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Automation in road distress detection,diagnosis and treatment
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作者 Xu Yang Jianqi Zhang +3 位作者 Wenbo Liu Jiayu Jing Hao Zheng Wei Xu 《Journal of Road Engineering》 2024年第1期1-26,共26页
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 emerge... 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. 展开更多
关键词 road detection road diagnosis road treatment Deep learning Intelligent maintenance
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3D Road Network Modeling and Road Structure Recognition in Internet of Vehicles
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作者 Dun Cao Jia Ru +3 位作者 Jian Qin Amr Tolba Jin Wang Min Zhu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第2期1365-1384,共20页
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 transp... 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. 展开更多
关键词 Internet of vehicles road networks 3D road model structure recognition GIS
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Review of advanced road materials, structures, equipment, and detection technologies 被引量:2
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作者 JRE Editorial Office Maria Chiara Cavalli +37 位作者 De Chen Qian Chen Yu Chen Augusto Cannone Falchetto Mingjing Fang Hairong Gu Zhenqiang Han Zijian He Jing Hu Yue Huang Wei Jiang Xuan Li Chaochao Liu Pengfei Liu Quantao Liu Guoyang Lu Yuan Ma Lily Poulikakos Jinsong Qian Aimin Sha Liyan Shan Zheng Tong B.Shane Underwood Chao Wang Chaohui Wang Di Wang Haopeng Wang Xuebin Wang Chengwei Xing Xinxin Xu Min Ye Huanan Yu Huayang Yu Zhe Zeng You Zhan Fan Zhang Henglong Zhang Wenfeng Zhu 《Journal of Road Engineering》 2023年第4期370-468,共99页
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,... 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. 展开更多
关键词 road engineering Advanced road material Advanced road structure Advanced road equipment Advanced road detection technology
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Structural Design of Roadbed and Pavement in Transition Section of Roads and Bridges
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作者 Bai Fan 《Journal of World Architecture》 2024年第4期21-26,共6页
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 f... 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. 展开更多
关键词 road and bridge transition section roadbed pavement structure design Lap plate Easing transition section Drainage system
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Risk assessment of oil and gas investment environment in countries along the Belt and Road Initiative 被引量:1
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作者 Bao-Jun Tang Chang-Jing Ji +3 位作者 Yu-Xian Zheng Kang-Ning Liu Yi-Fei Ma Jun-Yu Chen 《Petroleum Science》 SCIE EI CAS CSCD 2024年第2期1429-1443,共15页
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 inv... 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. 展开更多
关键词 Belt and road Initiative Oil and Gas Investment Risk assessment
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A Brief Discussion on the Development of the Silk-Weaving Industry Along the “Southern Silk Road” in Yunnan 被引量:1
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作者 Lin Kaiqiang 《Contemporary Social Sciences》 2024年第1期18-33,共16页
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 l... 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.” 展开更多
关键词 Southern Silk road Bashu area YUNNAN silk-weaving technique
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基于ROAD的租车订购系统业务流程建模
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作者 严志超 倪枫 +3 位作者 刘姜 李业勋 陈年年 周兴郡 《智能计算机与应用》 2024年第5期227-234,共8页
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... 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。 展开更多
关键词 业务架构建模 road元架构 BPMN IDEF0
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Local failure mechanism of sand-blocking fence in latticed dune along desert roads
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作者 LI Liangying LV Lele +3 位作者 LI Qi WANG Zhenqiang YANG Youhai YIN Wenhua 《Journal of Mountain Science》 SCIE CSCD 2024年第2期526-537,共12页
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 o... 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. 展开更多
关键词 Latticed dune Sand-blocking fence Local failure Numerical simulation Desert roads
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Numerical Prediction of Ride Comfort of Tracked Vehicle Equipped with Novel Flexible Road Wheels
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作者 Yaoji Deng Zhiyue Wang +3 位作者 Youqun Zhao Junjie Gong Hui Shen Fen Lin 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2024年第4期277-289,共13页
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 th... 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. 展开更多
关键词 Ride comfort Flexible road wheel Finite element model Dynamic model Tracked vehicle
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Unstructured Road Extraction in UAV Images based on Lightweight Model
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作者 Di Zhang Qichao An +3 位作者 Xiaoxue Feng Ronghua Liu Jun Han Feng Pan 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2024年第2期372-384,共13页
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 roa... 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. 展开更多
关键词 Unstructured road Lightweight model Triple Multi-Block(TMB) Semantic segmentation net
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Optimized Binary Neural Networks for Road Anomaly Detection:A TinyML Approach on Edge Devices
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作者 Amna Khatoon Weixing Wang +2 位作者 Asad Ullah Limin Li Mengfei Wang 《Computers, Materials & Continua》 SCIE EI 2024年第7期527-546,共20页
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 N... 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. 展开更多
关键词 Edge computing remote sensing TinyML optimization BNNs road anomaly detection QUANTIZATION model compression
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Resilience assessment and optimization method of city road network in the post-earthquake emergency period
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作者 Wang Haoran Xiao Jia +1 位作者 Li Shuang Zhai Changhai 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2024年第3期765-779,共15页
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 ... 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. 展开更多
关键词 city road network post-earthquake emergency period traffic demand resilience evaluation optimization model
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ConvNeXt-UperNet-Based Deep Learning Model for Road Extraction from High-Resolution Remote Sensing Images
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作者 Jing Wang Chen Zhang Tianwen Lin 《Computers, Materials & Continua》 SCIE EI 2024年第8期1907-1925,共19页
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 inco... 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. 展开更多
关键词 Deep learning semantic segmentation remote sensing imagery road extraction
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Weakly Supervised Network with Scribble-Supervised and Edge-Mask for Road Extraction from High-Resolution Remote Sensing Images
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作者 Supeng Yu Fen Huang Chengcheng Fan 《Computers, Materials & Continua》 SCIE EI 2024年第4期549-562,共14页
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 human... 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. 展开更多
关键词 Semantic segmentation road extraction weakly supervised learning scribble supervision remote sensing image
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Autonomous Vehicle Platoons In Urban Road Networks:A Joint Distributed Reinforcement Learning and Model Predictive Control Approach
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作者 Luigi D’Alfonso Francesco Giannini +3 位作者 Giuseppe Franzè Giuseppe Fedele Francesco Pupo Giancarlo Fortino 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第1期141-156,共16页
In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory... In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory tubes by means of routing decisions complying with traffic congestion criteria. To this end, a novel distributed control architecture is conceived by taking advantage of two methodologies: deep reinforcement learning and model predictive control. On one hand, the routing decisions are obtained by using a distributed reinforcement learning algorithm that exploits available traffic data at each road junction. On the other hand, a bank of model predictive controllers is in charge of computing the more adequate control action for each involved vehicle. Such tasks are here combined into a single framework:the deep reinforcement learning output(action) is translated into a set-point to be tracked by the model predictive controller;conversely, the current vehicle position, resulting from the application of the control move, is exploited by the deep reinforcement learning unit for improving its reliability. The main novelty of the proposed solution lies in its hybrid nature: on one hand it fully exploits deep reinforcement learning capabilities for decisionmaking purposes;on the other hand, time-varying hard constraints are always satisfied during the dynamical platoon evolution imposed by the computed routing decisions. To efficiently evaluate the performance of the proposed control architecture, a co-design procedure, involving the SUMO and MATLAB platforms, is implemented so that complex operating environments can be used, and the information coming from road maps(links,junctions, obstacles, semaphores, etc.) and vehicle state trajectories can be shared and exchanged. Finally by considering as operating scenario a real entire city block and a platoon of eleven vehicles described by double-integrator models, several simulations have been performed with the aim to put in light the main f eatures of the proposed approach. Moreover, it is important to underline that in different operating scenarios the proposed reinforcement learning scheme is capable of significantly reducing traffic congestion phenomena when compared with well-reputed competitors. 展开更多
关键词 Distributed model predictive control distributed reinforcement learning routing decisions urban road networks
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Three-dimensional thermohaline structure estimation derived from HY-2 satellite data over the Maritime Silk Road and its applications
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作者 Zhiqiang Chen Xidong Wang +4 位作者 Xiangyu Wu Yuan Cao Zikang He Dakui Wang Jian Chen 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2024年第5期41-53,共13页
Estimated ocean subsurface fields derived from satellite observations provide potential data sources for operational marine environmental monitoring and prediction systems.This study employs a statistic regression rec... Estimated ocean subsurface fields derived from satellite observations provide potential data sources for operational marine environmental monitoring and prediction systems.This study employs a statistic regression reconstruction method,in combination with domestic autonomous sea surface height and sea surface temperature observations from the Haiyang-2(HY-2)satellite fusion data,to establish an operational quasi-realtime three-dimensional(3D)temperature and salinity products over the Maritime Silk Road.These products feature a daily temporal resolution and a spatial resolution of 0.25°×0.25°and exhibit stability and continuity.We have demonstrated the accuracy of the reconstructed thermohaline fields in capturing the 3D thermohaline variations through comprehensive statistical evaluations,after comparing them against Argo observations and ocean analysis data from 2022.The results illustrate that the reconstructed fields effectively represent seasonal variations in oceanic subsurface structures,along with structural changes resulting from mesoscale processes,and the upper ocean’s responses to tropical cyclones.Furthermore,the incorporation of HY-2 satellite observations notably enhances the accuracy of temperature and salinity reconstructions in the Northwest Pacific Ocean and marginally improves salinity reconstruction accuracy in the North Indian Ocean when compared to the World Ocean Atlas 2018 monthly climatology thermohaline fields.As a result,the reconstructed product holds promise for providing quasi-real-time 3D temperature and salinity field information to facilitate fast decisionmaking during emergencies,and also offers foundational thermohaline fields for operational ocean reanalysis and forecasting systems.These contributions enhance the safety and stability of ocean subsurface activities and navigation. 展开更多
关键词 HY-2 satellite observations subsurface structures reconstruction Maritime Silk road operational thermohaline product
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Automatic Road Tunnel Crack Inspection Based on Crack Area Sensing and Multiscale Semantic Segmentation
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作者 Dingping Chen Zhiheng Zhu +1 位作者 Jinyang Fu Jilin He 《Computers, Materials & Continua》 SCIE EI 2024年第4期1679-1703,共25页
The detection of crack defects on the walls of road tunnels is a crucial step in the process of ensuring travel safetyand performing routine tunnel maintenance. The automatic and accurate detection of cracks on the su... The detection of crack defects on the walls of road tunnels is a crucial step in the process of ensuring travel safetyand performing routine tunnel maintenance. The automatic and accurate detection of cracks on the surface of roadtunnels is the key to improving the maintenance efficiency of road tunnels. Machine vision technology combinedwith a deep neural network model is an effective means to realize the localization and identification of crackdefects on the surface of road tunnels.We propose a complete set of automatic inspection methods for identifyingcracks on the walls of road tunnels as a solution to the problem of difficulty in identifying cracks during manualmaintenance. First, a set of equipment applied to the real-time acquisition of high-definition images of walls inroad tunnels is designed. Images of walls in road tunnels are acquired based on the designed equipment, whereimages containing crack defects are manually identified and selected. Subsequently, the training and validationsets used to construct the crack inspection model are obtained based on the acquired images, whereas the regionscontaining cracks and the pixels of the cracks are finely labeled. After that, a crack area sensing module is designedbased on the proposed you only look once version 7 model combined with coordinate attention mechanism (CAYOLOV7) network to locate the crack regions in the road tunnel surface images. Only subimages containingcracks are acquired and sent to the multiscale semantic segmentation module for extraction of the pixels to whichthe cracks belong based on the DeepLab V3+ network. The precision and recall of the crack region localizationon the surface of a road tunnel based on our proposed method are 82.4% and 93.8%, respectively. Moreover, themean intersection over union (MIoU) and pixel accuracy (PA) values for achieving pixel-level detection accuracyare 76.84% and 78.29%, respectively. The experimental results on the dataset show that our proposed two-stagedetection method outperforms other state-of-the-art models in crack region localization and detection. Based onour proposedmethod, the images captured on the surface of a road tunnel can complete crack detection at a speed often frames/second, and the detection accuracy can reach 0.25 mm, which meets the requirements for maintenanceof an actual project. The designed CA-YOLO V7 network enables precise localization of the area to which a crackbelongs in images acquired under different environmental and lighting conditions in road tunnels. The improvedDeepLab V3+ network based on lightweighting is able to extract crack morphology in a given region more quicklywhile maintaining segmentation accuracy. The established model combines defect localization and segmentationmodels for the first time, realizing pixel-level defect localization and extraction on the surface of road tunnelsin complex environments, and is capable of determining the actual size of cracks based on the physical coordinatesystemafter camera calibration. The trainedmodelhas highaccuracy andcanbe extendedandapplied to embeddedcomputing devices for the assessment and repair of damaged areas in different types of road tunnels. 展开更多
关键词 road tunnel crack inspection crack area sensing multiscale semantic segmentation CA-YOLO V7 DeepLab V3+
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The coordinated evolution of ecological environment,public service,and tourism economy along the Silk Road Economic Belt,using the Dual-Carbon Targets
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作者 Shuo Yang Wei Guo +1 位作者 Tianjun Xu Tongtong Liu 《Chinese Journal of Population,Resources and Environment》 2024年第1期34-47,共14页
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 en... 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. 展开更多
关键词 Dual-carbon Ecological environment Public services Tourist economy Silk road Economic Belt
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Research on Developing an Assessment Scale for Tourism Experience Elements of Ancient Shu Road Heritage Trail
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作者 Wang Yuan Wang Bo Zhou Jiang 《Contemporary Social Sciences》 2024年第5期118-142,共25页
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 them... 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. 展开更多
关键词 ancient roads heritage trails tourism experience elements scale development
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Innovation Analysis of Rural Agricultural Economic Management Model in the Context of the Belt and Road Initiative
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作者 Huabin TANG 《Asian Agricultural Research》 2024年第6期11-12,18,共3页
[Objectives]To explore innovative strategies for rural agricultural economic development in the context of the Belt and Road Initiative.[Methods]This research adopts the method of literature review and field research,... [Objectives]To explore innovative strategies for rural agricultural economic development in the context of the Belt and Road Initiative.[Methods]This research adopts the method of literature review and field research,systematically combs the research results related to the Belt and Road Initiative and rural agricultural economic management,and deeply understands the actual situation of rural agricultural economic management.[Results]The research shows that in the context of the Belt and Road Initiative,the rural agricultural economy is facing new development opportunities and challenges,but there are also some problems.In the new period,we should accelerate the innovative development of rural agricultural economy by promoting market-oriented reform,strengthening scientific and technological innovation,optimizing the industrial structure,deepening international cooperation and other measures.The Belt and Road Initiative provides an important opportunity for the innovation of rural agricultural economic management.Rural agricultural economic management should be actively integrated into the Belt and Road construction to improve the level of rural agricultural economic management.[Conclusions]This study provides useful exploration and reference for the innovation of rural agricultural economic management models,which helps to promote the healthy development of rural agricultural economy and achieve the goal of rural revitalization. 展开更多
关键词 The BELT and road INITIATIVE RURAL areas Agriculture ECONOMY ADMINISTRATION
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