Just owing to fatigue damage mechanics' obvious advantages that can reflect the essence of pavement cracking and facilitate the establishment of a connection between pavement performance and pavement structure, environment, and service life, the theory of fatigue damage mechanics has received increasing attention from road experts and scholars, and its application to asphalt pavement has been widely studied. However, current research still reveals problems that require urgent solutions, such as, the fundamentals of fatigue damage theory remain poorly understood, most research results have not yet been summarized, which hinder the development and wide use of fatigue damage theory. Therefore, this work conducts a systematic review of the fundamental content of fatigue damage mechanics and presents the research in the area of asphalt pavement, including the existing problems, some interesting topics that are worthy of further research are also suggested, which include the development of a triaxial damage constitutive model and a new damage evolution model capable of considering the influence of a mixture's viscoelastic characteristics, temperature, and loading rate on the damage evolution feature of the asphalt mixture. In addition, close-form solutions or viscoelastic calculation for asphalt pavement need to be derived, and other efficient large-scale or microscopic numerical methods for modeling pavement damage performance also need to be studied. The goal of the review is to promote the development and progress of fatigue damage mechanics in the area of asphalt pavement.

To evaluate the sensitivity of basalt fiber content, length-diameter ratio, and modulus to the flexural-tensile properties of fiber-reinforced asphalt mixture, the spatial random distribution of basalt fibers was realized by using the rand function in MATLAB and VBA in AutoCAD. A three-point bending beam with randomly distributed basalt fibers was modeled by ABAQUS finite element software. Basalt fiber content W (0.1%, 0.2%, 0.3%), length-diameter ratio L_d (23, 35, 47), and modulus E (8×10⁴, 9×10⁴, 1×10⁵ MPa) were set for the experiment. Through the orthogonal experiment, the maximum tensile stress at the bottom of the specimens under 0.7 MPa wheel load was calculated, and the sensitivity of the influence of basalt fiber parameters on the flexural-tensile properties of asphalt mixture was analyzed by using range and variance analyses. Results show that the significance of variance analysis is consistent with that of range analysis. The order of sensitivity of parameters is W>L_d>E, which shows that basalt fiber content has the greatest influence on the flexural-tensile properties of asphalt mixture, followed by the length-diameter ratio, and the influence of fiber modulus on the flexural-tensile properties of asphalt mixture can be ignored. With the increase in basalt fiber and length-diameter ratio, the maximum tensile stress of asphalt mixture decreases, indicating the improvement of flexural-tensile performance. With the increase in the fiber modulus, the flexural-tensile properties of asphalt mixture are almost unchanged. The research results are believed to provide a reference for the application of basalt fibers in asphalt mixtures.

This study quantitatively analyzed the shape, angularity, and roughness of road aggregate particles. A contactless three-dimensional (3D) scanning technique was used to capture the 3D coordinate data of point clouds on an aggregate surface. The data were then used to reconstruct 3D elevation digital models of aggregate particles. Six independent feature parameters were subsequently used as an evaluation index to quantitatively describe the multilevel features of the 3D morphology of road aggregates. The methods for calculating and analyzing the feature parameters on the basis of the cloud data of the aggregate scanning point were also presented. The 3D morphologies of four types of road aggregates were studied. On the basis of the results, an aggregate polishing testing system was developed, and the practicability of the 3D roughness coefficient index was demonstrated accordingly. Results show that (1) the sphericity index can describe the compactness of aggregate shape, (2) the shape factor index can describe the needle-flake properties of aggregates, (3) the ellipsoid index can evaluate the sharp edges and corners of aggregates, (4) the maximum surface curvature can be used to identify the local angular features of particles, (5) the two-dimensional roughness index can be used to analyze the anisotropic characteristics of the surface profiles of aggregates, and (6) the 3D roughness index is suitable for evaluating the roughness of aggregate surface texture at the mesoscopic level. Under the experimental conditions of this study, the shape and angular features of aggregate particles matched the requirements of road performance. This result benefitted the formation of an aggregate skeleton structure in asphalt concrete with S>0.76, SF of 0.80-1.20, and E of 0.79-0.88. The aggregate texture was uneven, and the physical adsorption between the asphalt and the aggregates on the contact surface was relatively high when JRC^3D ≥ 11.0.

Aimed at the working life of bridges under the reiteration function of vehicle load, which is not mentioned in the current bridge design codes, this paper introduced the concept of normal working life. The authors regarded reinforced concrete bridges as the research object and proposed a fast method to calculate the working life to judge whether the working life can fit the requirement of design working life. On the basis of the equivalent constant amplitude stress amplitude method of Miner's criterion, the cumulative damages of the bridges were calculated, the average annual damage degrees were obtained by determining the relationship between cumulative damages and times, and the working life of the bridges was estimated. This method was applied to the calculations of T-beam bridges, and the influences of spans, transverse diaphragms, reinforcement ratios, vehicle loads, and S-N curve equations were analyzed. The calculation results showed that vehicle loads and S-N curve equations determine the accuracy of working life. The calculated life in accordance with the fatigue vehicle model in the specification is much longer than the design life. The load varies greatly from region to region. Compared with Guizhou Province, Jiangsu and Liaoning provinces have a higher traffic flow of heavy vehicles over 35 t, which results in years unfilled with the design life. With the increase in spans, the working life increases accordingly because the reinforcement ratios increase with the spans. The diaphragm plates and reinforcement ratios have a great influence on the working life. The working life of bridges with diaphragm plates is 18%-63% lower than that of bridges without diaphragm plates. The reinforcement ratios are lower, and the reduction rates of the working life are greater.

The bridge health monitoring system is being increasingly applied to bridge structure monitoring nowadays. However, due to the limitation in monitoring means and data analysis methods, many deficiencies still exist in the analysis and utilization of the monitoring data of bridge structures. In particular, damage identification and assessment technology is far from reaching the practical stage, and this restricts the development of the overall health monitoring technology. On the basis of the analysis of the strain responses of a bridge under vehicle load by using the theory of bridge strain influence line, we put forward a bridge damage identification and evaluation method based on strain ratio. The stiffness degradation matrix of the structure is deduced using the strain ratio of the corresponding parts of the test and reference sections, and the strain ratio and stiffness degradation matrices are accurately obtained using the load effect of test vehicles under closed traffic conditions. By analyzing a large amount of monitoring data in combination with the theory of random signal analysis and statistical technology, we analyze the probability distribution of the strain ratio and perform damage identification of the test section in accordance with the change in strain ratio distribution. A rapid damage identification method for the test section under closed and open traffic conditions is also proposed. The analysis reveals that the mode of the strain ratio is unchanged when the test section does not experience damage in a certain monitoring period under traffic load. We apply this method to a bridge health monitoring system and adopt Qingyin Yellow River Bridge in Jinan as an example to verify the effectiveness of the method. Results show that the method is efficient, accurate, and universal and can realize rapid and accurate online identification and assessment of bridge damage in closed and normal traffic conditions.

The 3D equation of the ultimate bearing capacity P_b of the karst cave foundation under self-weight γ is established using the associated flow law in the upper limit method of limit analysis on the basis of the Hoek-Brown strength criterion and the punching failure mode of the karst cave foundation. In combination with the variational principle, the equation of the punching failure line and the ultimate bearing capacity expression of the karst cave foundation are derived. The ultimate bearing capacity P_b and critical hole diameter of the karst cave foundation under self-weight are calculated by programing. The theoretical rationality is verified by indoor model tests. The research shows that:(1) The influence of the rock RMR value and uniaxial compressive strength σ_c on the ultimate bearing capacity of the karst cave foundation has nothing to do with the consideration of the self-weight γ factor. Both factors increase with the increase in uniaxial compressive strength σ_c and RMR value, and vice versa. These factors decrease with the increase in self-weight γ; however, the change is obscured; (2) The ultimate bearing capacity of the karst cave foundation P_b basically linearly increases with the increase in the thickness of the roof h of the cave; when considering the self-weight σ and thickness of the roof h, the change of the ultimate bearing capacity P_b of the karst cave foundation mainly depends on the difference between the increment of the internal dissipative and gravity power; (3) When RMR<40, self-weight γ has a great influence on the critical span D of the cave, and when RMR>60, self-weight has a small influence on the critical span D of the cave; (4) When RMR ≤ 40, the influence of self-weight γ on the ultimate bearing capacity P_b must be considered; when RMR ≥ 70, self-weight γ must be considered when calculating the ultimate bearing capacity P_b of the karst cave foundation because the error is generally within 3%.

To study detour scheme after failure of urban transit station, urban transit network model is constructed by considering the reciprocal of urban transit line departure time interval as the weight. In accordance with the characteristics of the traffic flow, the network is studied under different time intervals, namely, morning, evening, and flat rush hours. First, an urban transit network topological characteristic index analysis model was constructed by combining ABC management method to identify the key elements of each indicator. Second, on the basis of the research on topological characteristic indicators, average path length and global efficiency of the network were used to measure the urban transit network connectivity, and an urban transit network station failure optimization scheme was designed. The optimization effect was judged by the changes in the two index values before and after the bus stop detour in accordance with the number of stations in the bypass area, namely, two stations, one station, and zero stations. Finally, the reliability of the model is studied, considering the urban transit network in Huangdao District of Qingdao. Through the analysis of node degree, second-order node degree, centrality, and other indicators, the urban transit network in Huangdao District of Qingdao was found to have evident small-world characteristics, and the top ranking stations of node degree value and centrality index are mainly distributed in the new urban edge planning area and the urban center area. In addition, for stations with the same rank, the node centrality value at each time interval has the following order:morning rush hours> evening rush hours> flat rush hours. The top 10 urban transit stations with node degree value are selected as the failure stations for optimization analysis. Results show that the average shortest path length of the optimized network decreases, the global efficiency of the network increases, and the optimized scheme is reliable.

To alleviate traffic congestion in key areas, such as city centers, this study proposes an optimal pricing strategy that is based on the distance that users travel in a given cordon. The proposed strategy is derived from the theory of the macroscopic fundamental diagram (MFD). In this strategy, a non-negative, non-decreasing, and nonlinear distance-toll function is defined by a piecewise linear approximation method. A bi-level programming model is then constructed on the basis of the toll charge function and the characteristics of the MFD. The upper model considers the overall operating efficiency of the system and aims to maximize the outflow of the road network. The lower model assumes that users' route choice behavior complies with Wardrop's first principle to formulate a user equilibrium model under a fixed demand. In view of the non-additive property of path cost imposed by the nonlinear distance-toll function, the network transformation technique is used to realize the conversion between real networks and virtual networks. The Frank-Wolfe algorithm based on road segments is then used to solve the lower model. The verification of the reasonable feasibility of the pricing model and algorithm reveals that the implementation of cordon pricing schemes based on distance can make the outflow of the border area maintain the best level. Moreover, the obtained optimal charge function makes the system run efficiently. These results prove that the nonlinear optimal toll charge function is realistic and effective.

Temporary traffic flow observation plays a pivotal role in transportation planning, consultation, and decision-making, and it supplements fixed long-term traffic observation data. Although substantial automated technology has been used for traffic observation, such technology is limited by the temporariness and uncertainty of observation points; moreover, these methods are difficult to use in temporary observations. In this study, the YOLO_V3 algorithm, which is based on deep learning, is used for vehicle detection based on roadside videos of temporary observations. Moreover, a secondary detection framework based on vehicle detection and traffic counting regions is proposed. Then, a traffic counting pattern with Kalman filter, Hungarian allocation, and perspective projection transformation is established. In addition, by collecting multiple sets of actual video data, the effectiveness of the method under different conditions is analyzed in terms of three indicators:camera intersection angle with the road, erection height, and road traffic density. Results show that at a camera height of 3 m and a roadside angle of 30°, the accuracy is approximately 95%. However, traffic flow accuracy drops to approximately 90% when vehicles are blocked by large buses and trucks during detection. In this study, the algorithm is tested for execution efficiency using 1080p video streams on a Windows 10 x 64 operating system, a 2080Ti graphics card, a 64 GB RAM, and an i7-7820X CPU. Results show that camera installation angle and height have no considerable effect on operation efficiency. Under low-density traffic, the frames per second (FPS) value is approximately 44; under high-density traffic, the FPS value drops to approximately 33, indicating that the method still has high execution efficiency and can be used for real-time video traffic counting.

The vehicle operation condition for a certain kind of vehicle is used to describe the relationship between vehicle speed and time in a specific traffic environment. The experimental group uses the acquisition device dash cam to record the driving data of a light vehicle in Shanghai for research to quickly and accurately build the operation condition of the vehicle. The information of three different periods of time for three consecutive times is also collected with the sampling frequency of 1 Hz. We use smooth processing, elimination, attribution, and sliding window method to preprocess the huge data of vehicle operating condition for studying the driving condition of automobile. A total of 724 time discontinuities are divided into three types for different processing, smooth processing with smooth function of moving average filter to eliminate the abnormal value of speed, and idle processing with long-term parking. Thereafter, the method of sliding window is used to process the idle speed data. Then, the kinematic segments are cut, and the feature values are extracted. Finally, the dimension of 13 features is reduced to four principal components. On the basis of three methods, such as contour coefficient, K-means clustering analysis method is used to continuously verify and divide the dataset into three categories, namely, stop and go, high-speed driving, and low-speed driving, which are consistent with the reality. According to the time proportion of each category, the most representative 15 segments are selected to construct the 1254 s long steam. The error rate of the result is less than 10%. The construction model of the vehicle operation condition is very detailed for the data processing process of the vehicle operation condition, and the model constantly seeks optimization on the basis of the initial clustering center. This work provides a reference for the establishment of the vehicle performance research in line with the traffic and actual operation conditions of specific cities in China.