Infrastructures in Europe have been affected by impacts of extreme natural events with increasing frequency over the past decades. One of the most recent examples is the flooding that affected parts of Germany in June...Infrastructures in Europe have been affected by impacts of extreme natural events with increasing frequency over the past decades. One of the most recent examples is the flooding that affected parts of Germany in June 2013. Global warming is expected to change patterns of climate-related extreme events affecting infrastructure.This article presents an explanatory approach. Based on an observational design, causal connections between the occurrence and patterns of extreme events and related road infrastructure impacts are analyzed. The hazard mapping case study in the state of Baden-Wrttemberg combines traffic information and data on the June 2013 extreme precipitation in Germany. It examines the precipitation occurrence and road infrastructure impact characteristics in Baden-Wu¨ rttemberg and identifies spatiotemporal hazard patterns. The article suggests further research needs and fields of application for risk mapping in climate change adaptation research in Germany.展开更多
The condition of the road infrastructure has severe impacts on the road safety, driving comfort, and on the rolling resistance. Therefore, the road infrastructure must be moni- tored comprehensively and in regular int...The condition of the road infrastructure has severe impacts on the road safety, driving comfort, and on the rolling resistance. Therefore, the road infrastructure must be moni- tored comprehensively and in regular intervals to identify damaged road segments and road hazards. Methods have been developed to comprehensively and automatically digitize the road infrastructure and estimate the road quality, which are based on vehicle sensors and a supervised machine learning classification. Since different types of vehicles have various suspension systems with different response functions, one classifier cannot be taken over to other vehicles. Usually, a high amount of time is needed to acquire training data for each individual vehicle and classifier. To address this problem, the methods to collect training data automatically for new vehicles based on the comparison of trajectories of untrained and trained vehicles have been developed. The results show that the method based on a k-dimensional tree and Euclidean distance performs best and is robust in transferring the information of the road surface from one vehicle to another. Furthermore, this method offers the possibility to merge the output and road infrastructure information from multiple vehicles to enable a more robust and precise prediction of the ground truth.展开更多
Road infrastructure is facing significant digitalization challenges within the context of new infrastructure construction in China and worldwide.Among the advanced digital technologies,digital twin(DT)has gained promi...Road infrastructure is facing significant digitalization challenges within the context of new infrastructure construction in China and worldwide.Among the advanced digital technologies,digital twin(DT)has gained prominence across various engineering sectors,including the manufacturing and construction industries.Specifically,road engineering has demonstrated a growing interest in DT and has achieved promising results in DT-related applications over the past several years.This paper systematically introduces the development of DT and examines its current state in road engineering by reviewing research articles on DT-enabling technologies,such as model creation,condition sensing,data processing,and interaction,as well as its applications throughout the lifecycle of road infrastructure.The findings indicate that research has primarily focused on data perception and virtual model creation,while realtime data processing and interaction between physical and virtual models remain underexplored.DT in road engineering has been predominantly applied during the operation and maintenance phases,with limited attention given to the construction and demolition phases.Future efforts should focus on establishing uniform standards,developing innovative perception and data interaction techniques,optimizing development costs,and expanding the scope of lifecycle applications to facilitate the digital transformation of road engineering.This review provides a comprehensive overview of state-of-the-art advancements in this field and paves the way for leveraging DT in road infrastructure lifecycle management.展开更多
Infrastructure development within protected areas has become a critical concern in biodiversity conservation,particularly in ecologically sensitive regions like Bantimurung Bulusaraung National Park (TN Babul), Indone...Infrastructure development within protected areas has become a critical concern in biodiversity conservation,particularly in ecologically sensitive regions like Bantimurung Bulusaraung National Park (TN Babul), Indonesia. Thisstudy aims to evaluate the ecological, social, economic, institutional, and infrastructural sustainability of the Maros–Watampone road corridor that crosses TN Babul. Using a qualitative descriptive design, the research employed theMultidimensional Scaling (MDS) method supported by leverage and Monte Carlo analysis. Data were gathered fromkey stakeholders through purposive sampling and analyzed based on sustainability attributes across five dimensions.The findings reveal that environmental, institutional, and infrastructure dimensions scored in the "less sustainable"category, indicating high ecological risk and governance gaps. In contrast, economic and social dimensions weremoderately sustainable, reflecting emerging opportunities for inclusive growth. Sensitive attributes influencingsustainability include habitat fragmentation, road design, governance coordination, and community participation. Thestudy concludes that balancing development with conservation requires integrated, multi-stakeholder strategies andtargeted interventions that address the most vulnerable sustainability dimensions.展开更多
Recently,EY released its report Navigating the Belt and Road:Financial sector paves the way for infrastructure,which raises the fact that with the roll-out of the 'One Belt,One Road' initiative and the impleme...Recently,EY released its report Navigating the Belt and Road:Financial sector paves the way for infrastructure,which raises the fact that with the roll-out of the 'One Belt,One Road' initiative and the implementation of a series of reform measures,Chinese enterprises’outbound investments,led by infrastructure construction,continued its展开更多
This paper presents CW-HRNet,a high-resolution,lightweight crack segmentation network designed to address challenges in complex scenes with slender,deformable,and blurred crack structures.The model incorporates two ke...This paper presents CW-HRNet,a high-resolution,lightweight crack segmentation network designed to address challenges in complex scenes with slender,deformable,and blurred crack structures.The model incorporates two key modules:Constrained Deformable Convolution(CDC),which stabilizes geometric alignment by applying a tanh limiter and learnable scaling factor to the predicted offsets,and the Wavelet Frequency Enhancement Module(WFEM),which decomposes features using Haar wavelets to preserve low-frequency structures while enhancing high-frequency boundaries and textures.Evaluations on the CrackSeg9k benchmark demonstrate CW-HRNet’s superior performance,achieving 82.39%mIoU with only 7.49M parameters and 10.34 GFLOPs,outperforming HrSegNet-B48 by 1.83% in segmentation accuracy with minimal complexity overhead.The model also shows strong cross-dataset generalization,achieving 60.01%mIoU and 66.22%F1 on Asphalt3k without fine-tuning.These results highlight CW-HRNet’s favorable accuracyefficiency trade-off for real-world crack segmentation tasks.展开更多
New roads and infrastructure are driving tourism in China's Xizang Autonomous Region,putting once-remote places in the eastern Himalayas onto the trekking map while benefiting local families.
文摘Infrastructures in Europe have been affected by impacts of extreme natural events with increasing frequency over the past decades. One of the most recent examples is the flooding that affected parts of Germany in June 2013. Global warming is expected to change patterns of climate-related extreme events affecting infrastructure.This article presents an explanatory approach. Based on an observational design, causal connections between the occurrence and patterns of extreme events and related road infrastructure impacts are analyzed. The hazard mapping case study in the state of Baden-Wrttemberg combines traffic information and data on the June 2013 extreme precipitation in Germany. It examines the precipitation occurrence and road infrastructure impact characteristics in Baden-Wu¨ rttemberg and identifies spatiotemporal hazard patterns. The article suggests further research needs and fields of application for risk mapping in climate change adaptation research in Germany.
基金project of Technical Aspects of Monitoring the Acoustic Quality of Infrastructure in Road Transport(3714541000)commissioned by the German Federal Environment Agencyfunded by the Federal Ministry for the Environment,Nature Conservation,Building and Nuclear Safety,Germany,within the Environmental Research Plan 2014.
文摘The condition of the road infrastructure has severe impacts on the road safety, driving comfort, and on the rolling resistance. Therefore, the road infrastructure must be moni- tored comprehensively and in regular intervals to identify damaged road segments and road hazards. Methods have been developed to comprehensively and automatically digitize the road infrastructure and estimate the road quality, which are based on vehicle sensors and a supervised machine learning classification. Since different types of vehicles have various suspension systems with different response functions, one classifier cannot be taken over to other vehicles. Usually, a high amount of time is needed to acquire training data for each individual vehicle and classifier. To address this problem, the methods to collect training data automatically for new vehicles based on the comparison of trajectories of untrained and trained vehicles have been developed. The results show that the method based on a k-dimensional tree and Euclidean distance performs best and is robust in transferring the information of the road surface from one vehicle to another. Furthermore, this method offers the possibility to merge the output and road infrastructure information from multiple vehicles to enable a more robust and precise prediction of the ground truth.
基金supported by the National Key Research and Development Program of China(2022YFB2602103 and 2023YFA1008900)。
文摘Road infrastructure is facing significant digitalization challenges within the context of new infrastructure construction in China and worldwide.Among the advanced digital technologies,digital twin(DT)has gained prominence across various engineering sectors,including the manufacturing and construction industries.Specifically,road engineering has demonstrated a growing interest in DT and has achieved promising results in DT-related applications over the past several years.This paper systematically introduces the development of DT and examines its current state in road engineering by reviewing research articles on DT-enabling technologies,such as model creation,condition sensing,data processing,and interaction,as well as its applications throughout the lifecycle of road infrastructure.The findings indicate that research has primarily focused on data perception and virtual model creation,while realtime data processing and interaction between physical and virtual models remain underexplored.DT in road engineering has been predominantly applied during the operation and maintenance phases,with limited attention given to the construction and demolition phases.Future efforts should focus on establishing uniform standards,developing innovative perception and data interaction techniques,optimizing development costs,and expanding the scope of lifecycle applications to facilitate the digital transformation of road engineering.This review provides a comprehensive overview of state-of-the-art advancements in this field and paves the way for leveraging DT in road infrastructure lifecycle management.
文摘Infrastructure development within protected areas has become a critical concern in biodiversity conservation,particularly in ecologically sensitive regions like Bantimurung Bulusaraung National Park (TN Babul), Indonesia. Thisstudy aims to evaluate the ecological, social, economic, institutional, and infrastructural sustainability of the Maros–Watampone road corridor that crosses TN Babul. Using a qualitative descriptive design, the research employed theMultidimensional Scaling (MDS) method supported by leverage and Monte Carlo analysis. Data were gathered fromkey stakeholders through purposive sampling and analyzed based on sustainability attributes across five dimensions.The findings reveal that environmental, institutional, and infrastructure dimensions scored in the "less sustainable"category, indicating high ecological risk and governance gaps. In contrast, economic and social dimensions weremoderately sustainable, reflecting emerging opportunities for inclusive growth. Sensitive attributes influencingsustainability include habitat fragmentation, road design, governance coordination, and community participation. Thestudy concludes that balancing development with conservation requires integrated, multi-stakeholder strategies andtargeted interventions that address the most vulnerable sustainability dimensions.
文摘Recently,EY released its report Navigating the Belt and Road:Financial sector paves the way for infrastructure,which raises the fact that with the roll-out of the 'One Belt,One Road' initiative and the implementation of a series of reform measures,Chinese enterprises’outbound investments,led by infrastructure construction,continued its
文摘This paper presents CW-HRNet,a high-resolution,lightweight crack segmentation network designed to address challenges in complex scenes with slender,deformable,and blurred crack structures.The model incorporates two key modules:Constrained Deformable Convolution(CDC),which stabilizes geometric alignment by applying a tanh limiter and learnable scaling factor to the predicted offsets,and the Wavelet Frequency Enhancement Module(WFEM),which decomposes features using Haar wavelets to preserve low-frequency structures while enhancing high-frequency boundaries and textures.Evaluations on the CrackSeg9k benchmark demonstrate CW-HRNet’s superior performance,achieving 82.39%mIoU with only 7.49M parameters and 10.34 GFLOPs,outperforming HrSegNet-B48 by 1.83% in segmentation accuracy with minimal complexity overhead.The model also shows strong cross-dataset generalization,achieving 60.01%mIoU and 66.22%F1 on Asphalt3k without fine-tuning.These results highlight CW-HRNet’s favorable accuracyefficiency trade-off for real-world crack segmentation tasks.
文摘New roads and infrastructure are driving tourism in China's Xizang Autonomous Region,putting once-remote places in the eastern Himalayas onto the trekking map while benefiting local families.
