Automated pavement condition survey is of critical importance to road network management.There are three primary tasks involved in pavement condition surveys,namely data collection,data processing and condition evalua...Automated pavement condition survey is of critical importance to road network management.There are three primary tasks involved in pavement condition surveys,namely data collection,data processing and condition evaluation.Artificial intelligence(AI)has achieved many breakthroughs in almost every aspect of modern technology over the past decade,and undoubtedly offers a more robust approach to automated pavement condition survey.This article aims to provide a comprehensive review on data collection systems,data processing algorithms and condition evaluation methods proposed between 2010 and 2023 for intelligent pavement condition survey.In particular,the data collection system includes AI-driven hardware devices and automated pavement data collection vehicles.The AI-driven hardware devices including right-of-way(ROW)cameras,ground penetrating radar(GPR)devices,light detection and ranging(LiDAR)devices,and advanced laser imaging systems,etc.These different hardware components can be selectively mounted on a vehicle to simultaneously collect multimedia information about the pavement.In addition,this article pays close attention to the application of artificial intelligence methods in detecting pavement distresses,measuring pavement roughness,identifying pavement rutting,analyzing skid resistance and evaluating structural strength of pavements.Based upon the analysis of a variety of the state-of-the-art artificial intelligence methodologies,remaining challenges and future needs with respect to intelligent pavement condition survey are discussed eventually.展开更多
When filling embankment dams in cold regions,engineers must solve two freeze–thaw cycle(FTC)-induced soil problems.First,compacted soil constituting the dam is subjected to the FTC during dam construction.Second,loos...When filling embankment dams in cold regions,engineers must solve two freeze–thaw cycle(FTC)-induced soil problems.First,compacted soil constituting the dam is subjected to the FTC during dam construction.Second,loose soil material(LSM),which is subjected to the FTC,fills the dam.To investigate the effects of the aforementioned two problems on the hydraulic conductivity of compacted clayey soil,a series of permeation tests on clayey soil compacted before and after FTC were conducted in this study.The results showed that for the first problem,the hydraulic conductivity of compacted clayey soil subjected to one FTC significantly increases by two to three orders of magnitude because FTC-induced cracks can cause preferential flow in the permeation process.For the second problem,when the FTC number is less than a critical number,the FTC of the LSM may result in the development of united soil particles,thereby increasing the effective porosity ratio and hydraulic conductivity of the compacted soil.It was discovered that the hydraulic conductivity of compacted soil can increase by one to three times when the LSM is subjected to 10 FTCs.When the FTC number exceeds a critical number,the effective porosity ratio and hydraulic conductivity of the compacted soil may decrease with the FTC of the LSM.This should be investigated in future studies,and the results can be used to improve engineering management processes when filling embankment dams during winter in cold regions.展开更多
Over the course of storm or rainfall event,water thickness builds up on road surface resulting in a loss of contact between vehicle tires and road surface and puts drivers into immediate danger especially at high spee...Over the course of storm or rainfall event,water thickness builds up on road surface resulting in a loss of contact between vehicle tires and road surface and puts drivers into immediate danger especially at high speeds.Therefore this is a considerably dangerous condition of the road and the realistic measurements and prediction model of water film thickness(WFT)on pavement surface is crucial for determining the road friction coefficient and evaluating the impact of rainfall on traffic safety.A review of the principle as well as critical evaluation of current detection methods of pavement WFT were compared for consistency and accuracy in this paper.The method selection guidelines are given for different road surface water film thickness detection requirements.This paper also introduces the latest development of WFT detection and prediction models for asphalt pavement,and gives the calculation elements and conditions of different WFT prediction models from different modeling ideas,which provides a basis for the selection and optimization of WFT models for future researchers.This article also suggests a few insights as further research directions on this topic.(1)The research can consider the influencing factors of WFT to conduct research on the delineation standard of pavement WFT.(2)In order to meet the future traffic safety dynamic early warning needs,road factors of different material types,disease conditions and linear conditions should be studied,as well as a comprehensive and accurate real-time water film thickness detection and evaluation method considering meteorological factors of rainfall timing,scale and intensity.(3)The prediction model of WFT should be further studied by the analytical method to clarify the influence of the pavement WFT on the driving safety.展开更多
基金the National Natural Science Foundation of China(grant no.51208419).
文摘Automated pavement condition survey is of critical importance to road network management.There are three primary tasks involved in pavement condition surveys,namely data collection,data processing and condition evaluation.Artificial intelligence(AI)has achieved many breakthroughs in almost every aspect of modern technology over the past decade,and undoubtedly offers a more robust approach to automated pavement condition survey.This article aims to provide a comprehensive review on data collection systems,data processing algorithms and condition evaluation methods proposed between 2010 and 2023 for intelligent pavement condition survey.In particular,the data collection system includes AI-driven hardware devices and automated pavement data collection vehicles.The AI-driven hardware devices including right-of-way(ROW)cameras,ground penetrating radar(GPR)devices,light detection and ranging(LiDAR)devices,and advanced laser imaging systems,etc.These different hardware components can be selectively mounted on a vehicle to simultaneously collect multimedia information about the pavement.In addition,this article pays close attention to the application of artificial intelligence methods in detecting pavement distresses,measuring pavement roughness,identifying pavement rutting,analyzing skid resistance and evaluating structural strength of pavements.Based upon the analysis of a variety of the state-of-the-art artificial intelligence methodologies,remaining challenges and future needs with respect to intelligent pavement condition survey are discussed eventually.
基金supported by the National Natural Science Foundation of China(Grant No.41801039,42071095,41771066)the Second Tibetan Plateau ReferencesScientific Expedition and Research(STEP)program(Grant No.2019QZKK0905)+1 种基金the Science and Technology Project of Gansu Province(Grant No.21JR7RA052)the Science and Technology Project of Yalong River Hydropower Development Company(LHKA-G201906)。
文摘When filling embankment dams in cold regions,engineers must solve two freeze–thaw cycle(FTC)-induced soil problems.First,compacted soil constituting the dam is subjected to the FTC during dam construction.Second,loose soil material(LSM),which is subjected to the FTC,fills the dam.To investigate the effects of the aforementioned two problems on the hydraulic conductivity of compacted clayey soil,a series of permeation tests on clayey soil compacted before and after FTC were conducted in this study.The results showed that for the first problem,the hydraulic conductivity of compacted clayey soil subjected to one FTC significantly increases by two to three orders of magnitude because FTC-induced cracks can cause preferential flow in the permeation process.For the second problem,when the FTC number is less than a critical number,the FTC of the LSM may result in the development of united soil particles,thereby increasing the effective porosity ratio and hydraulic conductivity of the compacted soil.It was discovered that the hydraulic conductivity of compacted soil can increase by one to three times when the LSM is subjected to 10 FTCs.When the FTC number exceeds a critical number,the effective porosity ratio and hydraulic conductivity of the compacted soil may decrease with the FTC of the LSM.This should be investigated in future studies,and the results can be used to improve engineering management processes when filling embankment dams during winter in cold regions.
基金This research is supported by the National Key Research and Development Program of China(No.2021YFB2601000)the National Natural Science Foundation of China(NSFC)(No.51878063 and No.52008029)the Fundamental Research Funds for the Central Universities,CHD(300102213504).
文摘Over the course of storm or rainfall event,water thickness builds up on road surface resulting in a loss of contact between vehicle tires and road surface and puts drivers into immediate danger especially at high speeds.Therefore this is a considerably dangerous condition of the road and the realistic measurements and prediction model of water film thickness(WFT)on pavement surface is crucial for determining the road friction coefficient and evaluating the impact of rainfall on traffic safety.A review of the principle as well as critical evaluation of current detection methods of pavement WFT were compared for consistency and accuracy in this paper.The method selection guidelines are given for different road surface water film thickness detection requirements.This paper also introduces the latest development of WFT detection and prediction models for asphalt pavement,and gives the calculation elements and conditions of different WFT prediction models from different modeling ideas,which provides a basis for the selection and optimization of WFT models for future researchers.This article also suggests a few insights as further research directions on this topic.(1)The research can consider the influencing factors of WFT to conduct research on the delineation standard of pavement WFT.(2)In order to meet the future traffic safety dynamic early warning needs,road factors of different material types,disease conditions and linear conditions should be studied,as well as a comprehensive and accurate real-time water film thickness detection and evaluation method considering meteorological factors of rainfall timing,scale and intensity.(3)The prediction model of WFT should be further studied by the analytical method to clarify the influence of the pavement WFT on the driving safety.
