Cracking is a common pavement distress that would cause further severe problems if not repaired timely, which means that it is important to accurately extract the information of pavement cracks through detection and segmentation. Automated pavement crack detection and segmentation using deep learning are more efficient and accurate than conventional methods, which could be further improved. While many existing studies have utilized deep learning in pavement crack segmentation, which segments cracks from non‐crack regions, few studies have taken the exact pavement crack detection into account, which identifies cracks in the images from other objects. A two‐step pavement crack detection and segmentation method based on convolutional neural network was proposed in this paper. An automated pavement crack detection algorithm was developed using the modified You Only Look Once 3rd version in the first step. The proposed crack segmentation method in the second step was based on the modified U‐Net, whose encoder was replaced with a pre‐trained ResNet‐34 and the up‐sample part was added with spatial and channel squeeze and excitation (SCSE) modules. Proposed method combines pavement crack detection and segmentation together, so that the detected cracks from the first step are segmented in the second step to improve the accuracy. A dataset of pavement crack images in different circumstances were also built for the study. The F1 score of proposed crack detection and segmentation methods are 90.58% and 95.75%, respectively, which are higher than other state‐of‐the‐art methods. Compared with existing one‐step pavement crack detection or segmentation methods, proposed two‐step method showed advantages of accuracy.

In recent years, concerns about the depletion of nonrenewable resources, infrastructure sustainability, and environmental impact in pavement engineering have led to substituting petroleum-based paving materials with their biobased counterparts. Research efforts have been attempted to produce asphalt from renewable bioresources. As a special modifier for asphalt, petroleum-based epoxy resin has been used in a few asphalt paving projects that require superior performance of asphalt mixtures. This paper presents an attempt to develop a biobased epoxy modifier for asphalt using an epoxidized soybean oil (ESO) and a biobased curing agent, maleic anhydride (MA). The proper proportions of ESO, MA, and a base asphalt were determined to achieve a homogenous biobased epoxy asphalt binder (BEAB) with the desired properties evaluated by a rotational viscosity test, a penetration test, and a dynamic shear rheometer test. Pavement performance–related properties of asphalt mixtures using such a BEAB were also preliminarily evaluated using a Marshall stability test. At an optimum ratio of $0.45:1:8$ for $\mathrm{MA}:\mathrm{ESO}:\text{asphalt}$ , the BEAB showed higher Marshall stability than a mixture containing the base asphalt. Further research, however, is still needed to evaluate the asphalt mixtures with more pavement performance–based tests and to refine the BEAB formula.

The long-span steel bridge has experienced a rapid growth in China during the last two decades. Steel deck surfacing plays an important role in the durability of long-span steel bridges. So far, three types of surfacing materials have been used in China’s experience: epoxy asphalt (EA), Gussasphalt (GA), and stone matrix asphalt (SMA). Four main double-layered surfacing structures have been used via the combination of the three materials, GA-EA (EA on the top), GA-SMA, EA-SMA, and EA-EA. The objective of this study is to identify the best surfacing strategy from the four existing double-layered structures. A comprehensive performance evaluation was conducted to achieve this goal. The rutting resistance, low temperature performance, fatigue performance, and moisture damage resistance were evaluated for the individual surfacing materials, double-layered surfacing structures, and the composite structures consisting of steel deck and surfacing structures. The results showed that EA-EA had the best high-temperature performance, GA-EA had the best low-temperature performance, GA concrete had the lowest moisture susceptibility, and GA-EA possessed the best fatigue performance. In addition, the layer position had an influence on the rutting performance of the double-layered structure. Then, a simple ranking method taking account into the comprehensive performance was used to identify the best surfacing strategy. The GA-EA structure was found to be the best surfacing strategy for long-span steel bridges in China after the comparison.

The interfacial zone between aggregate particles and asphalt mortar presents a significant effect on the strength of an asphalt mixture. In this paper, basalt, limestone, and diabase were selected, and the influence of these aggregates on the mechanical characteristics and microstructures of the interfacial zone was investigated. Nanoindentation was employed to measure the change law of mechanical behavior in the region of the interfacial zone, and corresponding viscoelastic parameters were deduced; microstructural morphology was observed by scanning electron microscopy, and the effect of the mineralogical components on the interfacial zone was analyzed as well. Results show that the mechanical behavior of the interfacial transition zone is complicated. The modulus and hardness of asphalt mortar decrease with the increases in the aggregate surface distance, and then keep stable after the distance is greater than 40 μm. Both the relaxation time and dissipated energy ratio of the interfacial zone affected by the different aggregate types show a similar change law. These states indicate that aggregate types have little influence on the stress dissipation of asphalt mortar. However, creep compliances that quantify the ability of the deformation resistance show a significant difference; microstructure morphologies of the interfacial zone are affected by aggregates obviously, and micro pores present a different distribution and state in the interfacial zone.

Anti-skid performance is the most critical indicator that reflects the safety performance of the road surface. A good anti-skid performance of the road surface guarantees the safe and fast driving of vehicles. However, the asphalt pavement of highways has gradually exposed the anti-skid performance attenuation, which affects driving safety. Therefore, this study aims to accurately evaluate the anti-skid durability of asphalt mixtures based on a 1/3-size accelerated loading test with different anti-skid surfaces as the research object and explores the key factors affecting the long-term anti-skid performance of asphalt mixtures. The texture depth test and the pendulum value test show that the anti-skid durability of the SMA asphalt mixture is better than that of the AC asphalt mixture. The attenuation prediction equation of the British Pendulum Number (BPN), an anti-skid performance index based on an indoor accelerated loading test, was constructed. After the accelerated loading test stabilized, the BPN and BPN attenuation rate b were used as an index to evaluate the anti-skid durability of the asphalt mixture.