Pavement overlay on operating expressways can reduce the effective height of existing roadside W-beam guardrails and thereby compromise their crashworthiness. Prior research demonstrated that guardrails have had challenges meeting impact safety standards when pavement thickening. Focusing on a representative post-overlay condition in which the effective guardrail height is reduced to 600 mm, this study investigates the likely failure mechanism of the original guardrail and develops a retrofit structure to restore its protective performance. Finite element (FE) simulations indicate that, under the representative post-overlay condition, the existing guardrail is prone to unstable vehicle redirection and truck rollover, with inadequate blocking and guiding capability. To address this problem, a novel dual-row W-beam guardrail (DRG) retrofit concept is proposed. Two key design variables, namely the beam thickness and the spacing between the two beam rows, were optimized using an FNN-based surrogate model combined with NSGA-II. The optimization objectives were the maximum elevation of the vehicle gravity center, the maximum vehicle tilt angle, and the maximum dynamic lateral displacement of the guardrail. The optimized DRG was then evaluated through FE simulation and correlated with full-scale crash test results. Compared with the original post-overlay guardrail, the optimized DRG reduced rollover-related vehicle responses and improved overall crash-response performance. The full-scale test results showed good agreement with the FE predictions, supporting the feasibility of the proposed retrofit system under the representative test conditions.

Reflective cracking in semi-rigid base asphalt pavements remains a persistent challenge, particularly when moisture accumulates within confined base-layer cracks and conventional surface treatments fail to provide durable structural rehabilitation. To address this problem, this study developed a low-viscosity, micro-expanding, moisture-tolerant polyurethane grout for non-destructive crack repair. An amino-modified 3 A aluminosilicate molecular sieve was incorporated to scavenge free water and suppress undesirable side reactions of isocyanate groups, thereby improving foaming stability and crack-filling effectiveness under wet conditions. A Taguchi orthogonal design combined with analysis of variance was employed to optimize the key formulation parameters using pull-off adhesion strength and elongation at break as the evaluation indices. The optimized grout was evaluated through tensile and pull-off adhesion tests, composite pull-off and direct shear tests, and Fourier transform infrared spectrometer (FTIR) characterization. The results indicate that the developed grout exhibits favorable penetrability, strong interfacial bonding, and adequate load-transfer capacity, supporting both crack sealing and local structural rehabilitation. Field grouting tests further verified the material performance, and ground-penetrating radar images confirmed effective grout diffusion and crack filling in the repair zone. The proposed material and validation framework provides a practical and engineering-oriented solution for rehabilitating reflective cracks in semi-rigid base asphalt pavements.

OBJECTIVE:In road sign design, inappropriate layout can easily lead to excessive cognitive load on drivers. This hinders their ability to effectively allocate attention, resulting in missed critical road information and increased accident risks. Through empirical studies on drivers' visual recognition characteristics and cognitive load, this study investigates the rationality of information volume settings in urban road guide signs. METHODS:It employed a combination of simulation experiments and real vehicle tests. An information volume calculation model for guide signs was established. The visual recognition simulation experiment was designed to collect data. Real vehicle experiment was conducted to dynamically record drivers' physiological indicators. A cognitive load assessment model was developed to explore the reasonable range of information density for sequentially signs. RESULTS:From the perspective of ensuring reasonable visual recognition accuracy, the information volume of a single guide sign should be less than 90 bit on arterial roads and below 95 bit on secondary distributor roads. Real vehicle test results indicate that when the information density is below 9.1 bit/s, drivers experience relatively low cognitive load. When the information density exceeds 10.7 bit/s, cognitive load increases significantly. To ensure driving comfort and safety, the information density of signs should not exceed 12.0 bit/s. CONCLUSION:The information volume on guide sign should be maintained within a reasonable range. The information density of successive signs significantly influences drivers' cognitive load levels. These findings provide theoretical guidance and practical recommendations for optimizing the information design of urban guide signs and enhancing traffic safety.

OBJECTIVE:To improve the traffic risk conditions of mountainous expressway tunnel sections, it is necessary to conduct safety risk assessments and adopt different countermeasures according to the assessed risk levels. METHODS:An evaluation system was established with 4 primary indicators-tunnel condition, traffic characteristics, operational environment, and safety facilities-and 16 secondary indicators. Safety status was divided into 5 risk levels. To assign indicator weights objectively, information entropy was used to improve the traditional CRITIC method. Two assessment models based on extension matter-element theory and set pair analysis were then developed to form a dual-verification mechanism: the former handles indicator-grade incompatibility via correlation functions, while the latter treats assessment uncertainty using multiple connection numbers. RESULTS:Fifteen tunnels on the Guangzhou-Kunming Expressway in Yunnan Province were selected as evaluation objects. The improved CRITIC method effectively reduced subjective bias, with key indicator weights adjusted by up to 10% for more objective weighting. The extension matter-element model and set pair analysis (SPA) model yielded highly consistent dual assessment results (agreement rate >80%). Most tunnels were classified as low-risk, while several long tunnels were categorized as medium-risk. The SPA model showed greater advantages in describing risk evolution trends, clearly characterizing transitions between adjacent risk levels via potential series. CONCLUSION:The improved CRITIC method significantly enhances the objectivity of indicator weighting, making it more consistent with actual tunnel conditions. The combined application of the extension matter-element model and the set pair analysis model form a complementary dual verification mechanism. Case studies verified that this integrated evaluation system can accurately determine tunnel safety levels and provide a reliable basis for developing targeted risk prevention and control measures.

OBJECTIVES:The environmental landscape of highway tunnel entrance zones is closely related to driving performance. To investigate the impact mechanism of environmental information volume on drivers' visual workload in tunnel entrance zones, this study proposes a novel computational method for quantifying visual information. The aim is to provide a theoretical basis for improving tunnel entrance environments and enhancing driving safety. METHODS:Field experiments on highways collected environmental images, vehicle dynamics, and drivers' speed and psychological data from eight tunnel entrances. Visual field images were divided into five regions based on attention range: upper portal, central portal, left/right roadside, and pavement. HSV values were extracted to describe color and texture features. A model combining optical flow, sight distance, lane width, and speed quantified visual information volume, including traffic signs, and analyzed its relationship with visual workload. RESULTS:The subjective questionnaire results were consistent with the objective computational findings, verifying the reliability of the proposed method. Tunnel entrances with complex landscapes and diverse traffic signs exhibited higher levels of visual information, with drivers' gaze distributed across four areas: both sides of the road, the tunnel entrance center, and the roadway. In contrast, entrances with simpler landscapes and fewer signs had lower visual information levels, and drivers' gaze was mainly concentrated on the roadway and the tunnel entrance center. CONCLUSIONS:The proposed visual information quantification method effectively evaluates the impact of tunnel entrance environmental characteristics on driving visual workload. Appropriately controlling the proportion of traffic sign information (15%-25.55%) helps balance visual workload and comfort, while excessive or insufficient information may lead to discomfort due to underload or overload. These findings provide theoretical guidance and practical recommendations for optimizing tunnel entrance landscape design, traffic sign arrangement, and traffic safety enhancement.

Excessive or insufficient driving load disrupts driving comfort and highway coordination, increasing accident risk. This study examines the relationship between highway alignment and driving comfort, analyzing its effects on drivers' physiological responses and driving load. A naturalistic driving experiment collected eye movement and heart rate data from 28 drivers. Heart rate increase rate and pupil area change rate were selected as driving load indicators, and an entropy weight method was applied to establish a model. Using k-means clustering, driving load thresholds (0.34, 0.64) were determined, classifying comfort levels as "comfortable", "moderately comfortable", and "uncomfortable". Results show that steep slopes, small curve radii, and complex curved-slope sections increase driving load and reduce comfort. Alignment indices exhibit a "threshold effect", where exceeding comfort limits intensifies stress responses and lowers comfort. This study provides theoretical support for mountainous highway reconstruction and management.

OBJECTIVE:This study aims to reveal the spatial distribution characteristics of driving risks in two-lane mountainous highway tunnels, with a particular focus on the influence of different tunnel lengths on risk levels, thereby contributing to improved tunnel operational safety. METHODS:Field driving tests were conducted in 21 short, medium, and long tunnels located on two-lane highways in Chongqing, China. Multisource data were collected from 27 drivers, including heart rate growth rate, speed, illuminance change rate, and alignment complexity indices. The entropy-weighted method was used to determine the weights of various risk evaluation indicators, which were then integrated into the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model to compute the comprehensive risk value for each tunnel. Risk levels were classified into low, relatively high, and high using the K-means clustering algorithm to analyze spatial distribution patterns. RESULTS:The study showed that short tunnels exhibited the highest overall risk level, while long tunnels had the lowest. All three tunnel types displayed a consistent pattern, which is that entrance zones exhibited significantly higher risk than exit zones, with the lowest risk occurring in the middle segments. Specifically: (1) For short tunnels, the peak risk appeared 21 m after the entrance, with high-risk zones extending up to 144 m; (2) For medium tunnels, high-risk spans were concentrated within 50-75 m before and after the entrance, with the exit zone presenting the second-highest risk; (3) For long tunnels, the peak risk was found 2 m after the entrance, and both entrance and exit zones had significantly elevated risk. The average risk value in entrance segments was approximately 1.5 times that of the middle segments. CONCLUSIONS:Driving risks in two-lane highway tunnels exhibit distinct spatial distribution characteristics, with tunnel entrances and exits being the most risk-prone zones. Short tunnels, due to the frequent transition effect, present more pronounced risks. The findings provide theoretical support for tunnel structural design optimization, speed limit, and lighting system.

When carrying out construction on an expressway during operation period, the safety of personnel and equipment in the work zone is critical. There is an urgent need to develop barrier facilities that are suitable for work zone, provide protective capabilities, and have appropriate deformation. A novel barrier system, designated as the movable assembled barrier (MAB), has been introduced, offering the advantage of not necessitating anchoring to the pavement. The upper part consists of steel components, while the lower part is a reinforced concrete base. The barrier's resistance to vehicle impact is derived from the friction force between the base and the pavement. A finite element model, in conjunction with long short-term memory (LSTM) networks and genetic algorithms, was employed to optimize two critical structural parameters of the barrier: the friction coefficient between the barrier and the pavement, and the height of the barrier. This optimization was based on a dataset comprising maximum lift height of the gravity center, roll angle of vehicle and lateral displacement values of the barrier. In accordance with MASH testing requirements, the optimized barrier structure underwent numerical simulations to evaluate its crash performance, with results compared to full-scale crash tests. The research indicates that the MAB structure generates lower ASI values and roll angles during vehicle impacts. Additionally, the lateral displacement values of MAB are minimized, demonstrating good guiding performance for vehicles. Overall, the novel barrier meets the safety standards of MASH TL-4. This innovative barrier structure contributes to ensuring safety in expressway work zone.

During the design process of a new mountainous motorways, multiple route schemes are often proposed for a comprehensive design effort. Each route scheme will have its advantages and disadvantages, so it is often difficult to choose a route scheme. Usually the expert decision method is used to screen the route schemes, but this method mainly relies on the personal experience of experts, and it is difficult to measure the criteria, which can lead to the embarrassing situation that different experts do not agree on the choice of routes.In order to optimize the route scheme for the design process of mountainous motorways and improve the efficiency and scientificity of route scheme selection, evaluation indicators were selected from traffic safety, construction economy, and environmental friendliness. The Entropy Weight Method (EWM) was used to assign the weight of the evaluation indicators. By improving the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), the problem of subjective opinions and excessive reliance on objective data by designers in the multi factor evaluation process was overcome. A EWM-TOPSIS evaluation model was proposed. By analyzing specific examples of mountainous motorway construction, research results were obtained. The results indicate that the model can reflect the designer's intention towards the route scheme and the actual construction project. There is a high degree of consistency with the expert's empirical judgment, which verifies the feasibility and accuracy of the model. This model can provide reliable reference and basis for the decision-making of motorway route schemes in mountainous areas.

The content and density of traffic signs directly affect the operation of urban road traffic and the acceptance of drivers. In order to make up the limitation of quantitative research on density threshold of traffic signs on urban roads, a real vehicle experiment was used to record the drivers’ psychophysiology characteristics. The psychological and physiological indexes of drivers, such as pupil area, fixation intensity, heart rate change rate and heart rate variability, were explored and then principal component analysis was used to present a new index S to represent driving visual comfort level, which was divided into 5 grade scales. The information entropy theory was applied to quantify the amount of information for road traffic signs in driving tests, and a regression relationship between the information content of traffic signs and the comfort index S was established. To meet the requirements of driving comfort, the visual psychophysiological load threshold was -2.289≤S<-1.526 for the level of very comfortable, 1.526≤S<-0.763 for the level of relatively comfortable, -0.763≤S≤0.763 for the level of comfortable, 0.763

Abstract When driving on mountain roads, the drivers bear the dynamic load from the road environment. The sudden change of driving load will produce great safety risks and even lead to traffic accidents. In order to explore the driving risk of two‐lane road in mountainous areas, it is necessary to analyze the change of driving load from a quantitative point of view. Using the road driving experiment, 10 male drivers were selected according to the experimental road conditions, collect the driver's visual and heart rate indicators, analyze the driver's physiological indicators, and study the driver's driving load evolution process on the mountain road. Combined with the classification of road environment, a driving load evaluation model based on catastrophe progression method is constructed. The driving load is divided into four states: low load state, affordable state, chaotic state and high load state. It is found that most sections of mountain roads are in a low load and bearable state. In semi closed and closed environment, the driving load is in a chaotic state, which affects the driving safety. The evaluation model can be used to evaluate the traffic safety of road environment.

With the rapid development of urban transportation and the increase in per capita car ownership, the problem of urban traffic congestion is becoming increasingly prominent. Due to the uneven distribution of crowd in different regions of the city, it is difficult to determine and solve the traffic dynamics congestion. In order to solve the problem that it is difficult to determine the dynamics of traffic congestion areas caused by uneven distribution of vitality in different regions of mountainous cities, a crowded mega mountainous city is selected as research object and it proposes a model to calculate the change characteristics of regional crowd gathering. Baidu Heatmap is used as it could distinguish crowd gathering in certain urban core area. The heat map pictures in dozens of consecutive days is extracted and researchers conducted pixel statistical classification on thermal map images. Based on the pixel data of different levels of the pictures, the calculation model is established and an algorithm based on particle swarm optimization is proposed. The calibration of the relative active population equivalent density is conducted, and the distribution characteristics of crowd gathering in time and space are analyzed. The results show that there are obvious spatiotemporal characteristics for this selected city. In time, holidays have an important impact on crowd gathering. The peak time of crowd gathering on weekdays is different from that on rest days. The research in this paper has a direct practical value for the identification of traffic congestion areas and the corresponding governance measures. The dynamic identification of population gathering areas in mountainous mega cities, demand prediction for various transportation regions, and future population OD(Origin—Destination) planning are of great significance.

In order to obtain the quantitative relationship between multisource data from road landscape and driving visual comfort in two‐lane mountainous road, we collected the driver's eye movement data and road environment data through real vehicle tests. The threshold segmentation method and the target landscape area ratio method are used to process the visual image, and the spatial enclosure degree is used to express the driver's sense of spatial closure. In addition, an HSV color model is established to characterize the driver's visual perception of the mountain highway landscape environment. Combining the target landscape area ratio of road landscape with the amount of color information, the calculation method of road landscape information is obtained. According to the characteristics of normal distribution of pupil area ratio, five grades of driver's visual comfort level are proposed, and the regression relationship between comfort level and landscape information is established. The study found that there is a significant negative correlation between the amount of road landscape information and the driver's visual comfort. When the amount of road landscape information is less than 0.338, the driving comfort is higher, which is conducive to driving safety. However, when the amount of landscape information in the road area exceeds 0.644, the driving comfort decreases significantly, which is detrimental to driving safety.

Mountainous road landscape is the main source of driving information. The characteristics of two-lane mountainous road result in real-time dynamic changes in the driver's vision interesting areas. In order to explore the dynamic gaze characteristics, a driving experiment is conducted, and the gaze data of 10 drivers are collected. Markov chain is used to analyze the change process of gaze. The results show that: (1) when the current gaze point is in the straight front area, different road landscape has no significant impact on the gaze shift probability; (2) when the current gaze point is in the near left area, next gaze will expand the search scope to obtain much more driving information; (3) when the current gaze point is in the near right area, there is a high probability that the driver's next gaze will return to the front area; (4) when the current gaze point is in the far right area, the gaze will move back and forth between the near right and the far right areas; (5) when the current gaze point is in the far left area, there is a high probability that the gaze will remain in current area; (6) the main source of traffic information obtained by the driver in mountainous road landscape is the straight front area in the vision field, and the gaze point constantly shifts between the far ahead and the near ahead. The research results can provide technical reference for the construction of landscape in mountainous two-lane road.

文中基于某双向四车道高速公路连续9年的交通事故数据,将交通事故分为严重事故、一般事故2种类型,利用二项Logistic回归分析模型,选取了涉事车型、事发天气、事发时间、特殊路段类型、事故类型和事发月份共六类自变量进行分析,筛选其中的对高速公路的交通事故后果有明显影响的因素.研究结果表明:涉事车型、事发时间、特殊路段类型、事故类型和事发月份均对交通事故的严重程度有显著性影响,并从车型管制、加强路面巡逻、隧道及长陡坡路段采取主动安全措施、增强被动防护以提高路侧设施的保护能力、宣传教育等方面,提出了减缓交通事故严重程度的综合措施建议.

我国高速公路已逐渐进入大养护时代,准确合理的路面性能预测是路面养护决策的重要环节.以甬台温高速公路历年检测数据为基础,重点关注路面使用性能指标,建立科学准确的路面性能预测模型,分析路面性能衰变规律,得出优化合理的养护路段及养护措施,为科学化养护决策,针对性精准养护实施,节约养护成本提供依据,该结论可供高速公路养护单位参考.

现阶段有关沥青阻燃性能已有较多研究,但阻燃剂对沥青流变性能影响的研究较少,本文选择无机氮系阻燃剂MCA对高黏沥青进行改性,并从微观性能、阻燃性能、物理性能、高温性能及抗疲劳性能5个方面进行研究.通过FTIR试验结果得出MCA阻燃剂与高黏沥青间仅为物理共混,并通过温度扫描和多重应力蠕变恢复试验(MSCR)发现MCA阻燃剂对高黏沥青高温性能有较大提升作用,通过线性振幅扫描试验(LAS)发现MCA阻燃剂对高黏沥青抗疲劳性能有提升作用.结合MCA改性沥青流变性能及经济成本,推荐MCA阻燃剂掺量为8％.