The price of uncertainty in pavement infrastructure management planning: An integer programming approach

Currently there is a true dichotomy in the pavement maintenance and rehabilitation (M&R) literature. On the one hand, there are integer programming-based models that assume that parameters are deterministically known. On the other extreme, there are stochastic models, with the most popular class being based on the theory of Markov decision processes that are able to account for various sources of uncertainties observed in the real-world. In this paper, we present an integer programming-based alternative to account for these uncertainties. A critical feature of the proposed models is that they provide – a priori – probabilistic guarantees that the prescribed M&R decisions would result in pavement condition scores that are above their critical service levels, using minimal assumptions regarding the sources of uncertainty. By construction of the models, we can easily determine the additional budget requirements when additional sources of uncertainty are considered, starting from a fully deterministic model. We have coined this additional budget requirement the price of uncertainty to distinguish from previous related work where additional budget requirements were studied due to parameter uncertainties in stochastic models. A numerical case study presents valuable insights into the price of uncertainty and shows that it can be large.     

Predicting asphalt pavement crack initiation following rehabilitation treatments

Prolongation of the service life of pavements requires efficient prediction of the performance of their structural condition and particularly the occurrence and propagation of cracking of the asphalt layer. Although pavement performance prediction has been extensively investigated in the past, models for predicting the cracking probability and for quantifying impacts of associated explanatory factors following pavement treatment, have not been adequately investigated in the past. In this paper the probability of alligator crack initiation following pavement treatments is modeled with the use of genetically optimized Neural Networks, The proposed methodological approach represents the actual (observed) relationships between of probability of crack initiation and the various design, traffic and weather factors as well as the different rehabilitation strategies. Data from the Long Term Pavement Performance (LTPP) Data Base and the Specific Pavement Study 5 (SPS-5) are used for model development. Results indicate that the proposed approach results in accurately predicting the probability of crack initiation following treatment; furthermore it provided information on the relationship between external factors and cracking probability that can help pavement managers in developing appropriate rehabilitation strategies.     

A bottom-up solution for the multi-facility optimal pavement resurfacing problem

Transportation infrastructure management has been a subject of growing economic importance in recent years due to the magnitude of agency expenditures. Increasingly sophisticated methods have been developed to model pavement deterioration and solve for optimal management strategies. However, it is unclear whether these more complex methods are providing more useful results. This paper presents a simple approach for optimizing the frequency and intensity of resurfacing for multiple highway facilities. It builds upon existing optimization methods for the single-facility, continuous-state, continuous-time problem and corresponding results, which include a threshold structure for optimal solutions. This threshold structure allows for mathematical simplifications and for a straightforward optimization approach to be applied to the multi-facility case. The approach is bottom-up rather than top-down, preserving facility-specific features to develop informative budget allocation results. Application of the approach in a case study indicates that solutions are likely to be robust to deterioration model uncertainty, which is consistent with previous facility-level findings. In addition, the methodology is shown to be robust to the form of the deterioration model.     

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.     

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.     

冷再生技术在国道324线岑容公路中的应用

目前,冷再生技术广泛用于旧路的维修、改造及升级中。文章结合国道324线岑溪一容县一级公路沥青砼路面大修工程实践,介绍了路面基层冷再生技术及施工工艺。从实施效果来看,冷再生技术有保证质量、施工速度快、工程造价低和节能环保等优点,是一种较实用的公路沥青路面大修养护新的技术。     

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。     

广西天然碎石土路面低造价硬化技术研究

农村公路中大量存在的碎石路面由于缺少胶结材料,路面强度低、结构松散,极大的影响着农村公路的通行能力。文章以广西农村公路砂石路面为依托进行了低造价改造技术的试验研究。通过现场取样和室内、外试验结果分析,提出了适宜于农场公路碎石土路面改造的低造价硬化技术方案     

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.     

Modelling of the pavement acoustic longevity in Hong Kong through machine learning techniques

Traffic noise emission has long been a pervasive environmental and ecological problem, especially in the metropolitan cities with large-scale traffic network and high population density. Low noise road surface (LNRS) has been actively developed and applied as an effective measure to maintain the quieter environment of mobility service system. However, when LNRS is applied for noise abatement, the relationship between the acoustic performance and degradation of pavement has not been fully understood yet. To this end, this study aims to model the acoustic longevity of asphalt pavement as a function of the thickness, binder content, maximum aggregate size, and air void content of the pavement surface, as well as vehicle speed based on the long-term tyre-road noise data collected from 270 asphalt pavement sections in Hong Kong. Two machine learning techniques, namely artificial neural networks (ANN) and support vector machines (SVM), were employed and compared. It was found that both ANN and SVM could successfully model the pavement acoustic performance with acceptable model performance metrics. A case study showed that the ANN model was more aligned with the aging mechanisms of porous road surface, but the SVM model showed better training performance. The predicted acoustic deterioration rates of the porous surface case varied from −0.1 to 0.28 dB(A)/month rather than keeping a constant linear increasing trend, depending on pavement ageing periods and vehicle speed levels. The two-dimension sensitivity analysis (2D-SA) revealed the relative importance of pavement age and vehicle speed in controlling the acoustic performance.     

A multi-year pavement maintenance program using a stochastic simulation-based genetic algorithm approach

The objective of this paper is to introduce a multi-year pavement maintenance programming methodology that can explicitly account for uncertainty in pavement deterioration. This is accomplished with the development of a simulation-based genetic algorithm (GA) approach that is capable of planning the maintenance activities over a multi-year planning period. A stochastic simulation is used to simulate the uncertainty of future pavement conditions based on the calibrated deterioration model while GA is used to handle the combinatorial nature of the network-level pavement maintenance programming. The effects of the uncertainty of pavement deterioration on the maintenance program are investigated using a case study. The results show that programming the maintenance activities using only the expected pavement conditions is likely to underestimate the required maintenance budget and overestimate the performance of pavement network.     

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。     

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.     

水泥稳定碎石冷再生技术在公路路面改造中的应用

文章以国道G324线岑溪至容县（容县段）一级公路路面改造工程为例,总结水泥稳定碎石冷再生施工工艺,分析其应用的经济效益与社会效益,并结合工程应用的效果,评价稳定碎石冷再生技术是一种经济合理的路面改造方式,具有较高的应用价值.     

多孔沥青混合料路面降温机理研究

如何降低路面高温、减少城市热岛效应影响成为了近年来一个较为关注的问题。文章通过分析多孔沥青混凝土路面的热环境,提出多孔沥青混凝土路面的降温原理及方式。     

Risk-based maintenance and rehabilitation decisions for transportation infrastructure networks

A method for determining optimal risk-based maintenance and rehabilitation (M&R) policies for transportation infrastructure is presented. The proposed policies guarantee a certain performance level across the network under a predefined level of risk. The long-term model is formulated in the Markov Decision Process framework with risk-averse actions and transitional probabilities describing the uncertainty in the deterioration process. The well known Conditional Value at Risk (CVaR) is used as the measure of risk. The steady-state risk-averse M&R policies are modeled assuming no budget restriction. To address the short-term resource allocation problem, two linear programming models are presented to generate network-level polices with different objectives. While the proposed methodology is general and can be used with any performance indicator, pavement roughness is used for numerical studies and an analytical expression for computing CVaR is derived.     

Expert systems in pavement management

This paper discusses the potential application of expert systems, a new information technology derived from artificial intelligence research, to pavement management. The principal focus concerns the development of such knowledge-based or expert systems for project-level analysis and design of pavement rehabilitation strategies. Particular emphasis is placed on the needs of locally managed highway systems, although many of the concepts are also more broadly applicable. The paper provides a brief overview of the evolution and application of expert systems. Several major issues in pavement management are discussed which strongly suggest the appropriateness of expert systems approaches. These issues include the role of computerized pavement management systems, the acquisition of pavement performance data and current procedures for pavement structural evaluation and design. Current research on PARADIGM, an integrated set of expert systems for pavement rehabilitation decision-making, is described. Finally, a PARADIGM component system consisting of an operational prototype expert system for pavement surface condition evaluation, is presented as an example.     

基于隧道内部环境的路面性能研究

文章针对隧道内空间、湿度、噪音及水等工作环境特点，分析隧道路面的工作性能和工作机理，提出适用于隧道内部特殊环境的橡胶粉改性水泥路面、露石水泥路面以及沥青铺装路面结构。     

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.     

彩色沥青路面的应用与发展

彩色沥青路面作为功能性路面和景观道路,已引起了人们的广泛关注与重视.文章结合国内外彩色沥青路面的发展现状,介绍了彩色沥青路面的种类、设备、相关指标标准、配合比设计及施工工艺等,指出了彩色沥青路面目前存在的主要问题,为开展相关研究提供参考.