Travelling characteristics of road vehicles on single-level rail-cum-road bridge under the dynamic and aerodynamic impact of travelling trains

Aerodynamic and dynamic interference from trains is a key issue of concern for the safety of road vehicles travelling on single-level rail-cum road bridges.Based on the wind-road vehicle-train-bridge(WRTB)coupled vibration system developed herein,this study examines the dynamic characteristics when road vehicles meet trains in this situation.The influence of load combination,vehicle type and vehicle location is analyzed.A method to obtain the aerodynamic load of road vehicles encountering the train at an arbitrary wind speed is proposed.The results show that due to the windproof facilities and the large line distance between the railway and highway,the aerodynamic and dynamic influence of trains on road vehicles is slight,and the vibration of road vehicles depends on the road roughness.Among the road vehicles discussed,the bus is the easiest to rollover,and the truck-trailer is the easiest to sideslip.Compared with the aerodynamic impact of trains,the crosswind has a more significant influence on road vehicles.The first peak/valley value of aerodynamic loads determines the maximum dynamic response,and the quick method is optimized based on this conclusion.Test cases show that the optimized method can produce conservative results and can be used for relevant research or engineering applications.

Automation in road distress detection,diagnosis and treatment

Road transportation plays a crucial role in society and daily life,as the functioning and durability of roads can significantly impact a nation's economic development.In the whole life cycle of the road,the emergence of disease is unavoidable,so it is necessary to adopt relevant technical means to deal with the disease.This study comprehensively reviews the advancements in computer vision,artificial intelligence,and mobile robotics in the road domain and examines their progress and applications in road detection,diagnosis,and treatment,especially asphalt roads.Specifically,it analyzes the research progress in detecting and diagnosing surface and internal road distress and related techniques and algorithms are compared.In addition,also introduces various road gover-nance technologies,including automated repairs,intelligent construction,and path planning for crack sealing.Despite their proven effectiveness in detecting road distress,analyzing diagnoses,and planning maintenance,these technologies still confront challenges in data collection,parameter optimization,model portability,system accuracy,robustness,and real-time performance.Consequently,the integration of multidisciplinary technologies is imperative to enable the development of an integrated approach that includes road detection,diagnosis,and treatment.This paper addresses the challenges of precise defect detection,condition assessment,and unmanned construction.At the same time,the efficiency of labor liberation and road maintenance is achieved,and the automation level of the road engineering industry is improved.

3D Road Network Modeling and Road Structure Recognition in Internet of Vehicles

Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transportationsystem. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topologicalstructure of IoV to have the high space and time complexity.Network modeling and structure recognition for 3Droads can benefit the description of topological changes for IoV. This paper proposes a 3Dgeneral roadmodel basedon discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on moving vehicles areanalyzed. Then the effects of road curvature radius (Ra), longitudinal slope (Slo), and length (Len) on speed andacceleration are studied. Finally, a general 3D road network model based on road section features is established.This paper also presents intersection and road section recognition methods based on the structural features ofthe 3D road network model and the road features. Real GIS data from a specific region of Beijing is adopted tocreate the simulation scenario, and the simulation results validate the general 3D road network model and therecognitionmethod. Therefore, thiswork makes contributions to the field of intelligent transportation by providinga comprehensive approach tomodeling the 3Droad network and its topological changes in achieving efficient trafficflowand improved road safety.

Review of advanced road materials, structures, equipment, and detection technologies

As a vital and integral component of transportation infrastructure,pavement has a direct and tangible impact on socio-economic sustainability.In recent years,an influx of groundbreaking and state-of-the-art materials,structures,equipment,and detection technologies related to road engineering have continually and progressively emerged,reshaping the landscape of pavement systems.There is a pressing and growing need for a timely summarization of the current research status and a clear identification of future research directions in these advanced and evolving technologies.Therefore,Journal of Road Engineering has undertaken the significant initiative of introducing a comprehensive review paper with the overarching theme of“advanced road materials,structures,equipment,and detection technologies”.This extensive and insightful review meticulously gathers and synthesizes research findings from 39 distinguished scholars,all of whom are affiliated with 19 renowned universities or research institutions specializing in the diverse and multidimensional field of highway engineering.It covers the current state and anticipates future development directions in the four major and interconnected domains of road engineering:advanced road materials,advanced road structures and performance evaluation,advanced road construction equipment and technology,and advanced road detection and assessment technologies.

Structural Design of Roadbed and Pavement in Transition Section of Roads and Bridges

As the lifeline of social development,road and bridge projects are the main channel to realize resource transportation and economic circulation.Ensuring the quality of road and bridge project construction is crucial for the development of society,the economy,and people’s livelihoods.This paper studies the design of roadbed pavement structures in road and bridge transition sections.It aims to provide technical references and significance for China’s road and bridge engineering design and construction units,promoting scientific and standardized design in these actions.This will contribute to the safety and stable operation of road and bridge projects,offering effective technical support.Furthermore,it seeks to foster the sustainable and healthy development of China’s road and bridge engineering on a macro level.

Risk assessment of oil and gas investment environment in countries along the Belt and Road Initiative

With the implementation of the Belt and Road Initiative, China is deepening its cooperation in oil and gas resources with countries along the Initiative. In order to better mitigate risks and enhance the safety of investments, it is of significant importance to research the oil and gas investment environment in these countries for China's overseas investment macro-layout. This paper proposes an indicator system including 27 indicators from 6 dimensions. On this basis, game theory models combined with global entropy method and analytic hierarchy process are applied to determine the combined weights, and the TOPSIS-GRA model is utilized to assess the risks of oil and gas investment in 76 countries along the Initiative from 2014 to 2021. Finally, the GM(1,1) model is employed to predict risk values for 2022-2025. In conclusion, oil and gas resources and political factors have the greatest impact on investment environment risk, and 12 countries with greater investment potential are selected through cluster analysis in conjunction with the predicted results. The research findings may provide scientific decisionmaking recommendations for the Chinese government and oil enterprises to strengthen oil and gas investment cooperation with countries along the Belt and Road Initiative.

The coordinated evolution of ecological environment,public service,and tourism economy along the Silk Road Economic Belt,using the Dual-Carbon Targets

Carbon peak and carbon neutrality(dual-carbon)are important targets for the international response to climate change.The Silk Road Economic Belt is a strategic resource region and is important for future ecological environment and tourism development.Based on the“dual-carbon”targets,the Single index quantification,Multiple index synthesis,and Poly-criteria integration evaluation model were used in this study to measure the coordinated development index of the ecological environment,public service,and tourism economy along the Silk Road Economic Belt and to analyze its spatial and temporal evolution.Further,it explores the dynamic evolution and development trend of the three systems using the Kernel Density and Grey Markov Prediction Model.The results show that the coordinated development index along this region needs to be improved during the study period.Furthermore,the coordinated development index of the Southwest region is relatively higher than that of the Northwest region.From the development trend of the three systems,all of them develop in a stable manner;however,the tourism economy system is easily affected by external disturbances.The coordinated development index of the three systems changes dynamically and tends to be in a good state of coordination.There is a certain spatial and temporal heterogeneity.The gravity center of the coordinated development index has been in the Southwest region.During the forecast period,the coordinated development index along this region will improve significantly,while insufficient and unbalanced development will continue.

A Brief Discussion on the Development of the Silk-Weaving Industry Along the “Southern Silk Road” in Yunnan

Ancient Yunnan was one of the most significant regions along China’s ancient“Southern Silk Road.”During the Nanzhao period(738–902)of the late Tang Dynasty,Yunnan’s silk-weaving industry underwent a qualitative leap as skilled silk craftsmen from the Bashu area migrated to Yunnan and introduced mulberry planting,silkworm breeding,and advanced silk-weaving techniques from Sichuan to the region.Consequently,people in Yunnan gradually acquired expertise in brocade weaving and embroidery.Many even mastered complex silk-weaving techniques.The development and progress of the silk-weaving industry in the ancient Yunnan region were intricately linked to the economic function and value of silk as both a commodity and currency along the“Southern Silk Road.”The local government in ancient Yunnan was greatly motivated by the economic interests brought by the development of silk-related industries and recognized the significance of developing the local silk industry.They even initiated a campaign to capture skilled silk craftsmen from Sichuan,aiming to foster the growth of the silk-weaving industry in Yunnan.After years of dedicated efforts from the local government in ancient Yunnan,the region emerged as a significant hub for silk production along China’s ancient“Southern Silk Road.”Despite the devastation caused by the wars in other parts of the country,Yunnan’s silk industry continued to thrive and provide ample silk products to sustain trade along this renowned route.In the contemporary era,amidst the decline of the silk-weaving industry in eastern China,Yunnan has proposed an industrial development strategy known as“relocating the silk-weaving industry from east to west.”This involves introducing advanced silk production techniques from the eastern regions into Yunnan to enhance and enrich its local silk industry,thereby establishing it as a traditional national sector and securing a competitive position within the global silk market.The historical experience of Yunnan’s silk industry demonstrated that economic development opportunities can only be seized through proactive endeavors rather than passive anticipation.The modern Yunnan silk industry,which upholds its historical traditions,continues to actively engage in international high-end technical cooperation,thus ensuring the enduring vitality of the ancient“Southern Silk Road.”

Research on Developing an Assessment Scale for Tourism Experience Elements of Ancient Shu Road Heritage Trail

Cultural ancient roads,known in Chinese as gudao,serve as heritage trails that carry historical exchanges across various regions in China.Due to their extensive preservation,wide geographical distribution,diverse thematic variations,and considerable tourist appeal,these paths have emerged as representative heritage trails,increasingly transforming into a novel tourism product experience that is highly favored by tourists and recognized by government authorities.However,research on ancient roads for tourism in China currently lacks a systematic theoretical framework,as well as relevant policies,regulations,and standards to guide their practical development.Therefore,there is a pressing need to draw upon international best practices and conduct foundational research to develop an experience element system that aligns with the perceptions,behaviors,and consumption characteristics of Chinese tourists,thereby advancing theoretical exploration in this field.This study focuses on the representative Ancient Shu Road as a case study and employs a mixed-method approach that integrates qualitative and quantitative research.It aims to construct a tourist-centric scale for the experience elements of ancient road tourism while analyzing the interactive relationship between these experience elements and tourist needs.This study addresses a significant gap in the development of indicator systems for domestic studies of ancient road tourism experiences.Ultimately,the study establishes a comprehensive scale that encompasses three core categories—trail resources and environment,facilities and services,and modes of tourism activities—along with eight primary dimensions:core resources,surrounding cultural environment,surrounding natural environment,tourism reception facilities and services,infrastructure and support services,information facilities and information services,and outdoor and recreational activities.This scale consists of thirty-two specific items,providing a robust reference for future research endeavors.Additionally,the study proposes specific development strategies related to key mechanisms,spatial configuration,and facility construction to enhance the overall development of ancient road tourism.

基于ROAD的租车订购系统业务流程建模

基于业务架构为中心的企业架构开发思路,采用开放组架构框架(TOGAF)业务架构ACF元模型的划分,提出了一种ROAD架构迭代建模方法。针对目前ROAD元架构中业务活动模型采用IDEF0的活动模型导致的面向场景业务能力的不足,文中通过使用BPMN模型来覆盖IDEF0的活动建模,避免在描述复杂的业务过程时可能存在的局限性,并且更好地捕捉和表示所有的细节和关系,不会使得模型过于抽象。从而实现面向场景的系统建模和管理,提高业务架构设计的效率和精度。最后,文章中以旅游出行租车订购系统为例的方法,采用ROAD元架构方法建立场景化业务架构模型组,并对其进行讨论和改进,为现有架构体系提供一种面向场景的扩展思路。

Intelligent extraction of road cracks based on vehicle laser point cloud and panoramic sequence images

In light of the limited efficacy of conventional methods for identifying pavement cracks and the absence of comprehensive depth and location data in two-dimensional photographs,this study presents an intelligent strategy for extracting road cracks.This methodology involves the integration of laser point cloud data obtained from a vehicle-mounted system and a panoramic sequence of images.The study employs a vehicle-mounted LiDAR measurement system to acquire laser point cloud and panoramic sequence image data simultaneously.A convolutional neural network is utilized to extract cracks from the panoramic sequence image.The extracted sequence image is then aligned with the laser point cloud,enabling the assignment of RGB information to the vehicle-mounted three dimensional(3D)point cloud and location information to the two dimensional(2D)panoramic image.Additionally,a threshold value is set based on the crack elevation change to extract the aligned roadway point cloud.The three-dimensional data pertaining to the cracks can be acquired.The experimental findings demonstrate that the use of convolutional neural networks has yielded noteworthy outcomes in the extraction of road cracks.The utilization of point cloud and image alignment techniques enables the extraction of precise location data pertaining to road cracks.This approach exhibits superior accuracy when compared to conventional methods.Moreover,it facilitates rapid and accurate identification and localization of road cracks,thereby playing a crucial role in ensuring road maintenance and traffic safety.Consequently,this technique finds extensive application in the domains of intelligent transportation and urbanization development.The technology exhibits significant promise for use in the domains of intelligent transportation and city development.

Local failure mechanism of sand-blocking fence in latticed dune along desert roads

The latticed dunes in the Tengger Desert are widely distributed,and the sand-blocking fence placed here are highly susceptible to local failure due to complex wind-sand activities,posing a serious threat to the safe operation of the highway.To explore the local failure mechanism of sand-blocking fence in the latticed dune area,the local failure of sand-blocking fence in the latticed dune areas along the Wuhai-Maqin Highway in China was observed.Taking the first main ridge of the latticed dune as the placement location,the structure of the wind-sand flow field of sand-blocking fence placed at top,the bottom and the middle of windward slope was analyzed by Computational Fluid Dynamics(CFD).The results show that when placed at top of the first main ridge,the wind speed near the sand-blocking fence is the highest,up to 15.23 m/s.Therefore,the wind load strength on the sand barrier is correspondingly larger,up to 232.61 N∙m-2.As the strength of material continues to decrease,the nylon net is prone to breakage.The roots of the angle steel posts are susceptible to hollowing by vortex action,which can cause sand-blocking fence to fall over in strong wind conditions.When placed at the bottom of windward slope,wind speed drop near sand-blocking fence is greatest,with the decrease of 12.48-14.32 m/s compared to the original wind speed.This is highly likely to lead to large-scale deposition of sand particles and burial of the sand-blocking fence.When placed in the middle of windward slope,sand-blocking fence is subjected to less wind load strength(168.61N∙m-2)and sand particles are mostly deposited at the bottom of windward slope,with only a small amount of sand accumulating at the root of sand-blocking fence.Based on field observations and numerical modelling results,when the sand-blocking fence is placed in latticed dune area,it should be placed in the middle of the windward slope of the first main ridge as a matter of priority.Besides the sand-blocking fence should be placed at the top of the first main ridge,and sand fixing measures should be added.

Numerical Prediction of Ride Comfort of Tracked Vehicle Equipped with Novel Flexible Road Wheels

Enhancing ride comfort has always constituted a crucial focus in the design and research of modern tracked vehicles,heavily reliant on the driving system's performance.While the road wheel is a key component of the driving system,traditional road wheels predominantly adopt a solid structure,exhibiting subpar adhesion performance and damping effects,thereby falling short of meeting the demands for high-speed,stable,and long-distance driving in tracked vehicles.Addressing this issue,this paper proposes a novel type of flexible road wheel(FRW)characterized by a catenary construction.The study investigates the ride comfort of tracked vehicles equipped with flexible road wheels by integrating finite element and vehicle dynamic.First,three-dimensional(3D)finite element(FE)models of both flexible and rigid road wheels are established,considering material and contact nonlinearities.These models are validated through a wheel radial loading test.Based on the validated FE model,the paper uncovers the relationship between load and radial deformation of the road wheel,forming the basis for a nonlinear mathematical model.Subsequently,a half-car model of a tracked vehicle with seven degrees of freedom is established using Newton's second law.A random road model,considering the track effect and employing white noise,is constructed.The study concludes by examining the ride comfort of tracked vehicles equipped with flexible and rigid road wheels under various speeds and road grades.The results demonstrate that,in comparison to the rigid road wheel(RRW),the flexible road wheel enhances the ride comfort of tracked vehicles on randomly uneven roads.This research provides a theoretical foundation for the implementation of flexible road wheels in tracked vehicles.

Unstructured Road Extraction in UAV Images based on Lightweight Model

There is no unified planning standard for unstructured roads,and the morphological structures of these roads are complex and varied.It is important to maintain a balance between accuracy and speed for unstructured road extraction models.Unstructured road extraction algorithms based on deep learning have problems such as high model complexity,high computational cost,and the inability to adapt to current edge computing devices.Therefore,it is best to use lightweight network models.Considering the need for lightweight models and the characteristics of unstructured roads with different pattern shapes,such as blocks and strips,a TMB(Triple Multi-Block)feature extraction module is proposed,and the overall structure of the TMBNet network is described.The TMB module was compared with SS-nbt,Non-bottleneck-1D,and other modules via experiments.The feasibility and effectiveness of the TMB module design were proven through experiments and visualizations.The comparison experiment,using multiple convolution kernel categories,proved that the TMB module can improve the segmentation accuracy of the network.The comparison with different semantic segmentation networks demonstrates that the TMBNet network has advantages in terms of unstructured road extraction.

Optimized Binary Neural Networks for Road Anomaly Detection:A TinyML Approach on Edge Devices

Integrating Tiny Machine Learning(TinyML)with edge computing in remotely sensed images enhances the capabilities of road anomaly detection on a broader level.Constrained devices efficiently implement a Binary Neural Network(BNN)for road feature extraction,utilizing quantization and compression through a pruning strategy.The modifications resulted in a 28-fold decrease in memory usage and a 25%enhancement in inference speed while only experiencing a 2.5%decrease in accuracy.It showcases its superiority over conventional detection algorithms in different road image scenarios.Although constrained by computer resources and training datasets,our results indicate opportunities for future research,demonstrating that quantization and focused optimization can significantly improve machine learning models’accuracy and operational efficiency.ARM Cortex-M0 gives practical feasibility and substantial benefits while deploying our optimized BNN model on this low-power device:Advanced machine learning in edge computing.The analysis work delves into the educational significance of TinyML and its essential function in analyzing road networks using remote sensing,suggesting ways to improve smart city frameworks in road network assessment,traffic management,and autonomous vehicle navigation systems by emphasizing the importance of new technologies for maintaining and safeguarding road networks.

Numerical Simulations of Wave Impact Forces on the Open-Type Sea Access Road Using A Two-Phase SPH Model

A numerical study based on a two-dimensional two-phase SPH(Smoothed Particle Hydrodynamics)model to analyze the action of water waves on open-type sea access roads is presented.The study is a continuation of the analyses presented by Chen et al.(2022),in which the sea access roads are semi-immersed.In this new configuration,the sea access roads are placed above the still water level,therefore the presence of the air phase becomes a relevant issue in the determination of the wave forces acting on the structures.Indeed,the comparison of wave forces on the open-type sea access roads obtained from the single and two-phase SPH models with the experimental results shows that the latter are in much better agreement.So in the numerical simulations,a two-phaseδ-SPH model is adopted to investigate the dynamical problems.Based on the numerical results,the maximum horizontal and uplifting wave forces acting on the sea access roads are analyzed by considering different wave conditions and geometries of the structures.In particular,the presence of the girder is analyzed and the differences in the wave forces due to the air cushion effects which are created below the structure are highlighted.

Resilience assessment and optimization method of city road network in the post-earthquake emergency period

The post-earthquake emergency period,which is a sensitive time segment just after an event,mainly focuses on saving life and restoring social order.To improve the seismic resilience of city road networks,a resilience evaluation method used in the post-earthquake emergency period is proposed.The road seismic damage index of a city road network can consider the influence of roads,bridges and buildings along the roads,etc.on road capacity after an earthquake.A function index for a city road network is developed,which reflects the connectivity,redundancy,traffic demand and traffic function of the network.An optimization model for improving the road repair order in the post-earthquake emergency period is also developed according to the resilience evaluation,to enable decision support for city emergency management and achieve the best seismic resilience of the city road network.The optimization model is applied to a city road network and the results illustrate the feasibility of the resilience evaluation and optimization method for a city road network in the post-earthquake emergency period.

ConvNeXt-UperNet-Based Deep Learning Model for Road Extraction from High-Resolution Remote Sensing Images

When existing deep learning models are used for road extraction tasks from high-resolution images,they are easily affected by noise factors such as tree and building occlusion and complex backgrounds,resulting in incomplete road extraction and low accuracy.We propose the introduction of spatial and channel attention modules to the convolutional neural network ConvNeXt.Then,ConvNeXt is used as the backbone network,which cooperates with the perceptual analysis network UPerNet,retains the detection head of the semantic segmentation,and builds a new model ConvNeXt-UPerNet to suppress noise interference.Training on the open-source DeepGlobe and CHN6-CUG datasets and introducing the DiceLoss on the basis of CrossEntropyLoss solves the problem of positive and negative sample imbalance.Experimental results show that the new network model can achieve the following performance on the DeepGlobe dataset:79.40%for precision(Pre),97.93% for accuracy(Acc),69.28% for intersection over union(IoU),and 83.56% for mean intersection over union(MIoU).On the CHN6-CUG dataset,the model achieves the respective values of 78.17%for Pre,97.63%for Acc,65.4% for IoU,and 81.46% for MIoU.Compared with other network models,the fused ConvNeXt-UPerNet model can extract road information better when faced with the influence of noise contained in high-resolution remote sensing images.It also achieves multiscale image feature information with unified perception,ultimately improving the generalization ability of deep learning technology in extracting complex roads from high-resolution remote sensing images.

Weakly Supervised Network with Scribble-Supervised and Edge-Mask for Road Extraction from High-Resolution Remote Sensing Images

Significant advancements have been achieved in road surface extraction based on high-resolution remote sensingimage processing. Most current methods rely on fully supervised learning, which necessitates enormous humaneffort to label the image. Within this field, other research endeavors utilize weakly supervised methods. Theseapproaches aim to reduce the expenses associated with annotation by leveraging sparsely annotated data, such asscribbles. This paper presents a novel technique called a weakly supervised network using scribble-supervised andedge-mask (WSSE-net). This network is a three-branch network architecture, whereby each branch is equippedwith a distinct decoder module dedicated to road extraction tasks. One of the branches is dedicated to generatingedge masks using edge detection algorithms and optimizing road edge details. The other two branches supervise themodel’s training by employing scribble labels and spreading scribble information throughout the image. To addressthe historical flaw that created pseudo-labels that are not updated with network training, we use mixup to blendprediction results dynamically and continually update new pseudo-labels to steer network training. Our solutiondemonstrates efficient operation by simultaneously considering both edge-mask aid and dynamic pseudo-labelsupport. The studies are conducted on three separate road datasets, which consist primarily of high-resolutionremote-sensing satellite photos and drone images. The experimental findings suggest that our methodologyperforms better than advanced scribble-supervised approaches and specific traditional fully supervised methods.

Utilization of Solid Waste Materials as Roadbed Fillers in Road Construction:a Review

China has a large solid waste stockpile and a low resource utilisation rate,and the utilisation of solid waste resources is of great significance in promoting sustainable social development.In order to further promote the green and efficient development of China's road field,an overview of the current status of the application,research progress,hot frontiers,problems and their countermeasures based on the three aspects of industrial solid wastes,engineering solid wastes and municipal solid wastes in highway engineering was conducted,and the development prospect of the resourceful utilisation of solid waste in highway engineering was outlooked,with a view to promoting the development of China's green roads.Statistics on the stockpile,utilisation and comprehensive utilisation rate of industrial solid wastes in China are presented,and the optimal mixing amount,production process and application technology of industrial solid wastes for road base materials are systematically summarised.Based on the concept of high-value utilisation of solid waste,the mechanical properties,durability,construction technology and quality control standards of engineering solid waste applied in roadbed engineering are summarised,and the difficulties in the application of engineering solid waste in road engineering are summarised.Finally,the feasibility,mechanical properties and environmental characteristics of municipal solid waste domestic waste incinerator slag,waste tyres and plastics applied in road engineering are summarised.This review can provide references and lessons for the design and development of green roads,and promote the innovation and development of greening road engineering.