Search Results (51)

This study addresses the water basin effect in the underwater sand layer of steel pipe pile cofferdams by integrating the concept from building foundation pits to cofferdam foundation pit analysis. A theoretical derivation is presented for the deformation evolution of steel pipe piles and bottom seals within the cofferdam pit. The cofferdam construction dewatering process is divided into four stages: riverbed excavation for bottom sealing, dewatering to the second support, dewatering to the third support, and dewatering to final bottom sealing. The steel pipe piles are modeled as single-span or multi-span cantilever continuous beam structures. Using the superposition principle, deformation evolution equations for these statically indeterminate structures across the four stages are derived. The bottom seal is simplified to a single-span end-fixed beam, and its deflection curve equation under uniform load and end-fixed additional load is obtained via the same principle. A case study based on the 6# pier steel pipe pile cofferdam of Xi’an Metro Line 10 Jingwei Bridge rail-road project employs FLAC3D for hydrological–mechanical coupling analysis of the entire dewatering process to validate the water basin effect. Results reveal a unique water basin effect in cofferdam foundation pits. Consistent horizontal deformation patterns of steel pipe piles occur across all working conditions, with maximum horizontal displacement (20.72 mm) observed at 14 m below the pile top during main pier construction completion. Close agreements are found among theoretical, numerical, and monitored deformation results for both steel pipe piles and bottom seals. Proper utilization of the formed water basin effect can effectively enhance cofferdam stability. These findings offer insights for similar engineering applications. Full article

Rainfall can easily cause local sliding and collapse of carbonaceous mudstone deep road cut slopes. In order to study the strength characteristics of carbonaceous mudstone under different water environments, large-scale horizontal push shear tests were conducted on carbonaceous mudstone rock masses in their natural state and after immersion in saturated water. The push shear force–displacement relationship curve and fracture surface shape characteristics of carbonaceous mudstone samples were analyzed, and the shear strength index of carbonaceous mudstone was obtained, and numerical simulations on the stability and support effect of carbonaceous mudstone slopes were conducted. The research results indicate that carbonaceous mudstone can exhibit good structural properties and typical strain softening characteristics under natural conditions. The fracture surface, shear strength, and shear deformation process of carbonaceous mudstone samples will undergo significant changes after being soaked in saturated water. The average cohesion decreases by 33% compared to the natural state, and the internal friction angle decreases by 15%. The numerical simulation results also fully verify the attenuation of mechanical properties of carbonaceous mudstone after immersion, as well as the effectiveness of prestressed anchor cables and frame beams in supporting carbonaceous mudstone slopes. The research results provide an effective method for understanding the shear performance of carbonaceous mudstone and practical guidance for evaluating the stability and reinforcement design of carbonaceous mudstone slopes. Full article

Horizontal curves have been a significant safety concern on roads for years, often resulting in a high incidence of crashes. A European Road Safety Observatory report indicated that 53% of road crashes in the EU in 2020 occurred on rural roads, mainly due to misjudging when navigating these curves. This study explores innovative low-cost road designs for this issue, such as the red-white pattern edge line (RWE), the solid red edge line (RE), the alternating red-white checkered median stripe (RWM), and the red dragon’s teeth (RDT) to improve driver behavior around curves. The various road markings were tested based on speed, acceleration/deceleration, and lateral position before and during horizontal curves in a driving simulator using STISIM Drive^® 3. Fifty-two volunteers, aged between 20 and 75, participated in the study. The simulation road was designed according to the Flemish Road Agency (AWV) guidelines. The simulation tested twelve horizontal curves, including left and right turns, with 125 m and 350 m radii. The results were analyzed using within-subjects repeated measures ANOVA, with Greenhouse–Geisser correction for sphericity violations. It was revealed that these markings can reduce driving speeds and improve control, enhancing road safety. Specifically, the red-white median stripe resulted in better lateral positioning. At the same time, red dragon’s teeth minimized deceleration before curves, although their effects were less significant for curves with larger radii. Full article

Road horizontal curves, which significantly influence drivers’ visual search behavior and are closely linked to traffic safety, also constitute a crucial factor in sustainable road traffic development. This paper uses simulation driving experiments to explore the dynamic response characteristics of 27 typical subject drivers’ visual search behavior regarding road horizontal curve radius. Results show that in a monotonous, open road environment, the driver’s visual search is biased towards the inside of the curve; as the radius increases, the 85th percentile value of the longitudinal visual search length gradually increases, the 85th percentile value of the horizontal search angle gradually decreases, the 85th percentile value of vehicle speed gradually increases, and the dispersion and bias of the gaze points gradually decrease. The search length, horizontal angle, and speed approach the level of straight road sections (380 m, 10° and 115 km/h, respectively). When R ≥ 1200 m, a driver’s dynamic visual search range reaches a stable distribution state that is the same as that of a straight road. A dynamic visual search range distribution model for drivers on straight and horizontal curved road sections is constructed. Based on psychological knowledge such as attention resource theory and eye–mind theory, a human factor engineering explanation was provided for drivers’ attention distribution and speed selection mechanism on road horizontal curve sections. The research results can provide theoretical references for the optimization design of road traffic, decision support to improve the driver training system, and a theoretical basis for determining the visual search characteristics of human drivers in autonomous driving technology, thereby promoting the safe and sustainable development of road traffic. Full article

Mechanical construction has gradually been applied in cross passages of metro lines, but more mechanical mechanisms should be revealed. The section between Jingrong Street Station and Kunjia Road Station in Suzhou Metro Line 11 adopts a mechanical construction method to construct a cross passage. A novel flat-face cutterhead, which is different from curved cutter head is first used to cut and break the main tunnel in construction of cross passage. Based on the background of practical engineering, the finite element method was applied to simulate the breaking process of the main tunnel to explore the dynamic variation in the mechanical response of the segments cut by the flat-face cutterhead. The results indicate that the maximum vertical displacement caused by cutting mainly concentrates on the top of the fully cut rings. The maximum horizontal displacement occurs at the waist on the side of the tunnel portal in the semi-cut rings. The axial force level inside both types of segment rings reaches its peak after the tunnel is formed. The maximum axial force exists at the bottom and top of the fully cut ring and semi-cut ring, respectively. The change in the displacement around the portal is not substantial before the third stage, and it begins to increase significantly from the moment the concrete at the portal is penetrated. The existence of the pre-support system effectively controls the displacement of the third and fourth fully cut rings. Emphasis should be placed on reinforcing the soil near the top and waist of the second to fifth rings. The findings demonstrate that the application of flat-face cutterhead in mechanical construction of cross passages is safe, reliable, and efficient, and can provide valuable suggestions for further cutting parameters and soil reinforcement as well. Full article

With the increasing demand for autonomous driving, ensuring safe and efficient lane-changing behavior in multi-lane traffic scenarios has become a key challenge. This paper proposes an algorithm for active lane-changing decision-making and trajectory planning designed for intelligent vehicles in such environments. The lane-changing intent is evaluated using fuzzy logic, followed by an assessment of lane-changing feasibility based on a lane utility evaluation function. A hierarchical model for path and speed planning is established. Path clusters are generated using quintic polynomials. With a multi-objective cost function designed to ensure collision safety, smoothness, road boundaries, and trajectory continuity, dynamic programming (DP) and quadratic programming (QP) are employed to obtain the trajectory with the minimum cost among the trajectory set fitted by fifth-order polynomials, which is the optimal lane-changing trajectory. For speed planning, obstacles are projected onto the S–T coordinate system, which is a coordinate system with time as the horizontal axis and the distance(s) of the planned path as the vertical axis, and multi-objective cost functions for speed, acceleration, and speed continuity are designed. The speed curve is optimized using DP followed by QP under given constraints. Simulation results show that the proposed algorithm makes safe and effective lane-changing decisions based on traffic conditions, vehicle distances, and speeds. The model generates smooth and stable paths while ensuring the safe and efficient execution of lane changes. This process meets real-time requirements and verifies the reliability of the algorithm. Full article

Truck skidding crashes on horizontal curves pose a significant road safety concern, with improper braking being the primary cause. A data- and model-integrated driven method is proposed to investigate the mechanism and recommend the maximum safe braking deceleration rates without skidding (abbreviated as MSBDRs) for trucks on horizontal curves. Firstly, a comprehensive road–vehicle interaction model was developed, considering dynamic changes in brake force distribution, vertical tire load, and longitudinal and side friction during braking. Secondly, leveraging the “HighD” data set and employing cluster analysis principles, parameter data were extracted using Python and Matlab. Finally, through parameterizing model inputs, the transient dynamic response of trucks was examined, the potential of truck skidding was predicted, and the MSBDRs were recommended. The results indicate the following. (1) There is little concern of truck skidding during car-following braking maneuvers; however, there is a high potential of truck skidding during emergency braking maneuvers. (2) The MSBDR is 4.5 m/s² on a limit-minimum-radius horizontal curve; however, when combined with steep slopes, an overspeed exceeding 20%, and extremely wet road conditions, respectively, the MSBDRs decrease to 4 m/s², 3 m/s², and 2 m/s². These results provide a theoretical foundation for braking strategies in autonomous vehicles. Full article

Due to the transition of vehicle fleets from conventional driver-operated vehicles (DVs) to connected vehicles (CVs) and/or automated vehicles (AVs), vehicles with different technologies will soon operate on the same roads in a mixed-vehicle environment. Although a major goal of vehicle connectivity and automation is to improve traffic safety, negative safety impacts may persist in the mixed-vehicle environment. Speed disparity measures have been shown in the literature to be related to safety performance. Therefore, speed disparity measures are derived from the expected speed distributions of different vehicle technologies and are used as surrogate measures to assess the safety of mixed-vehicle environments and identify the efficacy of prospective countermeasures. This paper builds on speed models in the literature to predict the speed behavior of CVs, AVs, and DVs on horizontal curves on freeways and major arterials. The paper first proposes a methodology to determine speed disparity measures on horizontal curves without any control in terms of speed limit. The impact of speed limit or advisory speed, as a safety countermeasure, is modeled and assessed using different strategies to set the speed limit. The results indicated that the standard deviation of the speeds of all vehicles (${\sigma }_c$) in a mixed environment would increase on arterial roads under no control compared to the case of DV-only traffic. This speed disparity can be reduced using an advisory speed as a safety countermeasure to decrease the adverse safety impacts in this environment. Moreover, it was shown that compared to the practice of a constant speed limit based on road classification, the advisory speed is more effective when it is based on the speed behavior of various vehicle types. Full article

Due to poor road design, challenging terrain, and difficult geological conditions, traffic accidents on mountainous two-lane roads are more frequent and severe. This study aims to address the lack of understanding of key factors affecting accident severity with the goal of improving mountainous traffic safety, thereby contributing to sustainable transportation systems. The focus of this study is to compare the interpretability of model performances with three statistical models (Ordered Logit, Partial Proportional Odds Model, and Multinomial Logit) and six machine learning models (Decision Tree, Random Forest, Gradient Boosting, Extra Trees, AdaBoost, and XGBoost) on two-lane mountain roads in Yunnan Province, China. Additionally, we assessed the ability of these models to uncover underlying causal relationships, particularly how accident causes affect severity. Using the SHapley Additive exPlanations (SHAP) method, we interpreted the influence of risk factors in the machine learning models. Our findings indicate that machine learning models, especially XGBoost, outperform statistical models in predicting accident severity. The results highlight that accident patterns are the most significant determinants of severity, followed by road-related factors and the type of colliding vehicles. Environmental factors like weather, however, have minimal impact. Notably, vehicle falling, head-on collisions, and longitudinal slope sections are linked to more severe accidents, while minor accidents are more frequent on horizontal curve sections and areas that combine curves and slopes. These insights can help traffic management agencies develop targeted measures to reduce accident rates and enhance road safety, which is critical for promoting sustainable transportation in mountainous regions. Full article

As one of the early manifestations of road pavement structure degradation, road cracks will accelerate the deterioration of the road if not detected and repaired in time. Aiming at the problems of low recall and incomplete crack detection in current road detection, based on the U-Net network, this paper proposed an Attention-Dynamic Snake Convolution U-Net (ADSC-U-Net) network. Firstly, the dynamic snake-shaped convolution was added to the normal downsampling process to make the network adaptively focus on the slender and curved local features, which can solve the problem of low accuracy of small crack detection. Secondly, the attention mechanism was used to pay better attention to the significant features of positive samples under the condition of a large proportion gap between positive and negative samples, which solved the problem of the poor crack integrity detection effect. Finally, the dataset was expanded by random vertical and horizontal flip operations, which solved the problem of network training overfitting caused by the small-scale datasets. The experimental results showed that, when the input image had a resolution of 480 × 320, evaluation indices P, R, and F1 of ADSC-U-Net on the self-built dataset were 74.44%, 68.77%, and 69.42%, respectively. Compared to SegNet, DeepLab, and DeepCrack, the P was improved by 1.90%, 2.49%, and 11.64%, respectively; the R was improved by 8.01%, 4.70%, and 59.58%, respectively; and the comprehensive evaluation index F1 was improved by 5.73%, 4.02%, and 55.87%, respectively, which proves the effectiveness of the proposed method. Full article

The carbon emitted by vehicles traveling on curved roads is greatly affected by the alignment of the route, yet the mechanism behind this is not yet clear, leading to current horizontal alignment designs being unable to avoid this problem. To clarify the principles and indicator thresholds of low-carbon design for planar geometry, this study takes the carbon emission of traveling on curved routes as the research object, and establishes a relationship model between carbon emissions and design indicators based on the principles of vehicle dynamics and kinematics. Field tests were conducted to validate the quantitative relationship model. The model shows that both radius and superelevation are negatively correlated with carbon emissions, while the lateral force coefficient is positively correlated with carbon emissions. The contribution of radius to carbon emissions is greater than that of superelevation. This study clarifies the recommended values of low-carbon design indicators by assessing carbon emissions according to the current route design specification, outlines the principles of superelevation settings, and proposes a methodology to deal with the relationship between superelevation and the lateral friction coefficient. The research findings promote the quantification and standardization of low-carbon highway design, contributing to the early mitigation of high-carbon emissions from curved traffic during the design phase. Full article

The combination of horizontal curves and gradients can lead to visual perception errors by drivers, resulting in risky operations. While plant landscapes serve to guide road alignment and alleviate driver stress, irrational plant landscapes can obstruct the driver’s view, leading to traffic accidents. This study aims to explore the optimal configuration of plant landscapes on horizontal–vertical curve sections. The standard deviation of speed and lateral displacement were selected as two important measures of vehicle stability, and four crucial factors of plant landscapes were identified: color, height, roadside distance, and plant spacing. Subsequently, Design Expert 10, UC-win/Road 16.0 software, and a driving simulator were employed for scene design, modeling, and driving data acquisition. The Box–Behnken Design response surface method was utilized to analyze the influence of plant landscape factors on vehicle stability and predict the optimal configuration of plant landscapes on horizontal–vertical curve sections. Finally, validation experiments were conducted. The results indicate that the height and spacing of plants significantly affect vehicle speed, while plant height and roadside distance significantly impact vehicle lateral displacement. Through validation experiments, it was confirmed that the optimal plant landscape configuration is green in color, with a height of 4 m, a roadside distance of 1 m, and a plant spacing of 10 m. Therefore, rational plant landscapes can enhance driving stability and are essential measures for improving traffic efficiency and safety. Full article

Rural landscapes serve as important platforms to determine the landscape characteristics (LCs) of rural areas, demonstrating the landscape characteristics specific to certain regions to the public. However, the development trend of urban and rural areas is continuous and impacts the characteristics of rural landscapes, which directly affects the public’s visual experience and landscape perception. In order to improve the characteristics of rural landscapes, this study evaluates and analyzes their visual quality based on public preferences and eye movement heat maps. The results show that most subjects have a high preference for horizontal, open-view rural landscapes with fields and landform features as the dominant landscape elements. This study also found that the combination of strip-like or planar settlement buildings with regional characteristics and landform features has an active impact on the visual quality of rural landscapes. These results show that rural landscapes characterized by scattered settlement buildings without significant regional characteristics, horizontally curved roads, bridges, and other human-made landscape elements, and mixed and disorderly vegetation have low landscape preference, which degrades their visual quality. These research results provide crucial suggestions for landscape managers to protect and renew rural landscape features. Full article

The advent of autonomous vehicles (AVs) in the traffic stream is expected to innovatively prevent crashes resulting from human errors in manually driven vehicles (MVs). However, substantial safety benefits due to AVs are not achievable quickly because the mixed-traffic conditions in which AVs and MVs coexist in the current road infrastructure will continue for a considerably long period of time. The purpose of this study is to develop a methodology to evaluate the driving safety of mixed car-following situations between AVs and MVs on freeways based on a multi-agent driving-simulation (MADS) technique. Evaluation results were used to answer the question ‘What road condition would make the mixed car-following situations hazardous?’ Three safety indicators, including the acceleration noise, the standard deviation of the lane position, and the headway, were used to characterize the maneuvering behavior of the mixed car-following pairs in terms of driving safety. It was found that the inter-vehicle safety of mixed pairs was poor when they drove on a road section with a horizontal curve length of 1000 m and downhill slope of 1% or 3%. A set of road sections were identified, using the proposed evaluation method, as hazardous conditions for mixed car-following pairs consisting of AVs and MVs. The outcome of this study will be useful for supporting the establishment of safer road environments and developing novel V2X-based trafficsafetyinformation content that enables the enhancement of mixed-traffic safety. Full article

One technique employed to enhance road safety involves assessing the alignment’s consistency. A prevalent measure of consistency is evaluating speed variations along the alignment. A key consideration in this assessment is determining the speed upon which the road alignment should be based. This research reveals that on two-lane rural highways with low tortuosity alignments, operating speeds on horizontal curves and tangents consistently exceeded not only the design speeds but also the maximum permissible design speed for the road category. Consequently, using the design speed to assess consistency on these roads is deemed impractical, and utilizing operating speed poses challenges due to speeds exceeding the maximum permissible limit. The objectives of this paper are twofold: to explore the relationship between design consistency and safety levels on two-lane rural highways with low tortuosity alignments (which have been insufficiently covered in research) and to propose speed-control measures to limit the maximum operating speed to the maximum permissible speed. The study findings suggest that on roads with a low tortuosity alignment, operating speeds depend much more on the general characteristics of the alignment (evaluated in the operating speed models through the desired speed). Further, assessing speed consistency is feasible only with a rigorous control of the maximum operating speed (desired speed). Additionally, a specific type of speed control is recommended, achieved by limiting the curvature change rate (CCR) of the road section based on the desired speed (environmental speed), whose evaluation becomes a crucial factor. Full article