Development of distress condition index of asphalt pavements using LTPP data through structural equation modeling

Traditional pavement distress index such as the Pavement Condition Index (PCI) developed by U.S. Army Corps of Engineers determines coefficients of distresses based on subjective ratings. This study proposed an asphalt pavement distress condition index based on various types of distress data collected from the Long-Term Pavement Performance (LTPP) database through Structural Equation Modeling (SEM). The SEM method treated the overall distress index as a latent variable while various distresses were treated as endogenous and other influence factors such as age, layer thickness, material type, weather, environment and traffic, were exogenous observed variables. The SEM method modeled the contributions of various distresses as well as the influence of other factors on the overall pavement distress condition. Influences of age, layer thickness, material type, environment and traffic on the latent distress condition were in accordance with previous studies. Compared with previous attempts to model latent pavement condition index utilizing SEM method, more pavement condition measurements and influencing factors were included. Specifically, this study adopted the robust maximum likelihood estimator (MLR) to estimate parameters for non-normally distributed data and derived the explicit expression of latent variables with intercepts. A multiple regression prediction model was built to calculate an overall condition index utilizing those measured distress data. The established pavement distress index prediction model provided a rational estimation of weighting coefficients for each distress type. The prediction model showed that alligator cracking, longitudinal cracking in wheel path, non-wheel path longitudinal cracking, transverse cracking, block cracking, edge cracking, patch and bleeding were significant for the latent pavement distress index.     

Impact of climate change on pavement structural performance in the United States

This study uses climate projections from multiple models and for different climate regions to investigate how climate change may impact the transportation infrastructure in the United States. Climate data from both an ensemble of 19 different climate models at both RCP8.5 and RCP4.5 as well as three individual prediction models at the same Representative Concentration Pathways (RCP) levels is used. These models are integrated into the AASHTOWare Pavement ME software to predict the pavement performance. Comparisons are made between the predicted performance with respect to typical pavement distresses using both historical climate data as well as climate projection data. Though there is substantial variation for different prediction models in terms of the magnitude of the impact, the consistency in results suggest that projected climate changes are highly likely to result in greater distresses and/or earlier failure of the pavement. This finding is consistent across all the climate zones studied, but varies in magnitude of 2–9% for fatigue cracking and 9–40% for AC rutting at the end of 20 years depending on the climate region of the pavement section and prediction model used. This study also compares the impacts incorporating temperature only projections with temperature and precipitation projections. In this respect, the sections considered in this study do not show any substantial difference in the pavement performance when the precipitation data from the climate predictions are also considered in the climate inputs into AASHTOWare Pavement ME software.     

Investigating effects of asphalt pavement conditions on traffic accidents in Tennessee based on the pavement management system (PMS)

Pavement maintenance is essential for ensuring good riding quality and avoiding traffic congestion, air pollution, and accidents. Improving road safety is one of the most important objectives for pavement management systems. This study utilized the Tennessee Pavement Management System (PMS) and Accident History Database (AHD) to investigate the relationship between accident frequency and pavement distress variables. Focusing on four urban interstates with asphalt pavements, divided median types, and 55 mph speed limits, 21 Negative Binomial Regression models were developed for predicting various types of traffic accident frequencies based on different pavement condition variables, including rut depth (RD), International Roughness Index (IRI), and Present Serviceability Index (PSI). The modeling results indicated that the RD models did not perform well, except for predicting accidents at night and accidents under rain weather conditions; whereas, IRI and PSI were always significant prediction variables in all types of accident models. Comparing the models goodness‐of‐fit results, it was found that the PSI models had a better performance in crash frequency prediction than the RD models and IRI models. This study suggests that the PSI accident prediction models should be considered as a comprehensive approach to integrate the highway safety factors into the pavement management system. Copyright © 2010 John Wiley & Sons, Ltd.     

A competing Markov model for cracking prediction on civil structures

Cracks on the surface of civil structures (e.g. pavement sections, concrete structures) progress in several formations and under different deterioration mechanisms. In monitoring practice, it is often that cracking type with its worst damage level is selected as a representative condition state, while other cracking types and their damage levels are neglected in records, remaining as hidden information. Therefore, the practice in monitoring has a potential to conceal with a bias selection process, which possibly result in not optimal intervention strategies. In overcoming these problems, our paper presents a non-homogeneous Markov hazard model, with competing hazard rates. Cracking condition states are classified in three types (longitudinal crack, horizontal crack, and alligator crack), with three respective damage levels. The dynamic selection of cracking condition states are undergone a competing process of cracking types and damage levels. We apply a numerical solution using Bayesian estimation and Markov Chain Monte Carlo method to solve the problem of high-order integration of complete likelihood function. An empirical study on a data-set of Japanese pavement system is presented to demonstrate the applicability and contribution of the model.     

A joint bottom-up solution methodology for system-level pavement rehabilitation and reconstruction

We present a methodology for the joint optimization of rehabilitation and reconstruction activities for heterogeneous pavement systems under multiple budget constraints. The proposed bottom-up approach adopts an augmented condition state to account for the history-dependent properties of pavement deterioration, and solves for steady-state policies for an infinite horizon. Genetic algorithms (GAs) are implemented in the system-level optimization based on segment-specific optimization results. The complexity of the proposed algorithm is polynomial in the size of the system and the policy-related parameters. We provide graphical presentations of the optimal solutions for various budget situations. As a case study, a subset of California’s highway system is analyzed. The case study results demonstrate the economic benefit of a combined rehabilitation and reconstruction budget compared to separate budgets.     

时间序列法预测沥青路面损坏状况指数研究

由于沥青路面损坏状况影响因素很多,因此要准确预测路面损坏状况较困难。文章采用时间序列法建立预测模型,结合同三高速公路（上海段）路面损坏状况的实测数据进行预测分析。分析结果表明时间序列法具有较高的预测精度和易修正性。     

Joint optimization of freight facility location and pavement infrastructure rehabilitation under network traffic equilibrium

Establishment of industry facilities often induces heavy vehicle traffic that exacerbates congestion and pavement deterioration in the neighboring highway network. While planning facility locations and land use developments, it is important to take into account the routing of freight vehicles, the impact on public traffic, as well as the planning of pavement rehabilitation. This paper presents an integrated facility location model that simultaneously considers traffic routing under congestion and pavement rehabilitation under deterioration. The objective is to minimize the total cost due to facility investment, transportation cost including traffic delay, and pavement life-cycle costs. Building upon analytical results on optimal pavement rehabilitation, the problem is formulated into a bi-level mixed-integer non-linear program (MINLP), with facility location, freight shipment routing and pavement rehabilitation decisions in the upper level and traffic equilibrium in the lower level. This problem is then reformulated into an equivalent single-level MINLP based on Karush–Kuhn–Tucker (KKT) conditions and approximation by piece-wise linear functions. Numerical experiments on hypothetical and empirical network examples are conducted to show performance of the proposed algorithm and to draw managerial insights.     

Co-location decision tree for enhancing decision-making of pavement maintenance and rehabilitation

This paper presents a new decision tree induction method, called co-location-based decision tree (CL-DT), to enhance the decision-making of pavement maintenance and rehabilitation strategies. The proposed algorithm utilizes the co-location characteristics of spatial attribute data in the pavement database. The paper first presented the co-location mining algorithm, including spatial attribute data selection, determination of rough candidate co-locations, determination of candidate co-locations, pruning the non-prevalent co-locations, and induction of co-location rules, and then focused on the development of the co-location decision tree (CL-DT) algorithm, which includes the non-spatial attribute data selection, co-location algorithm modeling, node merging criteria, and co-location decision tree induction. A pavement database covering four counties, which are provided by North Carolina Department of Transportation (NCDOT), is used to verify the proposed method. The experimental results demonstrated that (1) the proposed CL-DT algorithm can make a better decision, and has higher accuracy than the existing decision tree methods do; (2) the training data can be fully played roles in contribution to decision tree induction and the computational time taken for the tree growing, tree drawing and rule generation is largely decreased; (3) quantity and locations of six treatment strategies proposed by the ITRC and by CL-DT is much close for each treatment strategy.     

Evaluating the effects of climate change on road maintenance intervention strategies and Life-Cycle Costs

Climate change has the potential to impact long-term road pavement performance. Consequently, to maintain pavements within the same ranges of serviceability as before, current pavement maintenance strategies need to be re-assessed and, if necessary, changed. Changes in maintenance may lead to different agency costs and user costs as a consequence. This paper commences by defining an assessment procedure, showing how maintenance intervention strategies and Life-Cycle Costs (LCC) may be affected by future climate. A typical Virginia flexible pavement structure and anticipated climate change was used as an example. This example is believed to be representative for a great number of localities in the United States. A method using historical climatic data and climate change projections to predict pavement performance using Mechanistic-Empirical Pavement Design Guide (MEPDG) under current or future climate was introduced. Based on pavement performance prediction, maintenance interventions were planned and optimized. The maintenance effects of three treatments (thin overlay, thin overlay with an intermediate layer, and mill & fill) were considered. A Life-Cycle Cost analysis is reported that used binary non-linear programming to minimize the costs (either agency costs or total costs) by optimizing intervention strategies in terms of type and application time. By these means, the differences in maintenance planning and LCC under current and future climate can be derived. It was found, that for this simplified case study, pavement maintenance and LCC may be affected by climate change Optimized maintenance may improve resilience to climate change in terms of intervention strategy and LCC, compared to responsive maintenance.     

Incorporating socio-political criteria into the maintenance prioritization of Chilean urban pavement networks

Managing urban pavement networks presents additional challenges when compared to the management of interurban pavements. In particular, the prioritization of maintenance activities – which is critical when resources are limited – requires special considerations. Within these considerations, there are socio-political criteria that are not formally considered in current UPMS (Urban Pavement Management Systems). In practice, decision makers consider these socio-political factors but without a formal procedure and proper information, leading to decisions based on subjective information, which lack traceability and reliability.The objective of this study is the identification and formal definition – including the quantification method – of socio-political criteria relevant for the sustainable management of urban pavement networks. The research method included the application of interviews and a survey of experts and practitioners in various agencies involved in the pavement maintenance decision-making process in Chile. As a result of the study, five primary socio-political criteria were identified: neighbors’ perception, proximity to critical infrastructure, benefited population, presence of alternative routes, and strategic selection based on public policy. These criteria were formalized – including how they should be quantified – through an expert panel. A regression analysis applied to various scenarios considered in the survey resulted in the quantification of the relative importance of the formalized socio-political factors to be considered in the decision process, complementing technical and economic criteria. Future research will explore the use of Geographic Information Systems (GIS) to quantify the recommended socio-political factors and implement them in an UPMS.     

沥青路面动力响应分析方法研究

西部交通建设科技项目"沥青路面动力响应分析方法研究"旨在建立车辆-道路系统动力学模型,研究高速重载车辆荷载作用下沥青路面结构的动力响应情况,分析动力载荷对沥青路面结构使用性能的影响,从而提出适合重载交通条件的沥青路面动力响应理论分析方法。本篇对该项目的技术创新点、主要研究成果、社会经济效益及推广应用前景进行了介绍,为今后沥青路面的结构改造与设计提供理论依据。     

温度荷载下沥青路面表面裂缝扩展的数值模拟

文章基于线弹性断裂力学的有限元法,对沥青路面开裂以后的温度应力及裂缝在温度作用下的扩展规律、裂缝尖端的应力强度因子及其与路面温度分布和路面材料特性等参数之间的关系进行了数值分析。结果表明,合理设计沥青面层的厚度和优选温缩性小的路面材料是提高沥青路面抗裂性能的重要方法。     

Incorporating inspection decisions in pavement management

Pavement management systems need to address not only maintenance and rehabilitation (M&R) decisions, but also facility inspection decisions. The state of the art in pavement management is lacking of any consistent methodology for making such decisions on a cost-effectiveness basis. Such a methodology must recognize the presence of interactions between M&R and inspection decisions. These interactions argue for a joint decision-making approach, where the sum of inspection and M&R costs is minimized. This paper reviews different possible mathematical formulations to such a joint decision-making model, having various levels of restriction and computational complexity. These formulations are then compared and the effect of the forecast uncertainty on the minimum expected costs produced by each of them is investigated empirically. It is concluded that optimizing inspection decisions jointly with M&R decisions can lead to substantial cost savings, especially for high precisions of forecasting.     

南钦高速公路改扩建路面改造方案设计

文章基于南钦高速公路原水泥混凝土路面的使用状况及检测评定结果,对南钦高速公路路面病害进行了分析,同时借鉴国内改扩建项目路面工程的设计理念与施工经验,提出了三种新旧路面处理改建方案,并通过比选得出了合理可行的方案。     

移动荷载作用下沥青路面表面裂缝应力强度因子分析

文章结合沥青面层和半刚性基层间的摩擦接触状况，分析沥青路面表面裂缝应力强度因子的变化规律，探讨了不同的面层厚度、不同的面层和基层模量以及不同的裂缝深度对应力强度因子的影响，为改进沥青路面的抗裂设计方法和表面裂缝的养护维修提供理论参考。     

浅议公路路面裂缝的治理措施

文章分析了沥青公路路面出现裂缝的原因,从施工技术、养护管理、材料特征、公路排水性能及路基设计等方面提出了针对性的解决方法及预防路面产生裂缝的具体措施。     

Impact of environmental assessment and budgetary restrictions in pavement maintenance decisions: Application to an urban network

Road agencies are facing the challenges of aging pavements, deteriorating networks, and insufficient maintenance budgets. This study addresses two limitations in the current state of practice in pavement management. First, because the evaluation of maintenance strategies has traditionally focused on economic and technical aspects, it neglects the environmental impact of maintenance decisions. Second, current management systems often provide a unique, optimised pavement maintenance strategy based on a specific objective(s) and constraint(s). The main objective of the study is to analyse the effect of including environmental aspects and funding availability in the design of maintenance strategies. To achieve this objective, the study followed a three-step methodology. First, this study reviews existing practices on pavement maintenance and the criteria considered to trigger the application of maintenance treatments and their effects on pavement condition. Then, maintenance strategies are optimised considering three levels of budgetary capacity and a sustainable evaluation which incorporates technical, economic, and environmental aspects over the pavement lifecycle. Finally, a case study dealing with an urban pavement network in Chile is analysed. Results obtained from this case study show that an increment of 2% in maintenance budget allows to account for more sustainable maintenance decisions, such as cold in-place recycling and full-depth slab repair, whose greenhouse gas emissions are lower than other alternatives. Results also show that functional asphalt overlay and microsurfacing are more recommended in flexible pavements when budgetary restrictions are low, whereas recommended treatments for rigid pavements exhibit small variability with budgetary restrictions.     

新疆公路沥青路面裂缝产生原因及防治措施

文章结合新疆地区的气候特点,分析了新疆公路沥青路面裂缝产生的主要原因,并从设计、施工、材料、社会因素等方面入手提出了相应的裂缝防治措施。     

不同基层类型水泥混凝土路面温度翘曲脱空研究

结合国内相关标准,文章提出了水泥混凝土路面板翘曲脱空检测方法及判定标准,采用以FWD 24 h连续检测后板角板中弯沉值的方法,对广西地区不同基层水泥混凝土路面进行了脱空检测,对比分析了其各自特点和使用性能之间的差异,以及翘曲脱空现象和成因。同时提出了不同基层水泥混凝土路面脱空检测的要求及合理检测时机。     

Quantifying sustainable strategies for the construction of highway pavements in Illinois

The environmental and economic burdens of various pavement construction strategies are evaluated in this study. A partial life-cycle approach was used to determine the environmental and economic benefits of asphalt concrete and Portland concrete mix designs as well as pavement-related pay items. Approximately 920 designs were assessed to determine the upstream energy consumption and global warming potential (GWP) of producing these mixes. In general, it was found that transportation hauling distances as well as asphalt binder type and production imposed the greatest variability on the environmental and economic costs of the mixes. In many cases, these variabilities were seen to reduce some of the benefits from using increased recycled content. A similar analysis was performed for pay items where it was found that the contribution of environmental and economic impacts to a project followed a trend with upper pavement layers having the greatest impact, followed by subsequently lower layers, and finally earth exaction and preparation. A cost effectiveness (CE) analysis was then conducted for 18 sustainable strategies, the majority of which had, on average, cost savings as well as environmental savings for both energy and GWP at the mix design level. Overall, this study systematically used common reference units (i.e., mix designs and pay items) from the industry to assess general trends, inconsistencies, and implications from using sustainable strategies in pavement construction.