Pavement Maintenance Programming Research Articles

The effects of subsidy policy on sustainable pavement maintenance programming

ABSTRACT This study aimed to develop a framework for the assessment of the effect of subsidy policy on pavement maintenance programming using the HDM-4 tool. In this study, the financial and economic analyses were performed for four maintenance activities including routine maintenance, 50 mm overlay, microsurfacing, and crack sealing + patching +50 mm overlay. The results showed that maintenance activity type was more effective in comparison with the intervention level in optimum maintenance programming based on user cost. In other words, in terms of economic analysis, the amount of subsidy cost of each maintenance activity had an impact on their priority on the maintenance program. Also, results indicated that the subsidy policy decreases the role of the maintenance program and intervention level in the minimisation of user cost.

Pavement Maintenance Program at the Network Level: Mixed-Integer Programming with Multiple Objectives

Pavement network conditions deteriorate over the years of use. To keep pavement conditions at acceptable levels, highway agencies plan pavement maintenance and rehabilitation (M&R) programs and perform accordingly. Highway agencies usually face budget variability for pavement M&R activities because of limited resources, economic conditions, and changes in policies. The situation makes it difficult for highway agencies to keep an acceptable pavement condition at the network level. Therefore, it is important for highway agencies to adopt M&R policies that can maximize the network condition as well as handle the deviation of the network condition considering the available maintenance funds. In this paper, a multi-period multi-objective linear integer programming model is proposed. Two objectives, maximization of the average network condition and minimization of deviation of the network condition from an idealized network condition trend, are considered in the formulation. The model is formulated for fixed M&R budgets, as well as for variable M&R budgets. The proposed model provides an M&R program for the pavement network that helps decision makers to manage pavement maintenance programs considering budgetary constraints. A case study examining a network of 45 pavement sections is conducted. The solutions of the fixed-budget and variable-budget model are presented. In addition, the values of the system to the decision maker are discussed. Results show that the proposed model is an attractive way to manage pavement maintenance programs at the network level.

Methods and factors of prioritizing roads for maintenance: a review for sustainable flexible pavement maintenance program

Methods and factors of prioritizing roads for maintenance: a review for sustainable flexible pavement maintenance program

PROBABILISTIC MODEL FOR PREDICTION OF INTERNATIONAL ROUGHNESS INDEX BASED ON MONTE CARLO

The IRI International Regularity Index is a performance indicator that evaluates the functional condition of a pavement structure. Its value is a key input for the management of road assets, allowing to establish the opportune moment for carrying out interventions on the pavement. In addition, it is used to receive road surfaces, assess vehicle operating costs, evaluate the profitability of road projects and establish the cash flow in the financial administration of the project. The IRI data obtained from measurements carried out in the field, feed the deterministic deterioration model that allows future estimations of the indicator and the development of pavement maintenance programs. This research proposes to evaluate in a probabilistic way the model of the IRI International Regularity Index of the HDM-4 program, by assigning probability density functions to the input variables from real data taken in the field. To achieve this objective, a Montecarlo-type simulation model was developed, where roads must be classified by their geographical location, structural capacity of the pavement and traffic intensity expressed in Number of Equivalent Axes. The research results provide the IRI characterized by probability density functions, allowing its estimation from an expected reliability value.

Predicting International Roughness Index Based on Surface Distresses in Various Climate and Traffic Conditions Using Laser Crack Measurement System

Roughness is one of the most significant parameters in the evaluation of pavement performance. Surface distresses are among the main factors leading to roughness. The collection and evaluation of roughness data require the application of modern equipment such as road surface profilers. In the absence of such equipment, roughness prediction models that are based on surface distresses might provide a desirable assessment of pavement conditions. This research employs the laser crack measurement system (LCMS) to detect and measure surface distresses and roughness along 268 km of primary roads in Iran. Compared with manual survey, LCMS provides maximum detection and measurement accuracy. Based on the LCMS output, distresses with a higher correlation with the International Roughness Index (IRI) were selected as predictors in linear regression models and artificial neural networks (ANN). The models were developed for 10 m and 100 m length sections of the roads under different climate and traffic conditions. The results indicate that the performance of ANN for the 100 m sections with coefficient of determination ( R2) of 0.82 is superior to other models. The best case was that of using ANN in 100 m sections for regions with moderate climate and medium traffic levels, with a 0.94 correlation. Satisfactory results in field validation of the models demonstrated that agencies can use other methods of data collection (e.g., manual, right of way [ROW]) to assess the surface distresses and roughness condition of their roads from the developed models with minimum spending and without expensive equipment. Such estimates can be employed to make informed decisions in pavement maintenance programs at the network level.

An integer linear programming approach for pavement maintenance and rehabilitation optimization

ABSTRACT A highway in poor conditions can raise transportation costs. Due to budgetary constraints, pavement maintenance programming is considered a difficult decision-making problem. In this article we propose a novel mathematical model and a different variant of the pavement maintenance management problem, solved with integer linear programming. The novelty of this approach is the use of the Pavement Surface Rating as the condition indicator, along with a proposed conversion strategy between most used performance indices. Additionally, we propose a simpler and broader deterioration model, when compared to existent ones, using a table system. This renders the model to be solved easily, allowing it to be implemented worldwide, given its generic characteristics. Many computational experiments were performed, both on artificial benchmark instances and on a real-world case study. The proposed model is shown to obtain optimal solutions in short computational times, and it is able to solve much larger instances than the ones found in the literature. Optimal solutions from benchmark instances, consisting of 5,000 segments and an analysis period of 30 years, were found in less than 45 minutes. Additionally, the optimal solutions have a difference of more than 20% in average, when compared to a greedy algorithm.

A Binary Cuckoo Search for Combinatorial Optimization in Multiyear Pavement Maintenance Programs

For the optimization analysis of pavement maintenance programs, combinatorial optimization is a pervasive problem. Genetic algorithms (GAs) are widely used to solve combinatorial optimization problems in pavement maintenance programs. However, owing to the stochastic search mechanisms underlying GAs, they are more likely to produce a relatively unsatisfactory solution due to premature convergence. Hence, a binary cuckoo search (BCS) algorithm was implemented to solve the optimization problem. To the best of our knowledge, this is the first time that a BCS algorithm has been applied to pavement maintenance management system. Three hypothetical cases are used to investigate and demonstrate the effectiveness of the BCS algorithm, in which uncertainty‐based performance degradation is considered. The results of a comparison between GA and BCS clearly justify the advantages of the search paths underlying the BCS in alleviating premature convergence. Therefore, the BCS algorithm can help decision makers to make more appropriate trade‐off decisions for pavement maintenance programs.

A constraint-based, efficiency optimisation approach to network-level pavement maintenance management

Network-level pavement maintenance programming is characterised by its high computational complexity. In this article, a novel modelling to solve this problem efficiently is proposed. In this modelling, careful care has been taken to reduce the search space and formulate the original problem as one of the well-known problems of the literature on mathematical optimisation. Efficient algorithms can therefore be used to find a solution. According to this approach, the maintenance programming problem is divided into two sub-problems: (i) the first performs a reduction of the search space by filtering road section maintenance alternatives based on technical criteria; (ii) the second computes a road network-level maintenance program by optimising efficiency subject to budget constraints. The section-level filtering of alternatives is modelled as a constraint satisfaction problem and solved using appropriate constraint satisfaction algorithms. The network-level maintenance programming is modelled as a generalised assignment problem, whose resolution is well documented in the literature on optimisation. This approach has shown to be very effective, with strong computational performances for different road network sizes.

Comparison of Field Performance of Crack Treatment Methods in Asphalt Pavement of Texas

AbstractCrack sealing and crack filling treatments have always been an important consideration to prolong the life of pavement among all pavement maintenance programs. Crack sealing uses a router t...

Quantifying the environmental impacts of crack sealing and filling treatment in hot mix asphalt pavement

Crack sealing and filling treatments have always been an important consideration in order to prolong the life of pavement among all the pavement maintenance programs. Crack sealing uses a router to cut the crack to provide a uniform rectangular reservoir for greater penetration of sealants in order to have good bonding whereas crack filling is simply inserting sealant without performing any modification to the crack walls. This research study is intended to compare the initial and long-term environmental burdens between crack sealing and filling treatment. The parameters related to the field implementation of crack treatment methods (length sealed per day, amount of materials, configuration techniques, and equipment data) were collected from the Abilene district database system and the inventory loadings were gathered from the industry and the literature. Each life cycle phase of crack filling and sealing treatment was quantified in eight impact categories in terms of environmental emissions. In general the results of this study indicated that the initial environmental emissions of crack sealing treatment are very high compared to filling technique. However, this environmental burdens can be compensated along with an approximately 25% reduction in emissions by implementing crack sealing treatment over a long period.

Towards a sustainable optimization of pavement maintenance programs under budgetary restrictions

Transport sector constitutes the second largest source of global greenhouse gas (GHG) emissions, being the road transportation the main contributor of these emissions. Efforts in the road sector have traditionally focused on vehicle emissions and infrastructure is typically not included in the emissions account. Road environmental impact is estimated to increase by 10% if the stages of road design, construction, and operation were considered. Previous literature has widely study sustainable practices in pavement design and construction, with little attention paid to maintenance. Current state of practice reveals that pavement managers barely consider environmental performance and their evaluations solely rely on technical and economic criteria. This situation creates the need to incorporate, in an integrated manner, technical, economic, and environmental aspects in the design of maintenance programs. The main objective of this research is to develop a tool for the optimal design of sustainable maintenance programs. Given a maintenance budget, the tool aims to maximize the long-term effectiveness of the network while minimizing GHG emissions derived from the application of maintenance treatments. The capability of the proposed tool is analyzed in a case study dealing with an urban pavement network. In comparison to the traditional maintenance policy, the proposed tool designs maintenance programs that increase the average network condition by up to 22% and reduces GHG emissions by 12%. This application also analyzes the effect of different budgetary scenarios in the technical and environmental performance of the network. This application helps pavement managers in the trade-off between budget and network performance.

Coordination of User and Agency Costs Using Two-Level Approach for Pavement Management Optimization

Pavement maintenance and rehabilitation programming requires the consideration of conflicting objectives to optimize its life-cycle costs. While there are several approaches to solve multiobjective problems for pavement management systems, when user costs or environmental impacts are considered the optimal solutions are often impractical to be accepted by road agencies, given the dominating share of user costs in the total life-cycle costs. This paper presents a two-stage optimization methodology that considers maximization of pavement quality and minimization of agency costs as the objectives to be optimized at the pavement section level, while at the network level, the objectives are to minimize agency and user costs. The main goal of this approach is to provide decision makers with a range of optimal solutions from which a practically implementable one could be selected by the agency. A sensitivity analysis and some trade-off graphics illustrate the importance in balancing all the objectives to obtain reasonable solutions for highway agencies. Multiobjective optimization problems at both levels are solved using genetic algorithms. The results of a case study indicate the applicability of the methodology.

THE EFFECT OF PRESERVATION MAINTENANCE ACTIVITIES IN ASPHALT CONCRETE PAVEMENT SUSTAINABILITY

Pavement infrastructure is crucial to quality lifestyle and affluence of society. Since the pavement structure deteriorates after a while, appropriate pavement preservation maintenance is essential to attain a superior performing, safety, and economic pavement network for the users. Nowadays, within a modern society resources and budget are restricted that make it necessary for transportation agencies to discover approaches to use the resources to optimize benefits included in daily operation. Simultaneously, focus on the idea of environmental sustainability has increased substantially. Pavement preservation assists environmental sustainability by preserving energy, raw materials, and mitigating greenhouse gases (GHG) by maintaining good roads in the perfect condition. Thereby, a sustainable pavement maintenance program should look into allocating budget and resources to pavement preservation. Various types of pavement preservation treatments use different levels of energy and produce GHG emissions. Preservation treatments considered in this study included thin hot-mix asphalt (HMA) overlay, chip seal, slurry seal and crack seal. This research states the methodology in sustainable pavement preservation maintenance. Its focus is on quantifying and recognizing which of these pavement preservations practices minimize environmental impacts. As the economic is one of the components in triple bottom-line in sustainability, the next step is focusing on cost-benefit of preservation maintenance activity and comparing by rehabilitation activity. This research aims to persuade pavement organization to apply correct perseverance activity on the right time and proper manner to enhance sustainable development.

Flexible pavement maintenance programming considering the minimisation of maintenance and rehabilitation costs and the maximisation of the residual value of pavements

This article presents the development and implementation of a multi-objective decision-aid tool (MODAT) which considers different possible goals: minimisation of agency costs; minimisation of user costs; maximisation of the residual value of pavements, etc. The MODAT uses the deterministic pavement performance model used in the AASHTO flexible pavement design method. The application of the new decision-aid tool is illustrated with a case study involving the main road network of Castelo Branco, a district of Portugal. The knee point, which represents the most interesting solution of the Pareto frontier, corresponds to an agency cost weight value of 81% and a weight value of 19% for the residual value of pavements, demonstrating that agency costs, because they are generally much greater than residual value of pavements, dominate the decision process.

Pavement cracking measurements using 3D laser-scan images

Pavement condition surveying is vital for pavement maintenance programs that ensure ride quality and traffic safety. This paper first introduces an automated pavement inspection system which uses a three-dimensional (3D) camera and a structured laser light to acquire dense transverse profiles of a pavement lane surface when it carries a moving vehicle. After the calibration, the 3D system can yield a depth resolution of 0.5 mm and a transverse resolution of 1.56 mm pixel−1 at 1.4 m camera height from the ground. The scanning rate of the camera can be set to its maximum at 5000 lines s−1, allowing the density of scanned profiles to vary with the vehicle's speed. The paper then illustrates the algorithms that utilize 3D information to detect pavement distress, such as transverse, longitudinal and alligator cracking, and presents the field tests on the system's repeatability when scanning a sample pavement in multiple runs at the same vehicle speed, at different vehicle speeds and under different weather conditions. The results show that this dedicated 3D system can capture accurate pavement images that detail surface distress, and obtain consistent crack measurements in repeated tests and under different driving and lighting conditions.

Evaluation of Effects of Priority Preferences on Optimal Resource Allocation in Pavement Management

Certain aspects of prioritization have commonly been employed in the optimum resource allocation program for pavement maintenance management. However, issues associated with incorporating priority preferences into pavement maintenance programming have not been evaluated. For example, application of priority weights to certain problem parameters will affect the optimality of the end solution with respect to the original objective. However, the degree of loss in optimality is related to the form or structure, the magnitudes, and the range of priority weights adopted. Decision makers, who adopt such an approach, are often oblivious to the degree of sub-optimality of the solutions. Therefore, this paper presents a study that examines the implications of applying priority weights, of varying magnitudes and ranges, in the pavement maintenance programming analysis in terms of optimality of the solution/strategy.

Optimisation of maintenance strategy for rural road network using genetic algorithm

The objective of this paper is to develop an optimised maintenance strategy for the rural road network of Kerala state. This is accomplished with the development of a bi-objective deterministic optimisation model which simultaneously satisfies the objectives of both minimisation of total maintenance cost and maximisation of performance of the road network. The model is capable of planning the maintenance activities over a multi-year planning period. The performance of the road network is accounted using the composite index, namely Pavement Condition Index. The constraint-based genetic algorithm was used as the optimisation tool since it very well takes care of the combinatorial nature of the network-level pavement maintenance programming. The applicability of the model is illustrated using a case study for the rural road network of Kerala state in India. The effort made through this research work to develop a suitable Pavement Maintenance and Management System for rural road network can lead to the proper maintenance and upkeep of the rural roads, thereby triggering a positive impact on the Indian economy.

Pavement maintenance programming considering two objectives: maintenance costs and user costs

This paper presents the development and implementation of a Multi-Objective Decision-Aid Tool (MODAT) tested with data from the Estradas de Portugal's Pavement Management System. The MODAT uses a multi-objective deterministic section-linked optimisation model with different possible goals: minimisation of agency costs, minimisation of user costs, maximisation of the residual value of pavements, etc. The MODAT also uses the deterministic pavement performance model used in the AASHTO flexible pavement design method. The application of the new Decision-Aid Tool is illustrated with a case study involving the main road network of Castelo Branco, a district of Portugal. In this application, the Knee point, that represents the most interesting solution of the Pareto frontier, corresponds to an agency costs weight value of 4% and an user costs weight value of 96%, demonstrating that user costs, which are generally much higher than agency costs, dominate the decision process.

Automated Pothole Distress Assessment Using Asphalt Pavement Video Data

Potholes, as a severe type of pavement distress, are currently identified and assessed manually in pavement-maintenance programs. This manual process is time-consuming and labor-intensive. Existing methods for automated pothole detection either rely on expensive and high-maintenance range sensors or make use of acceleration data, which only apply when the pothole is on the tires’ path. The authors’ previous work has proposed and validated a camera-based pothole-detection method. However, this method is limited to single frames and cannot determine the severity of potholes. This paper presents a novel method that addresses these issues by incrementally updating a representative texture template for intact pavement regions and using a vision tracker to reduce the computational effort, improve the detection reliability, and count potholes efficiently. The improved method was implemented and tested on real data. The results indicate a significant capability and performance increase of this method over its predecessor.

Incorporating Priority Preferences into Pavement Maintenance Programming

Traditionally, it has been a common practice to apply priority weights to selected parameters in the process of optimal programming of pavement maintenance. However, there are several issues associated with this approach of incorporating priority preferences into pavement maintenance programming. For instance, applying priority weights to selected problem parameters will lead to a suboptimal solution with respect to the original objective function (such as minimal total maintenance cost or maximum pavement condition). The decision makers may not be aware of this consequence and the magnitude of loss in optimality caused by their choice of priority scheme. This paper proposes an improved methodology of incorporating priority preferences into pavement maintenance programming to overcome these problems. Instead of applying priority weights directly into the mathematical formulation of maintenance programming, priority preferences are handled in two stages of postprocessing of the optimal programming process, namely, a tie-breaking analysis and a trade-off analysis. The optimal programming problem is first solved without applying priority weights to any parameters of the problem. This ensures that the optimality of the solution is not disturbed. In the tie-breaking postprocessing, prioritized maintenance activities are identified to replace lower-priority activities in the solution without affecting the optimality of the solution. Finally, a trade-off analysis is performed to introduce more prioritized activities into the solution on the basis of the willingness of the highway agency to accept some loss in optimality.