With the continuous promotion of strong transportation strategies, the demand for high-quality sand and gravel materials in China's transportation infrastructure remains high. Environmental protection requirements continue to grow, and the shortage of natural resources continues to exacerbate. Therefore, alternatives to sand and gravel aggregates have become the main direction of development in the field of road engineering. China's western region has long been plagued by wind and sand problems, and successive exploratory studies have been conducted on the application of aeolian sand in road engineering, which have confirmed the significance of aeolian sand resource utilization for promoting green and low-carbon transportation in the sustainable development of road engineering industry. Therefore, this study focuses on the problems of large regional differences in aeolian sand and the lack of corresponding standardized research. The physicochemical properties of aeolian sand and its engineering characteristics in different regions are systematically discussed, analyzing its potential activity, excitation mode, and mechanism. The progress of research on the application of aeolian sand in roadbed and pavement engineering is summarized, thereby illustrating the influence and mechanism of aeolian sand on the performance of pavement concrete and semi-rigid bases, comprehensive utilization and treatment technology of aeolian sand in roadbed engineering, prevention and control of wind-blown sand of aeolian sand roadbeds, and performance of aeolian sand roadbeds in resisting scouring and water damage. Finally, development trends in the application of aeolian sand and research focus directions for the future of road engineering are presented.

The vibration-based road roughness detection technology, which estimates road roughness by measuring vehicle vibrations induced by road profiles, has been of interest in recent years. To address the challenges of labor-intensive calibration and limited stability in existing vibration-based road roughness detection methods, a rapid calibration method based on parameter estimation is proposed, accompanied by a sensitivity analysis of the vehicle vibration parameters' impact on the detection performance. This approach begins by constructing a seven-degree-of-freedom full-vehicle dynamics model and introduces a calibration method based on impact testing, with a model updating approach. Subsequently, a virtual simulation platform is established to simulate various road evenness conditions, replacing the traditional labor-intensive calibration process and obtaining multiple regression models for vehicle vibration indicators, vehicle speed, and international roughness index (IRI). Relying on the calibrated vehicle model, the influences of vehicle suspension parameters and fluctuation in vehicle mass distribution on the IRI detection performance were investigated. Field tests and research results demonstrate that the calibrated vehicles' evenness detection results align well with the laser profiler, with detection errors significantly correlated with the segment length and detection speed. Under conditions with segment lengths of 100 m or larger and vehicle speeds of 30 to 60 km·h^-1, the IRI detection errors are within 0.5 m·km^-1. A sensitivity analysis reveals that the tire equivalent stiffness coefficients and suspension stiffness coefficients exhibit the highest sensitivity, which highlights the significant impact of tire pressure variations and suspension spring wear on the evenness detection. This research provides a methodological support to advance the widespread application of the vibration-based road evenness detection technology.

Transportation sector is one of the major sources of global carbon emissions, and as a major transport country, China is facing a huge challenge to reduce transportation carbon emissions. Researchers have conducted extensive research on carbon emission assessment and emission reduction measures in recent years. This paper focuses on the highway construction stage, reviewing previous studies on three aspects: carbon emission assessment, carbon reduction, and carbon sequestration compensation. The results show that: most carbon emission assessment methods use the Life Cycle Assessment(LCA) model throughout the highway construction stage, in which the basic data accounting focuses on the emission factor method, as well as software, platforms, and other tools combined with artificial intelligence; emission side of the carbon reduction is mainly centered on green geo-technology, solid waste resource utilization technology, and green-efficient project management, to completely accomplish the carbon reduction goal; carbon compensation research includes compensation measures and effect evaluation of the carbon sequestration, and its carbon compensation measures are mainly in using slope vegetation photosynthesis to sequester carbon and new materials to increase carbon sinks. Moreover, carbon sequestration effects are evaluated using the subjective-objective combination analysis method. The analysis reveals that unsolved problems still exist: lack of unified standards for emission factors, leading to considerable errors in carbon emission assessment; lack of comprehensive assessment methods for the specific emission reduction ratio of emission reduction measures and the poor combination with artificial intelligence; the carbon compensation measures are largely insufficient and the carbon sequestration effect assessment method is subjective. Future research should focus on exploring the accuracy of the assessment method; proposing more effective carbon emission reduction measures and enhancing the research on the assessment of emission reduction effect; adopting more diversified carbon compensation measures, and establishing a universally applicable compensation effect assessment method. This review paper provides a comprehensive reference for carbon emission reduction research in transportation geotechnical field and assists in realizing the goal of the “carbon peaking and carbon neutrality” strategy.

To investigate the dynamic response characteristics of loess under impact loading, a series of impact compression tests with varied strain rate were conducted on loess samples with four different moisture contents of 13%, 16%, 19%, and 22% using the split Hopkinson pressure bar (SHPB) testing technique. The design speeds of the impact rod were 4, 6, 8, and 10 m·s^-1. The experimental results show that the dynamic stress-strain relationship of loess under impact loading exhibits obvious subsection characteristics. It can be divided into three stages: elastic deformation, plastic flow, and failure. The strain rate and moisture content significantly influence the dynamic characteristics of the loess samples. An increase in strain rate prolongs the plastic flow process of the loess, while an increase in moisture content leads to a transition from a predominantly plastic flow characteristic to a brittle failure in the dynamic stress-strain development of the loess. The yield strength, failure strength, and failure strain of the loess increase with the increase in the strain rate and decrease with the increase in the moisture content. The compressive wave velocities of the loess samples are primarily influenced by the moisture content. The higher moisture content results in higher compressive wave velocities. Additionally, a Z-W-T component model considering damage evolution was used to simulate the dynamic response of the loess. The simulated stress-strain relationship of the loess shows a good agreement with the SHPB experimental results. Further analysis of the model parameters reveals that the response of the loess is considerably more sensitive to high strain rates than to low strain rates.

To study the effect of the load on bearing characteristics of slender energy piles, a centrifuge model test was conducted with different loads applied on slender frictional energy piles, and the energy piles were subjected to 30-year thermal-cold cycles. The centrifuge acceleration was 70g. The model pile was composed of aluminum tube. Five groups of strain gages and six groups of thermistors were set uniformly throughout the pile body to measure the axial force and temperature. Standard Fengpu sand was used as the test material around the pile and bearing layer of the pile bottom. 30 hot-cold cycles were applied to the energy piles with free and top loads. In a slender pile with a length-to-diameter ratio of 50, the maximum axial force occurs at 3/4 of the depth in the middle and lower parts of the pile approximately, as a result of the coupling effect between the change in temperature and the friction resistance at the lower part of the pile. The influence of the circulating temperature on the axial force of the pile is primarily concentrated in the first cycle. The slender pile body causes the tip of the frictional pile to exhibit a certain end-bearing effect. In the thermal cycle stage, the end of the slender energy pile exhibits a large embedment depth, and the axial force of the lower part changes significantly. During the cold circulation process, slender piles with load on the top have a deeper embedment distance at the lower part of the pile body. The application of pile-top loads can reduce the attenuation value of the pile shaft axial force and the negative friction resistance on the pile side caused by heating. For energy piles subjected to a combination of top load and long-term cycle temperature, the bearing capacity of the energy pile foundation is reduced to a certain extent. The bearing capacity of the pile head reduces by 14.8% compared with that of the energy pile with a free pile head, while keeping the pile head load unchanged. Therefore, the long-term bearing characteristics of energy piles should be considered in the design.

This study aims to determine and intelligently predict the optimal vibration frequency of subgrade-filler compaction. The natural frequencies of different material-compaction degrees were determined through vibration-compaction experiments and the hammer modal method. The correlation between the natural frequency and optimal vibration frequency was determined, based on the maximum dry density of the materials and the dynamic stiffness. The relationship between the material characteristics and optimal vibration frequency was established, and the key control-feature parameters of the optimal vibration frequency were proposed. A machine-learning prediction model based on the key control-feature parameters was constructed and the prediction model was optimized using a bilevel evaluation method. The results indicate that the vibration frequency at the natural frequency results in the largest maximum dry density and the most optimal state for dynamic stiffness. The key controlling features influencing the optimal vibration frequency include the maximum particle size of the material, gradation parameters, content of needle-shaped particles in the coarse aggregate, and Los Angeles abrasion value. In a comparative analysis of the prediction models, the artificial neural network (ANN) model is considered to have the best goodness-of-fit and can be used as the core model for optimal vibration-frequency prediction. The research findings provide a novel approach for determining the optimal vibration frequency in subgrade compaction and offer theoretical guidance and support for intelligent subgrade construction.

Water content at the root-soil interface is often unsaturated due to transpiration and water absorption in plants. To quantify the contribution of interfacial suction to the shear strength of the root-soil interface, a shear-strength model of the root-soil interface considering interfacial suction was developed based on the principle of unsaturated effective stress. The model divides the shear strength of the root-soil interface into two parts: one caused by the net normal stress, and the other by the interfacial matric and tension suctions. The root-soil interface shear strength of the roots of four plants, Magnolia multiflorum, Privet microphylla, vetiver, and Robinia pseudoacacia, was measured under different interfacial suction and normal load conditions using a single pull test. The relative error of the test and model values was less than 9%, verifying the accuracy and reliability of the model. The root-soil interface friction coefficient was significantly correlated with root surface roughness by analyzing the influencing factors of the model. Among them, the average height of the root surface roughness index had the largest correlation with the root-soil interface friction coefficient, with a correlation coefficient of 0.96 and a weight of 0.35. The effective stress parameters were closely related to the bending surface radius, saturation radius, and filling and contact angles, and increased with the increase in interfacial volume water content. The interfacial suction stress depends on the relative magnitude of the matrix suction and the effective stress parameter; it increased first and then decreased with the increase in the interfacial volume moisture content. The above results provide reference for further exploring the mechanical mechanism of root-oil interface interaction and optimizing the ecological protection design of slope.

The stability analysis of a slope reinforced with a frame-prestressed anchor rod structure under an earthquake action is required for practical applications. Pseudodynamic and limit equilibrium methods were used, and the unit horizontal spacing of the anchor rod was adopted as the calculation unit. The dynamic safety coefficient of a slope under an earthquake action and the formula for determining the variation in the anchor rod axial force were derived, considering the dynamic variation in the anchor rod axial force under the earthquake action. The stability of the slope reinforced with a frame-prestressed anchor rod structure under an earthquake action was analyzed by programming a solution using MATLAB. The results show that the traditional methods of calculating the slope stability coefficient based on the initial prestress or ultimate pullout bearing capacity of anchor rods may underestimate or overestimate slope stability. The method proposed in this study considers the gradual transition of the axial force on the anchor rod from the prestress to ultimate pullout bearing capacity, providing a more accurate evaluation of the stability of the slope reinforced with the frame-prestressed anchor rod structure. Within a cycle, slip may occur when the stability coefficient of the slope is lower than 1, and the anchor rod undergoes elastic deformation, with its axial force increasing periodically. The reinforcement force provided by the frame-prestressed anchor rod structure increases, stabilizing the slope and resulting in a gradual decrease in the axial force growth rate of the anchor rod. The stability coefficient within a cycle first decreases to a minimum value and then increases, showing an overall cosine variation pattern. With time, the stability coefficient improves within a cycle. The horizontal spacing of the anchor rod is the most significant factor that influences the stability of the slope reinforced with the frame-prestressed anchor rod structure during an earthquake, followed by the internal friction angle of the soil, acceleration coefficient, and soil cohesion. The amplification coefficient of the acceleration amplitude has the second most significant impact on the slope stability, whereas the inclination angle of the anchor cables has the least impact.

Load-carrying capacity is a key index reflecting the service performance of highway bridges. Its reliable evaluation is key for determining the safety risk of bridges in advance, which can provide an important basis for decision-making, such as that pertaining to bridge reinforcement and reconstruction. In this study, the connotations of bridge load-carrying capacity evaluation were analyzed from the aspects of evaluation targets and evaluation methods, the current development of technical standards for load-carrying capacity evaluation in the United States and China was introduced, and the implementation method and evaluation theory of proof and diagnostic load-testing methods were demonstrated. Proof load testing can directly determine whether the bridge load-carrying capacity satisfies the requirements, whereas diagnostic load testing should be further developed in the future as it offers more bridge information and ease of implementation. Additionally, in this study, the verification theory used for the load-carrying capacity in the codes of various countries was systematically compared; three types of resistance correction methods, including direct structural testing, state-parameter mapping, and a time-varying deterioration-prediction model, were summarized; the correction methods for the bridge load effect were described comprehensively in terms of load and bridge models; and the reliability targets of bridge evaluation in various countries were analyzed. The British and American codes have established a multilevel evaluation reliability target by discounting the design load and resistance factor, which is worthy of reference for the Chinese bridge evaluation code. Finally, an outlook into the future development of load-carrying capacity evaluation methods in terms of testing methods, evaluation theories, and technological equipment is presented.

To solve the problems of easy rusting of assembled segmental pier reinforcements in coastal erosion environments and large residual displacements of bridge piers after strong earthquakes, hybrid reinforced precast segmental assembled concrete piers with stainless steel reinforcement and unbonded prestressed glass fiber-reinforced polymer (GFRP) bars are proposed. The damage modes of the hybrid-reinforced piers were revealed through the proposed static tests. In addition, the seismic performance parameters including hysteresis performance, bearing capacity, energy dissipation, residual displacement, prestressing change, stiffness degradation, rebar strain, and joint opening of the piers were analyzed and compared with the seismic performance of the hybrid-reinforced segmental-assembled piers with bonded non-initial prestressed GFRP tendons. The results show that the unbonded GFRP reinforcement applied 50% of the vertical axial compression ratio of the top of the pier preload, and the residual displacement of the specimen could be reduced by nearly 40%; however, the peak bearing capacity was reduced by approximately 20%. With an increase in the reinforcement rate of the GFRP reinforcement and a reduction in the reinforcement rate of the stainless-steel reinforcement, the residual displacement of the specimen was reduced by 38%, and the bearing capacity was reduced by 10%. The vertical axial pressure ratio at the top of the pier, i.e., the effect of P-Δ effect on the maximum bending moment at the bottom of the pier, is more apparent. With sufficient initial tensile force and reinforcement rate of unbonded prestressed GFRP tendons, while considering the influence of the ultimate tensile strain of GFRP tendons, the same horizontal bearing capacity as the bonded case can be achieved, but the residual displacement of the pier column can significantly reduce.

This research aims to clarify the failure modes and crack development patterns of engineered cementitious composite (ECC) to normal concrete (NC) composite beams. The four-point bending test was conducted on five composite beams to investigate the effects of the reinforcement ratio and layer thickness on the structural flexural performance. The research findings demonstrated that the failure modes of ECC-NC composite beams were clearly distinguished from pure NC beams, manifested by better flexural performance and effective utilization of the properties of ECC. Under a constant reinforcement rate, the increasing ECC layer thickness evidently slowed down the stiffness degradation of composite beams, thereby enhancing the flexural capacity of ECC-NC composite beams. Based on the parametric analysis, the optimal thickness of the composite layer was in the range of 0.3h-0.5h, which can effectively play a role in replacing some longitudinal bars. Combined with the response surface method, the maximum reinforcement ratio was found to be related to the thickness of the composite layer, with a negative correlation in the range of 0-0.5h and a positive correlation in the range of 0.5h-h. Therefore, setting ECC in the compression zone can increase the limit reinforcement ratio, and the high reinforcement ratio can improve flexural stiffness and slow down the crack extension. Finally, a calculation method for the bending capacity of ECC-NC composite beams was developed based on the strip method, which can be used to evaluate the capacity evolution accurately, with an error of approximately 6%. This theoretical achievement can offer underpinning for the structural design of composite beams. The comprehensive research of this paper proved that the substitution of NC with ECC not only enhances the structural flexural capacity but also retards the crack extension, and improves the cracking-control ability of composite beams.

To improve the seismic performance of double-column bridges with laminated rubber bearings (LRBs), a novel bearing connection system using a replaceable shape-optimized composite metallic yielding damper (SCMYD) was proposed. The mechanical behavior of the SCMYD-LRB system was analyzed, and a seismic design scheme for bridge structures with SCMYD was proposed. Subsequently, a numerical analysis model for the seismic performance of a double-column bridge in the transverse direction using the SCMYD-LRB system was established, and the accuracy of the model was verified. Finally, a seismic fragility analysis of the bridge using the SCMYD-LRB system was conducted using a probabilistic damage analysis method based on dual seismic intensity parameters. The results indicate that the damage would concentrate on the bearings and shear keys of the bridges under the transverse seismic action. Compared with the bridge equipped only with LRB, the damage to the bearings and shear keys would clearly decrease for the bridge with the SCMYD-LRB system. Regardless of whether the SCMYD-LRB system or only LRBs were applied to the bridge structure, the piers were primarily in a state of slight and moderate damage, with the probability of exceeding severe damage being less than 3%. The reasonable setting of SCMYD ensured that the bridge piers were not severe damage and significantly reduced the risk of the main beam falling damage in the transverse direction of the bridge.

Vortex shedding and drifting are common characteristics of the flow field around bridge girders during the occurrence of vortex-induced vibrations. Based on the spatial and temporal pressure field of the main beam surface, the spatial distribution characteristics of the statistical parameters of the vortex-induced dynamics (e.g., correlation coefficient, contribution value, dimensionless work) are systematically analyzed. The basic theory of simplified vortex-induced dynamics is established, and simplified vortex-induced mechanisms of typical bridge main beams are proposed. This method can deduce the characteristics of key flow fields and the spatiotemporal evolution model of the dominant synchronous aerodynamic force to reveal the vortex mechanism. Using a typical box girder as an example, the simplified vortex method is verified by combining the time-frequency characteristics of aerodynamic force, numerical flow field, and spectral proper orthogonal decomposition (SPOD). The results show that the correlation coefficient, contribution value, and dimensionless work are similar harmonic functions of the phase lag between the pulsating pressure and vortex-induced force (moment) when vertical (torsional) vortex-induced vibration occurs. When the phase lag changes monotonically, the aforementioned statistical parameters show wave-like distribution, and the corresponding dominant aerodynamic force shows traveling wave, space-time evolution characteristics along the flow direction, collectively referred to as aerodynamic traveling wave mode. This mode and the corresponding simplified vortex mode map each other and form the simplified vortex mode together. In vertical vortex-induced vibration, the drift distance from the vortex leading edge separation to the trailing edge is approximately k wavelengths, which requires k vibration cycles; that is, the k^th order vertical simplified vortex mode induced by the separation point dominates. The drift distance from the vortex leading edge separation to the trailing edge is approximately (k+0.5) wavelengths, and it requires (k+0.5) vibration cycles, where k is a positive integer; that is, the k^th order torsional simplified vortex mode induced by the separation point is dominant. The aerodynamic dominant SPOD mode on the upper surface of a typical box girder presents a traveling wave evolution along the flow direction, the correlation coefficient presents a wave-like distribution, and the wave-vortex modes map each other, which verifies the simplified vortex method well. In this paper, the basic theory of simplified vortex is systematically established, and a simplified vortex method system with multiscale aerodynamic spatiotemporal evolution characteristics associated with vibration effects is described as “one body.” A simplified vortex model with key flow field characteristics is deduced, and an aerodynamic traveling wave “two wing” model is constructed to perform accurate simulations of the aerodynamic spatiotemporal evolution characteristics. It provides a new theoretical basis for the analysis of the physical mechanism of eddy vibration in bridge girders, the construction of a mathematical model of eddy-induced force, and the comparison and selection of eddy vibration suppression measures.

This study investigated the material parameter values for the long-life design of concrete cable-stayed bridges and target reliability index values for PC main beam components. In addition, it investigated the random degradation law of concrete strength, a method for determining material parameter values considering the design service life, and a calculation method for the target reliability index considering the material performance degradation of cable-stayed bridge PC main beam components. First, based on relevant measured data, a random process identification of concrete compressive strength degradation under freeze-thaw cycles was conducted. The results show that the degradation law of concrete strength under freeze-thaw cycles followed the Gamma process, and a Gamma process identification method was established. Second, a method was proposed to determine the required material performance values by considering the design service life. Based on the conclusion that the degradation of the concrete compressive strength follows the Gamma process, a one-dimensional probability distribution of the concrete performance degradation process at any time was obtained. The concrete compressive strength design value that meets the requirements of the design service life was determined based on the probability density function with α^' = 0.05 percentile value when the structure is in service until the design service life. Finally, the time-varying flexural bearing capacity of the cable-stayed bridge PC main beam was calculated by considering the degradation of concrete strength, rebar corrosion, and collaborative working capacity degradation of the rebar and concrete. The time-varying reliability index of a cable-stayed bridge PC main beam was calculated using the checkpoint method. Based on the degradation of the service period reliability index, a method was established to determine the target reliability index of the cable-stayed bridge PC main beam, considering the design service life under the condition of a long-life design. This study provides a reference for reasonably determining target reliability index values for cable-stayed bridges.

Fiber reinforced polymer has the potential to replace traditional steel cables in long-span cable-bearing bridges due to its advantages of high strength, light weight, corrosion resistance and low creep. To achieve long-term and reliable application of carbon fiber-reinforced polymer (CFRP) tendon anchorage in civil engineering-such as the cables in cable-stayed bridges, suspenders of arch bridges, and others- long-term performance experiments of eight CFRP tendon composite anchorage specimens with pure epoxy resin and epoxy resin incorporating basalt fiber or talc powder as bonding media were conducted for at least 1 000 h. The effects of different admixtures on the long-term performance of the anchorage were investigated, and the residual anchoring performance after the long-term performance experiments was tested. Results reveal that the bonding state of the tendons and bonding medium of the eight tested specimens remain intact after long-term performance experiments, thus indicating that the novel composite anchorage has excellent long-term performance. Compared with the specimen with pure epoxy resin, the slippages of single-tendon specimens with 0.5 % basalt fiber or talc decreased by 37% and 29.5%, respectively, and their residual load increased by 11% and 6.8%, respectively. When the content was 1%, the corresponding values were almost unchanged, thus indicating that adding an appropriate amount of basalt fiber or talc to the epoxy resin can effectively improve the long-term performance of the composite anchorage. In addition, because the specimen with talc powder can only reduce the creep deformation of the bonding medium and cannot improve the bonding performance between the bonding medium and the CFRP tendon, the improvement effect is not as obvious as that of the basalt fiber. After the long-term performance experiments, the failure mode of the eight specimens in the static load test was attributed to tendon fracture, and the residual anchorage efficiency was greater than 95%, indicating that the novel composite anchorage can still effectively anchor the CFRP tendons after long-term performance experiments (lasting 1 000 h) and can work safely and effectively for a long time, thus demonstrating its capability for use in practical engineering.

The reinforcement effect of prestressed anchor cables with small diameter on the surrounding rock of soft rock tunnels was systematically investigated. First, the bearing arch effects of the surrounding rock of a tunnel strengthened using small-diameter prestressed anchor cables were simulated and analyzed based on a stratum-structure model. A generalized “load-structure” mechanical analysis model of the anchored surrounding rock was established. A formula for calculating the bearing capacity of the anchored surrounding rock with the combined support of long and short anchor cables was derived. Subsequently, numerical analysis of the simulated loading of the anchored surrounding rock was performed. The development process of a plastic zone in the anchored surrounding rock and the main factors influencing the ultimate bearing capacity were studied. The effectiveness of anchor cable support schemes was also explored. Finally, the reinforcement effect of small- diameter prestressed anchor cables on the surrounding rock of a soft rock tunnel was verified and summarized through on-site testing. The results indicate that a superimposed arch composed of a shallow and a deep bearing arch is formed in the surrounding rock under the combined support of long and short anchor cables. In this case, the diffusion range of the pre-tensioning force is higher than that obtained with the short anchor cable scheme, and the engineering economy can be considered comparable to that of the long anchor cable scheme. After the anchored surrounding rock is loaded, its inner surface first enters a plastic state. Considering the corresponding load when the inner surface enters the plastic state as the bearing capacity of the anchored surrounding rock tends to be conservative. The ultimate bearing capacity of the anchored surrounding rock can be obtained using numerical calculation methods, which mainly depend on the strength of the surrounding rock and the anchoring force of the anchor cable. The active support obtained with small- diameter anchor cables and high pre-tension can significantly increase the overall stiffness of the anchored surrounding rock. Under the conditions of relatively soft rock and soft rock strata, small- diameter (Φ21.8) prestressed combined long-short anchor cables (5 m+10 m, 19 per ring of upper and middle benches, spacing of 80 cm, design anchoring force of 450 kN, design pre-tensioning force of 350 kN) were used, and the maximum deformation of the tunnel was basically controlled within 30 cm according to actual measurements. For extremely soft rock formations, ensuring that small-diameter anchor cables have a sufficient anchoring force is a key technical problem that must be solved urgently.

Mountain tunnels often pass through poor strata such as high-ground stress soft rock and fault fracture zones. Because of the poor stability and high pressure of the rock surrounding the tunnel, the initial support is prone to structural damage, such as shotcrete cracking, spalling, and steel arch distortion, whereby the support structure loses its bearing capacity and causes disasters such as tunnel collapse. To improve the synergistic bearing capacity between the steel arch and shotcrete in tunnel support, a composite structure support is proposed by arranging stud shear connectors at the contact interface. Considering the stress characteristics of the tunnel support, a test was conducted on the large eccentric compression members. The failure mode and bearing characteristics of the composite structure support were analyzed, and an expression of the ultimate bearing capacity of the tunnel steel-sprayed concrete composite structure was established through theoretical calculations. The results show that the failure mode of the contact interface is determined by the separation and spalling between steel and concrete, which is consistent with the large-deformation failure mode of the actual tunnel support. When stud shears are arranged on the steel web, the failure mode is only cracking and crushing, which significantly improves the anti-slip and synergistic bearing capacity. A steel-concrete composite structure with stud shear connectors exhibits good ductility, bearing capacity, and bending stiffness. Compared with the natural bonding condition, the ultimate bearing capacity increased by 14.83%, and the lateral deflection decreased by 24.27%. Under natural bonding conditions, the section of the steel-concrete structure can no longer meet the plane section assumption when the large eccentric loading is greater than 0.4 times the ultimate load; however, it can still meet the plane section assumption when the stud shear is loaded to 0.8 times the ultimate load under web layout condition. Concurrently, a theoretical calculation formula was established for the ultimate bearing capacity of large eccentric compression of steel-concrete supporting structures with studs and further verified. These results provide theoretical support for the design of tunnel primary support.

To systematically analyze and summarize the current research status and development trends in the operational management of emergency medical service (EMS) vehicles, this study organizes the research framework of EMS vehicle operational management into three levels: strategic, tactical, and operational, based on 1 502 articles indexed from the Web of Science database. The findings reveal that at the strategic level, research on EMS vehicle location focuses on continuous improvement of coverage definition and accurate characterization of inherent uncertainties within the system. Key research methods include stochastic planning and robust optimization as uncertainty modeling and optimization approaches. At the tactical level, EMS vehicle relocation is categorized into multiperiod and dynamic relocation based on the triggering of relocation decisions. Given the complexity of relocation with respect to location, the research emphasizes the application of heuristic and reinforcement learning algorithms in addressing real-world large-scale problems. Decisive issues at the operational level include EMS vehicle dispatch, destination selection, and route planning. Research on EMS vehicle dispatch has evolved from rule-to model-based and from independent to joint optimization in relocation. Destination selection involves coordinated optimization with hospital workload, and route planning primarily addresses special scenarios such as disaster response. In future research, optimization in EMS vehicle operational management should focus on the dual research threads of dynamics and uncertainty. This entails accurately characterizing the sources of system uncertainty while leveraging finer-grained data to assist real-time decision-making. In terms of specific modeling and solving techniques, joint optimization of multiple decision problems across different levels should be conducted to progress from local to system optimum EMS vehicle location and dispatch schemes. However, efficient algorithms for handling real-world large-scale scenarios continue to pose a challenging research direction.

Urban expressways, as essential transportation corridors, present unique challenges for traffic management, especially in merging zones. This study proposes a lane change decision-making model for connected and automated vehicles (CAVs) designed to optimize their operation in these complex environments. Specifically, the model addresses the unique lane change dynamics in urban expressway merging zones, focusing on safety, efficiency, and comfort. The analysis begins with a spatiotemporal overlap evaluation between lane-changing vehicles and adjacent traffic, providing the basis for identifying potential collision risks. For CAVs and neighboring vehicles exhibiting spatiotemporal overlap, the lane change time to collision (LCTTC) is computed, enabling dynamic risk assessment. The resulting risk metrics are integrated into a multi-objective reward function to optimize the deep q-network (DQN) architecture, which balances vehicle safety, operational efficiency, and passenger comfort. A novel, risk-aware lane change strategy, termed the security improvement deep q-network (SIDQN), is then proposed. Simulation experiments validate the effectiveness of this strategy, with results demonstrating a lane change success rate exceeding 95% and an average speed of no less than 21.008 m·s^-1. Moreover, the SIDQN strategy improves safety performance in complex merging scenarios, reducing the LCTTC ratio to just 9.56%, a substantial decrease compared to baseline strategies. The accident rate remains minimal. Additionally, the SIDQN strategy limits the number of lane changes to four and minimizes ineffective consecutive lane changes, reducing extreme acceleration and deceleration events and thereby enhancing passenger comfort. In conclusion, the proposed lane change decision-making model significantly improves performance in urban expressway merging zones and provides a valuable reference for advancing CAV safety and comfort in intelligent, connected environments.

Traffic state completion methods can provide comprehensive holographic traffic network information for traffic management systems, supporting the formulation of urban signal control strategies and dynamic balancing of traffic flow. Leveraging the advantages of real-time acquisition of multi-source traffic data through intelligent and connected technologies, this paper proposes a real-time traffic state completion method based on graph convolutional neural networks. First, a holographic traffic perception system with an “end-edge-cloud” information interaction architecture was constructed, enabling feature-level fusion of multi-source traffic data. Second, an undirected graph model of the road network was built based on the road network topology. Anomaly data identification and interpolation methods were applied to correct the raw data, forming an effective dataset. The hidden layer weights of the completion network were determined according to the spatiotemporal relationships of the actual road network. Third, the spatial features of intersections were clustered by mapping the original data to the spatial dimension through the graph convolutional approach, which incorporates adjacency relationships and the traffic states of intersections. The gate recurrent unit (GRU) was used to traverse the data along the time series, extracting temporal features for state data completion calculations. Finally, field tests were conducted at typical intelligent and connected intersections in the Beijing High-level Automated Driving Demonstration Area. The test results show that for long-term sequence data, the method achieved an error of no more than 10.64% compared to the real values. The overall performance, as measured by the reduction in root mean-squared error (RMSE), was 17.2% lower than that of existing methods such as the long short-term memory (LSTM) neural network. This completion method provides a theoretical foundation and implementation solution for the application of traffic holographic perception technology in future intelligent and connected environments.

The new quality of productive forces is a contemporary advanced force that is fostered by revolutionary breakthroughs in technology, innovative allocation of production factors, and deep transformation and upgrading of industries. Transportation industry development focuses on the quantity of expansion. Development of quality and efficiency is not high if the traditional path of development constrains the socio-economic development needs and eliminates the original development path which is key in the mental productivity of empowerment. Therefore, this paper proposes the connotation and characteristics of the new quality of productive forces in transportation from the perspective of the development of transportation and transportation productive forces, thereby constructing an evaluation index system for the level of new quality of productive forces in transportation, which better serves economic and social development as a measurement standard. Taking the port in the field of transportation as a case study, the study evaluates and measures the new quality of productive forces in port enterprises using the analytic hierarchy process (AHP) and the entropy weight method. Based on theoretical and empirical research and analysis, the transportation industry is believed to be in a key period of innovative development in the digital economy era. The development of transportation should fully leverage the new quality of productive forces to achieve high-quality development. The improvement of the level of new quality of productive forces in transportation should be promoted from three aspects: labor force, means of labor, and objects of labor, to strengthen the coupling of the system. Empowering digital elements, optimizing the allocation of all factors, enhancing the resilience of the transportation system, carrying out full-process transportation services, building a green and low-carbon transportation system, and strengthening the safety protection capabilities of transportation should be systematically and comprehensively promoted.

Recently, autonomous vehicles (AVs) have gradually reached the stage of real-world testing and demonstration on public roads. AVs interact frequently with humans, and their driving performance requirements have shifted from a functional level of “safe and stable driving” to an interactive level of “driving like a human.” The construction of evaluation indices and methods that can accurately characterize the human cognition of driving behavioral ability is necessary to guide the continuous development and improvement of automated driving technology to demonstrate human-like or superhuman driving ability. This study focused on the construction of an evaluation indicator system for the driving behavioral ability of autonomous vehicles. This paper first elaborates on the definition and boundaries of the driving behavioral ability of autonomous vehicles. Then, the current status and existing problems of the evaluation index system for driving behavioral ability are presented. Moreover, an STCER-H index system is proposed, which includes five dimensions of instantaneous indicators: Driving Safety, Travel Efficiency, Driving Comfort, Energy Efficiency, and Regulatory Compliance, as well as a comprehensive “Humanoid Level of Driving Behavior” indicator. Consequently, the existing modeling methods for individual indicators are reviewed, the connotations of each dimension indicator are clarified, and the current status and problems of each dimension indicator are summarized. At the level of statistical evaluation in multidimensional aggregation, the definition and modeling suggestions of “Humanoid Level of Driving Behavior” indicator are primarily discussed. Finally, a summary of the challenges and future research prospects of the existing evaluation index system for driving behavioral ability is presented to provide a reference for academic and industry research.

Driver state monitoring technology, as a key means for improving vehicle intelligence and safety, aims to accurately identify and deeply understand the driver's actions, emotions, and attention states. Although significant progress has been made in this field, a systematic summary of the principles of deep learning algorithms is lacking. In view of this, this paper systematically reviews driver state monitoring algorithms based on images and deep learning to meet the needs of the continuous development of intelligent vehicle technology. First, the methodology in the literature is elaborated upon. The existing publicly available datasets are then organized and described. Subsequently, in-depth exploration is conducted from the aspects of data selection and processing, model architecture, model training and evaluation, and optimization. Finally, the shortcomings of the current research are summarized, and the main future development directions are outlined. The results show that: ① the research on driver state monitoring based on image and deep learning has progressed to a certain depth; ② data selection and processing techniques show diversity; ③ model architectures continue to evolve in the direction of multi-modal, multitasking, lightweight, and high robustness, gradually beginning to adopt training strategies for incomplete supervision and multi-objective optimization. However, most research methods lack systematic testing of actual driving scenarios neither fully considering the behavioral characteristics of drivers under natural driving conditions nor the changes in the human-computer interaction patterns of intelligent vehicles, making it difficult to construct an all-around monitoring function for various driving scenarios and driver personalities. The further development of driver state monitoring algorithms is mainly limited by two factors. First, the current deep learning methods still have deficiencies in their domain adaptation, interpretability, and operational efficiency. Second, large-scale high-quality datasets under natural driving environments are lacking. This review is dedicated to providing effective guidance and important references for further development of high cognitive driver state monitoring systems.

The development of autonomous vehicle platoons will lead to new accident patterns. Insufficient research exists on occupant injury and protection associated with this new type of accident. To provide a reference for the research and technological development of occupant protection in autonomous vehicle platoon collisions, a continuous crash accident scenario involving a typical three-car autonomous vehicle platoon under high-speed conditions was utilized to determine boundary conditions such as impact time and speed. A full-scale finite element simulation was conducted to obtain the driver kinematics and injury response in each collision condition, and driver injury risk in the autonomous vehicle platoon collision scenarios was analyzed. The results show that although the risk of skull fracture is less than 1%, the risk of severe craniocerebral injury is significant, with the highest predicted risk of AIS 3+ using the BrIC criterion reaching 70.2%. Owing to excessive forward bending and backward extension of the cervical spine, three types of ligaments are at risk of serious injury. Furthermore, the risk of chest rib fracture is relatively low, whereas the risk of viscera damage is contingent on the collision sequence. When the middle car first experiences a frontal collision and is then rear-ended, the maximum principal strain on the driver's heart and liver far exceeds the damage threshold of 0.3, resulting in significant damage risk. Conversely, when the middle car is rear-ended and then collides with the front car, the maximum principal strain on the driver's internal organs is less than 0.3, resulting in a low overall damage risk.