Predicting the International Roughness Index of JPCP and CRCP Rigid Pavement:A Random Forest(RF)Model Hybridized with Modified Beetle Antennae Search(MBAS)for Higher Accuracy

To improve the prediction accuracy of the International Roughness Index(IRI)of Jointed PlainConcrete Pavements(JPCP)and Continuously Reinforced Concrete Pavements(CRCP),a machine learning approach is developed in this study for the modelling,combining an improved Beetle Antennae Search(MBAS)algorithm and Random Forest(RF)model.The 10-fold cross-validation was applied to verify the reliability and accuracy of the model proposed in this study.The importance scores of all input variables on the IRI of JPCP and CRCP were analysed as well.The results by the comparative analysis showed the prediction accuracy of the IRI of the newly developed MBAS and RF hybrid machine learning model(RF-MBAS)in this study is higher,indicated by the RMSE and R values of 0.2732 and 0.9476 for the JPCP as well as the RMSE and R values of 0.1863 and 0.9182 for the CRCP.The accuracy of this obtained result far exceeds that of the IRI prediction model used in the traditional Mechanistic-Empirical Pavement Design Guide(MEPDG),indicating the great potential of this developed model.The importance analysis showed that the IRI of JPCP and CRCP was proportional to the corresponding input variables in this study,including the total joint faulting cumulated per KM(TFAULT),percent subgrade material passing the 0.075-mm Sieve(P_(200))and pavement surface area with flexible and rigid patching(all Severities)(PATCH)which scored higher.

Mitigating Urban Heat Island Effects: A Review of Innovative Pavement Technologies and Integrated Solutions

In this review paper,we present a thorough investigation into the role of pavement technologies in advancing urban sustainability.Our analysis traverses the historical evolution of these technologies,meticulously evaluating their socio-economic and environmental impacts,with a particular emphasis on their role in mitigating the urban heat island effect.The evaluation of pavement types and variables influencing pavement performance to be used in the multi-criteria decision-making(MCDM)framework to choose the optimal pavement application are at the heart of our research.Which serves to assess a spectrum of pavement options,revealing insights into the most effective and sustainable practices.By highlighting both the existing challenges and potential innovative solutions within thefield,this paper aims to offer a directional compass for future urban planning and infrastructural advancements.This review not only synthesizes the current state of knowledge but also aims to chart a course for future exploration,emphasizing the critical need for innovative and environmentally sensitive pavement tech-nologies in the creation of resilient and sustainable urban environments.

Intelligent pavement condition survey:Overview of current researches and practices

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.

Condition indices for rigid pavements: A comparative analysis of state DOTs using Michigan PMS data

Pavement infrastructure is vital in providing services and links between various sectors of society. Therefore, thepreservation and maintenance of these roads are critical to attaining a pavement network in good conditionthroughout its service life. Various performance indicators like the international roughness index (IRI), pavementcondition index (PCI), and present serviceability rating (PSR) have been used by the state department of transportation (DOT) and highway agencies for evaluating pavement surface conditions and planning future maintenance strategies. Limited data availability, multiple distresses depending on region, lack of correlation of thesecondition indices to maintenance strategies, and data collection limitations pose a challenge for applying theseindices to local conditions. This paper compares condition indices of different states for rigid pavements. Further,using a specific condition index for local conditions is also highlighted. For this purpose, five states and theircorresponding condition indices were evaluated and compared to the Michigan DOT distress index (DI). Thesestates include Virginia, Minnesota, North Dakota, Louisiana, and Oregon. The corresponding distresses of eachcondition index were converted to make them compatible with the MDOT DI. This study used the MDOT'spavement management system (PMS) database to evaluate each condition index for 433 rigid pavement sections.Each distress index was plotted against MDOT DI and compared using a paired t-test. Results show that thecondition indices of Virginia and Minnesota are comparable to DI in terms of the Spearman correlation value. Thet-test results show that except for Virgina, condition indices from other states statistically differ from DI.Therefore, one can't use those directly for local conditions in Michigan. This paper presents the evaluation anddata requirements for each condition index and its impact on selecting a maintenance treatment.

Review on dynamic analysis of road pavements under moving vehicles and plane strain conditions

This paper reviews works on the dynamic analysis of flexible and rigid pavements under moving vehicles on the basis of continuum-based plane strain models and linear theories.The purpose of this review is to provide in-formation about the existing works on the subject,critically discuss them and make suggestions for further research.The reviewed papers are presented on the basis of the various models for pavement-vehicle systems and the various methods for dynamically analyzing these systems.Flexible pavements are modeled by a homogeneous or layered half-plane with isotropic or anisotropic and linear elastic,viscoelastic or poroelastic material behavior.Rigid pavements are modeled by a beam or plate on a homogeneous or layered half-plane with material properties like the ones for flexible pavements.The vehicles are modeled as concentrated or distributed over a finite area loads moving with constant or time dependent speed.The above pavement-vehicle models are dynamically analyzed by analytical,analytical/numerical or purely numerical methods working in the time or frequency domain.Representative examples are presented to illustrate the models and methods of analysis,demonstrate their merits and assess the effects of the various parameters on pavement response.The paper closes with con-clusions and suggestions for further research in the area.The significance of this research effort has to do with the presentation of the existing literature on the subject in a critical and easy to understand way with the aid of representative examples and the identification of new research areas.

Automatic Pavement Crack Detection Based on Octave Convolution Neural Network with Hierarchical Feature Learning

Automatic pavement crack detection plays an important role in ensuring road safety.In images of cracks,information about the cracks can be conveyed through high-frequency and low-fre-quency signals that focus on fine details and global structures,respectively.The output features obtained from different convolutional layers can be combined to represent information about both high-frequency and low-frequency signals.In this paper,we propose an encoder-decoder framework called octave hierarchical network(Octave-H),which is based on the U-Network(U-Net)architec-ture and utilizes an octave convolutional neural network and a hierarchical feature learning module for performing crack detection.The proposed octave convolution is capable of extracting multi-fre-quency feature maps,capturing both fine details and global cracks.We propose a hierarchical feature learning module that merges multi-frequency-scale feature maps with different levels(high and low)of octave convolutional layers.To verify the superiority of the proposed Octave-H,we employed the CrackForest dataset(CFD)and AigleRN databases to evaluate this method.The experimental results demonstrate that Octave-H outperforms other algorithms with satisfactory performance.

Development and optimization of object detection technology in pavement engineering: A literature review

Due to the rapid advancement of the transportation industry and the continual increase in pavement infrastructure,it is difficult to keep up with the huge road maintenance task by relying only on the traditional manual detection method.Intelligent pavement detection technology with deep learning techniques is available for the research and industry areas by the gradual development of computer vision technology.Due to the different characteristics of pavement distress and the uncertainty of the external environment,this kind of object detection technology for distress classification and location still faces great challenges.This paper discusses the development of object detection technology and analyzes classical convolutional neural network(CNN)architecture.In addition to the one-stage and two-stage object detection frameworks,object detection without anchor frames is introduced,which is divided according to whether the anchor box is used or not.This paper also introduces attention mechanisms based on convolutional neural networks and emphasizes the performance of these mechanisms to further enhance the accuracy of object recognition.Lightweight network architecture is introduced for mobile and industrial deployment.Since stereo cameras and sensors are rapidly developed,a detailed summary of three-dimensional object detection algorithms is also provided.While reviewing the history of the development of object detection,the scope of this review is not only limited to the area of pavement crack detection but also guidance for researchers in related fields is shared.

Flexible pavement longitudinal joint quality evaluation using non-destructive testing

Longitudinal joint construction quality is critical to the life of flexible pavements.Maintaining deteriorated longitudinal joints has become a challenge for many highway agencies.Improving the joint's quality through better compaction during construction can help achieve flexible pavements with longer service lives and less maintenance.Current quality control(QC)and quality assurance(QA)plans provide limited coverage.Consequently,the risk of missing areas with poor joint compaction is significant.A density profiling system(DPS)is a non-destructive alternative to conventional destructive evaluation methods.It can provide quick and continuous real-time coverage of the compaction during construction in dielectrics.The paper presents several case studies comparing various types of longitudinal joints and demonstrating the use of DPS to evaluate the joint's compaction quality.The paper shows that dielectric measurements can provide valuable insight into the ability of various construction techniques to achieve adequate levels of compaction at the longitudinal joint.The paper proposes a dielectric-based longitudinal joint quality index(LJQI)to evaluate the relative compaction of the joint during construction.It also shows that adopting DPS for assessing the compaction of longitudinal joints can minimize the risk of agencies accepting poorly constructed joints,identify locations of poor quality during construction,and achieve better-performing flexible pavements.

Effect of Seasonal Variations on the Behavior of Flexible Pavements in Burkina Faso: Towards Alternating and Periodic Loading of Multi-Axle Heavy Goods Vehicles for Road Durability

Bituminous materials are heat-sensitive, and their mechanical properties vary with temperature. This variation in properties is not without consequences on the performance of flexible road structures under the repeated passage of multi-axles. This study determines the influence of seasonal variations on the rate of permanent deformation, the rut depth of flexible pavements and the effect of alternating loading of heavy goods vehicles following the temperature variations on the durability of roads. Thus, an ambient and pavement surface temperature measurement was carried out in 2022. The temperature profile at different layers of the modelled pavement, the evaluation of deformation rates and rutting depth were determined using several models. The results show that the permanent deformation and rutting rates are higher at the level of the bituminous concrete layer than at the level of the asphalt gravel layer because the stresses decrease from the surface to the depth of the pavement. On the other hand, the variations in these rates, permanent deformations and ruts between the hot and so-called cold periods are more pronounced in the bitumen gravel than in bituminous concrete, showing that gravel bitumen is more sensitive to temperature variations than bituminous concrete despite its higher rigidity. Of these results, we suggested a periodic and alternating loading of the different types of heavy goods vehicles. These loads consist of fully applying the WAEMU standards with a tolerance of 15% during periods of high and low temperatures. This regulation has increased 2 to 3 times in the durability of roadways depending on the type of heavy goods vehicle.

A systematic review of rigid-flexible composite pavement

Rigid-flexible composite pavement has gained significant popularity in recent decades.This paper provides a comprehensive review of the research progress concerning rigid-flexible composite pavement,aiming to promote its application and address key issues while identifying future directions.The design theory and methodology of rigid-flexible composite pavement are discussed,followed by a description of its structural and mechanical behavior characteristics.The load stress,temperature stress,and their interactive effects between the asphalt layer and the rigid base were analyzed.It is clarified that the asphalt layer serves a dual role as both a“functional layer”and a“structural layer”.Typical distresses of rigid-flexible composite pavement,which primarily occur in the asphalt layer,were discussed.These distresses include reflective cracking,top-down cracking,rutting,and compressive-shear failure.Generally,the integrity of the rigid base and the interlaminar bonding conditions significantly impact the performance and distress of the asphalt layer.The technology for enhancing the performance of rigid-flexible composite pavement is summarized in three aspects:asphalt layer properties,rigid base integrity,and interlaminar bonding condition.The study concludes that developing high-performance pavement materials based on their structural behaviors is an effective approach to improve the performance and durability of rigid-flexible composite pavement.The integrated design of structure and materials represents the future direction of road design.

Loading Stress Analysis of Cement Concrete Pavement in Mountainous Areas

The suitable cement concrete pavement for mountainous areas is a form of low-cost cement concrete pavement that uses unconventional graded stones in different proportions in ordinary concrete,allowing the concrete to fully contact the stones and form a stable and well-bonded slab with large particle stones.As large particle stones replace a certain volume of cement concrete,they have good economic performance and are a low-cost form of cement concrete pavement.This study researches the use of ANSYS tools to analyze the influence of geometric dimensions and material properties of rigid pavement structural layers on the mechanical properties of pavement structures.

Analysis of Historic Pavement and Bridge Conditions and Alternative Funding Levels for the Michigan Department of Transportation

In 1997 the Michigan Department of Transportation (MDOT) established an ambitious set of condition targets for its pavements and bridges, and the Department received increased revenue from a 4-cent-per-gallon increase in the state motor fuels tax to help meet its targets. However, over time, actual revenue was less than both what was initially estimated as needed to meet the targets and what was projected from the tax increase. Consequently, actual conditions were projected to fall short of the target levels, so the department issued bonds to address the shortfall through 2012. To support deliberations on future funding, in 2013 MDOT performed an analysis of historic conditions to determine what additional fuel tax revenues would have been required beginning in 1997 to: replace bond revenues used to fund pavement and bridge projects from 1997 to 2012;and enable MDOT to meet its condition targets. The analysis was performed using data on actual pavement and bridge funding and conditions;as well as predicted funding and conditions for different hypothetical increases in fuel taxes. The analysis concluded that, in addition to the actual increase of 4 cents per gallon, a fuel tax increase of another 10 cents per gallon would have been required in 1997 to replace bond revenue used for pavement and bridges and allow MDOT to meet its condition targets. The analysis results were used to help inform the discussion of Michigan’s target asset conditions and funding, and demonstrate application of MDOT’s pavement and bridge management systems for performing historic analyses.

Study on the Construction Technology of Subgrade Pavement in Road and Bridge Settlement Section

With the continuous development of China’s economy,the construction of roads and bridges work has put forward higher requirements.Due to various factors,the long-term use of roads and bridges will produce a settlement phenomenon.Therefore,it is crucial to address settlement issues during the construction of roads and bridges to ensure that the quality of subgrade and pavement construction meets national regulations.This paper introduces the harm of subgrade pavement subsidence,analyzes the causes of subgrade pavement deformation,and discusses the technical points of subgrade pavement construction,hoping to provide some reference for relevant practitioners.

Analysis of Roadbed Pavement Designs for Highway Reconstruction and Upgrading

This paper focuses on the route and roadbed pavement design in highway reconstruction and upgrading projects.It discusses the importance of project design for highway reconstruction and upgrading,highlighting key aspects of route design and roadbed pavement design.The analysis reveals that the main design considerations in these projects include controlling factors of route reconstruction,expansion,and upgrading,as well as route plan design and longitudinal section design combined with roadbed pavement.In roadbed pavement design,it is crucial for designers to thoroughly collect existing data and make reasonable use of the current roadbed and pavement to develop a comprehensive design scheme.This analysis aims to provide a reference for the reasonable design of such projects.

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.

Pavement Cracks Coupled With Shadows:A New Shadow-Crack Dataset and A Shadow-Removal-Oriented Crack Detection Approach

Automatic pavement crack detection is a critical task for maintaining the pavement stability and driving safety.The task is challenging because the shadows on the pavement may have similar intensity with the crack,which interfere with the crack detection performance.Till to the present,there still lacks efficient algorithm models and training datasets to deal with the interference brought by the shadows.To fill in the gap,we made several contributions as follows.First,we proposed a new pavement shadow and crack dataset,which contains a variety of shadow and pavement pixel size combinations.It also covers all common cracks(linear cracks and network cracks),placing higher demands on crack detection methods.Second,we designed a two-step shadow-removal-oriented crack detection approach:SROCD,which improves the performance of the algorithm by first removing the shadow and then detecting it.In addition to shadows,the method can cope with other noise disturbances.Third,we explored the mechanism of how shadows affect crack detection.Based on this mechanism,we propose a data augmentation method based on the difference in brightness values,which can adapt to brightness changes caused by seasonal and weather changes.Finally,we introduced a residual feature augmentation algorithm to detect small cracks that can predict sudden disasters,and the algorithm improves the performance of the model overall.We compare our method with the state-of-the-art methods on existing pavement crack datasets and the shadow-crack dataset,and the experimental results demonstrate the superiority of our method.

Multi-objective optimization in highway pavement maintenance and rehabilitation project selection and scheduling:A state-of-the-art review

The motivation for cost-effective management of highway pavements is evidenced not only by the massive expenditures associated with these activities at a national level but also by the consequences of poor pavement condition on road users.This paper presents a state-of-the-art review of multi-objective optimization(MOO)problems that have been formulated and solution techniques that have been used in selecting and scheduling highway pavement rehabilitation and maintenance activities.First,the paper presents a taxonomy and hierarchy for these activities,the role of funding sources,and levels of jurisdiction.The paper then describes how three different decision mechanisms have been used in past research and practice for project selection and scheduling(historical practices,expert opinion,and explicit mathematical optimization)and identifies the pros and cons of each mechanism.The paper then focuses on the optimization mechanism and presents the types of optimization problems,formulations,and objectives that have been used in the literature.Next,the paper examines various solution algorithms and discusses issues related to their implementation.Finally,the paper identifies some barriers to implementing multi-objective optimization in selecting and scheduling highway pavement rehabilitation and maintenance activities,and makes recommendations to overcome some of these barriers.

Fast prediction of the mechanical response for layered pavement under instantaneous large impact based on random forest regression

The layered pavements usually exhibit complicated mechanical properties with the effect of complex material properties under external environment.In some cases,such as launching missiles or rockets,layered pavements are required to bear large impulse load.However,traditional methods cannot non-destructively and quickly detect the internal structural of pavements.Thus,accurate and fast prediction of the mechanical properties of layered pavements is of great importance and necessity.In recent years,machine learning has shown great superiority in solving nonlinear problems.In this work,we present a method of predicting the maximum deflection and damage factor of layered pavements under instantaneous large impact based on random forest regression with the deflection basin parameters obtained from falling weight deflection testing.The regression coefficient R^(2)of testing datasets are above 0.94 in the process of predicting the elastic moduli of structural layers and mechanical responses,which indicates that the prediction results have great consistency with finite element simulation results.This paper provides a novel method for fast and accurate prediction of pavement mechanical responses under instantaneous large impact load using partial structural parameters of pavements,and has application potential in non-destructive evaluation of pavement structure.

Do aeolian deposits and sand encroachment intensity shape patterns of vegetation diversity and plant functional traits in desert pavements?

The effects of sand encroachment on composition,diversity,and functional patterns of vegetation in drylands are rarely studied,and yet addressing these aspects is important to deepen our understanding of the biodiversity conservation.This study aimed to investigate the effect of sand encroachment on plant functional biodiversity of desert pavements(gravel deserts)in the Sahara Desert of Algeria.Plants were sampled and analyzed in three desert pavements with different levels of sand encroachment(LSE)and quantity of aeolian deposits(low,LLSE;medium,MLSE;and high,HLSE).Within the sample-plot area(100 m^(2)),density of every plant species was identified and total vegetation cover was determined.Plant taxonomic and functional diversity were analyzed and compared between LSE.Result showed that 19 plant species in desert pavements were classified into 18 genera and 13 families.Asteraceae and Poaceae were the most important families.The species Anabasis articulata(Forssk)Moq.characterized LLSE desert pavements with 11 species,whereas Thymelaea microphylla Coss.&Durieu ex Meisn.and Calobota saharae(C&D)Boatwr.&van Wyk were dominant species of desert pavements with MLSE(14 species)and HLSE(10 species),respectively.The highest values of species richness and biodiversity were recorded in desert pavements with MLSE,while low values of these ecological parameters were obtained in desert pavements with HLSE.Desert pavements with LLSE were characterized with the highest values of species abundances.Plant communities were dominated by chamaephytes,anemochorous,arido-active,and competitive stress-tolerant plants.The increase in LSE along the gradient from LLSE to HLSE induced significant changes in plant community variables including decreases in plant density,plant rarity,lifeform composition,morphological type,and aridity adaptation.Desert pavements with HLSE favor the degradation of vegetation and trigger biodiversity erosion.

Improvement of Binocular Reconstruction Algorithm for Measuring 3D Pavement Texture Using a Single Laser Line Scanning Constraint

The dense and accurate measurement of 3D texture is helpful in evaluating the pavement function.To form dense mandatory constraints and improve matching accuracy,the traditional binocular reconstruction technology was improved threefold.First,a single moving laser line was introduced to carry out global scanning constraints on the target,which would well overcome the difficulty of installing and recognizing excessive laser lines.Second,four kinds of improved algorithms,namely,disparity replacement,superposition synthesis,subregion segmentation,and subregion segmentation centroid enhancement,were established based on different constraint mechanism.Last,the improved binocular reconstruction test device was developed to realize the dual functions of 3D texture measurement and precision self-evaluation.Results show that compared with traditional algorithms,the introduction of a single laser line scanning constraint is helpful in improving the measurement’s accuracy.Among various improved algorithms,the improvement effect of the subregion segmentation centroid enhancement method is the best.It has a good effect on both overall measurement and single pointmeasurement,which can be considered to be used in pavement function evaluation.