as a “tracking aggregate” to study the aggregate transfer behavior in asphalt mixtures. The IAA in the upper layer tends to move vertically downward, while the particles in the lower layer tend to move horizontally and spatial rotation in the process of rotating compaction. With the increase in asphalt content, the lubrication effect between aggregate particles is obvious, and the friction resistance of aggregate particles decreases when it is embedded downward. Affected by shear force in the process of rotary compaction, the aggregate particles are easier to overcome friction and cause large horizontal migration and spatial rotation. With the increase in compaction temperature, the viscosity of asphalt binder decreases, and the contact friction between aggregate particles decreases. The asphalt content has a significant effect on the displacement in the horizontal plane D_xoy of the aggregate. The asphalt content and compaction temperature have significant effects on the spatial rotation angle Φ of aggregate, but the asphalt content has a greater impact on it.

Emulsified asphalt mixture has the characteristics of convenient construction and durable performance, but its poor early strength and demulsification seriously restrict the popularization and application of this material. At present, the coal gangue produced by coal‐fired power plants is generally discarded, resulting in serious environmental pollution. The combination of coal gangue and emulsified asphalt can explore an efficient utilization way for more and more coal gangue and also solve the curing problem of asphalt. In order to give full play to the advantages of existing materials and make rational use of resources, this paper studies the factors affecting the performance of coal gangue emulsified asphalt mixture based on orthogonal experimental design and optimizes its material composition parameters by considering the coupling effect of two factors. The water stability of coal gangue emulsified asphalt mixture is evaluated by the immersion Marshall test. Finally, the strength formation mechanism of coal gangue emulsified asphalt mixture is analyzed from the microscopic point of view. The results determined 7.5% as the optimum amount of emulsified asphalt in coal gangue emulsified asphalt mixture and recommended the best parameter combination of 7.5% emulsified asphalt, 6% coal gangue, and 5% water consumption. With the increase of coal gangue content, the water loss resistance of emulsified asphalt mixture increases gradually, and the water stability of emulsified asphalt mixture can be improved by adding coal gangue. According to the microscopic analysis, the strength of the mixture is formed by the joint action of emulsified asphalt and coal gangue, in which the hydration products of coal gangue and asphalt play the role of cementation and strength together. The ordinary emulsified asphalt mortar mainly contains CaCO₃, which mainly plays the role of physical filling.

Reliable transverse crack prediction can benefit the design and maintenance and improve the reliability of field investigation for asphalt pavement in permafrost regions of Qinghai-Tibet plateau. This study adopted the crack prediction model in the newly developed pavement design method named Pavement ME Design (PMED) and the modified grey predictive model (GM (1, 1)) to predict the transverse crack of asphalt pavement in permafrost regions. The complementary advantages for the two models based on the weight distribution theory were discussed, and a combined prediction model (PME-DGM combination model) taking account into region characteristics was developed. Finally, the applicability of combined prediction model was analyzed. The result showed that, the predictive accuracy of PME-DGM combination model established by the error sum of squares reciprocal method was the highest, the best weight allocations for each sub-model were L_NCH = 0.601 and L_DGM = 0.399, and the combination model can be applied in the permafrost region involved in this paper; The combination model is more appropriate in predicting the development trend of transverse crack of project-level asphalt pavement in permafrost regions; For PMED predictive model, this study raised a modified method base on a third-party model (DGM (1,1), and the result showed that the method worked well in the permafrost region of Qinghai-Tibet plateau.

The traditional evaluation method of construction quality for asphalt pavement has gradually lagged behind the pace of development of the road industry. Big data, Internet of Things (IoT), and intelligent sensing technology have been reflected in the field of road engineering, but these technologies also have technical shortcomings in terms of applicability, durability, real‐time performance, and portability in practice. To provide a new method for construction quality evaluation of asphalt pavement, this study developed an intelligent sensing aggregate (ISA) with low cost and high precision based on the 3D printing and Internet of Things (IoT) technology. Based on the laboratory test and field test, the sensing characteristics, high‐temperature resistance, and mechanical properties of ISA are analyzed to verify the reliability of ISA. Through the quantitative analysis of ISA perception data, the Driving Perception Index (DPI) is proposed. By analyzing the quantitative correlation between the spatial angle of ISA and the compaction degree, the quantitative correlation between the DPI, International Roughness Index (IRI), and the deflection value, the evaluation standard of construction quality for asphalt pavement is established. The result shows that the best baud rate for ISA is 9600 bps, and the corresponding data transmission distance is 350 m. In the range of 6 m, the cars, trucks, trailers, and buses can be perceived by ISA. The maximum operating temperature of ISA is up to 200°C. Embedding ISA into asphalt mixture has no significant effect on original gradation of asphalt mixture. The established evaluation standard of construction quality for asphalt pavement takes into account the compaction quality, the requirements of bearing capacity, and the driving comfort of asphalt pavement, which is suitable for expressway and first‐class highway.