Pavement Maintenance Strategies Research Articles

Game theory–based bilevel model for multiplayer pavement maintenance management

Pavement maintenance is widely thought to be critical for promoting their sustainability. It plays a pivotal role in sustainable and resilient transportation infrastructure for economic development and social inclusion improvement. Existing research mainly focuses on optimizing the maintenance strategies based on one player but ignores the inherent conflicts and complex interactions among multiplayer decision-makers. To address these issues, this research examined the problem of pavement maintenance involving the highway agency and maintenance service providers under the uncertainty of pavement conditions with the aim of optimizing maintenance strategies. A novel bilevel mathematical model was proposed to handle the inherent conflicts and complex interactions among decision-makers based on the Stackelberg game and Nash game. The goal is to obtain the Stackelberg–Nash equilibrium solution, where the highway agency, as the upper-level leader, determines the maintenance tasks, whereas the service providers, as the lower-level followers, provide the corresponding maintenance activities. To formulate this complex model, a bilevel particle swarm optimization (BLPSO) algorithm was developed for pavement maintenance. Finally, a practical case was used to demonstrate the practicality and efficiency of the proposed model. The results show that the mathematical model can provide feasible and effective pavement maintenance strategies for multiplayer decision-makers in real-world applications.

An Overview of Pavement Maintenance Management Strategies in Malaysia

Pavement damages are always associated with its optimum function and considered among the main contributing factors to fatal accident. With significance growth of vehicular road traffic and of accompanying problems of overloading vehicles in Malaysia will indirectly contributed to worsen the condition. Unceasingly, road pavement will experience failures more rapidly than expected hence lead to negative socioeconomic effects. A proper and timely maintenance by road authorities must be made in order to sustain and maintain the roadway condition to keep them serviceable so that it will benefit not only safety but also improve economic growth and social development. Hence, this study was carried out to explore current practise of pavement maintenance strategies in Malaysia. To achieve that objective, a qualitative data of questionnaires distribution to industry practitioners that are involved in managing roads are analyzed to indicate the viability and practicability of pavement maintenance strategies in Malaysia. Other than that, specifics issue pertinent to pavement management also identified. The findings of this study are valuable in developing the realistic performance criteria for seamless road pavement maintenance strategies.

Life-Cycle Cost Analysis (LCCA) comparison of pavements (Flexible, rigid and rigid-admixed with cow bone ASH)

Life Cycle Cost Analysis (LCCA) acts as a decision support tool in economic evaluation of cost (agency and user) during pavement type selection, maintenance and rehabilitation strategy. The Life cycle cost analysis was done using the Present worth of Cost method. Technical Recommendations for Highway (TRH) 12 (pavement rehabilitation investigation and design) analysis was used for calculating the agency cost which entailed the initial rehabilitation, maintenance, future and salvage cost. The LCCA analysis period for this study was taken as 40 years as the analysis period have to be sufficiently long to reflect long-term cost differences associated with reasonable design strategies. The result of the study shows that the present worth cost for the varying Pavement presents the options available for decision making. The result revealed that the initial cost of Rigid pavement is the highest followed by the initial cost of Rigid pavement with 15% CBA while flexible Pavement has the lowest initial cost. However, considering the result showing the present worth cost for the varying pavement types present worth cost of flexible pavement is the highest followed by Rigid pavement and Rigid pavement with 15% CBA has the lowest life cycle cost. The study recommended that Rigid pavement with 15% CBA should be considered because it gives the lowest life cycle cost and the initial cost is relatively low.

AN INTEGRATED MULTI-OBJECTIVES OPTIMIZATION APPROACH ON MODELLING PAVEMENT MAINTENANCE STRATEGIES FOR PAVEMENT SUSTAINABILITY

Addressing the multi-dimensional challenges to promote pavement sustainability requires the development of an optimization approach by simultaneously taking into account future pavement conditions for pavement maintenance with the capability to search and determine optimal pavement maintenance strategies. Thus, this research presents an integrated approach based on the Markov chain and Particle swarm optimization algorithm which aims to consider the predicted pavement condition and optimize the pavement maintenance strategies during operation when applied in the maintenance management of a road pavement section. A case study is conducted for testing the capability of the proposed integrated approach based on two maintenance perspectives. For case 1, maintenance activities mainly occur in TM20, TM31, and TM41, with the maximum maintenance mileage reaching 88.49 miles, 50.89 miles, and 20.91 miles, respectively. For case 2, the largest annual maintenance cost in the first year is $15.16 million with four types of maintenance activities. Thereafter, the maintenance activities are performed at TM10, TM31, and TM41, respectively. The results obtained, compared with the linear program, show the integrated approach is effective and reliable for determining the maintenance strategy that can be employed to promote pavement sustainability.

Prioritization of pavement restoration and maintenance strategies in airports using APMS technique

The airport networks need large amounts of public funds. In addition, the airport network is supported by one of the main economic activities in modern industrial societies: transfer and movement of goods and passengers. Today, the airports need pavement network management and maintenance alone is no longer of any use. The purpose of this study is to provide a method to prioritize restoration and maintenance strategies in the rigid concrete pavement through implementing the Airport Pavement Management System (APMS) technique. In this paper, the Micro PAVER, which is the most comprehensive software in pavement management, is utilized. Furthermore, the prospects of pavement management on the runway pavement of Imam Khomeini airport were investigated by assessing the status of the airport’s rigid concrete pavement and applying different scenarios and procedures of restoration and maintenance. Ultimately, prioritization strategies of restoration and maintenance on the airport’s rigid concrete pavement are proposed.

Long-term performance evaluation of Iowa concrete overlays

ABSTRACT The use of concrete overlays has long been recognised as a cost-effective pavement maintenance and rehabilitation strategy. However, the long-term performance of various types of concrete overlays has not been fully investigated since there has not been enough performance data available to conduct such an evaluation. Concrete overlays have been regularly constructed on Iowa roadways since the late 1970s and many older projects are still in use. Performance-related data for in-service concrete overlays have been acquired from the available resources to evaluate long-term performance of concrete overlays in Iowa. The information collected includes Pavement Condition Index (PCI), International Roughness Index (IRI), overlay type, construction year, overlay thickness, joint spacing, traffic, and other construction and design-related data. Based on an evaluation of PCI and IRI changes during service life, it is observed that concrete overlays can provide at least 20 years of service life. In terms of PCI ratings, 89% of concrete overlays investigated have PCI values greater than 60% as of the time of the analysis. Similarly, 93% of concrete overlays have IRI values lower than 2.7 m/km (170 in/mile). The effects of overlays type and design features on long-term performance of Iowa concrete overlays are also discussed.

ANALYSIS OF THE FLEXIBLE PAVEMENT USING FALLING WEIGHT DEFLECTOMETER FOR INDIAN NATIONAL HIGHWAY ROAD NETWORK

The foremost requirement for developing efficient pavement maintenance and management strategies is to ascertain the properties of the pavement material and its structural capacity. This can be done by studying the response of the pavement to the applied load. In this study, the Falling Weight Deflectometer (FWD) and KGPBACK were used to evaluate the performance of a road section of the National Highway in the state of Haryana in India by studying the deflection in response to the load applied at selected points on the highway. FWD was used to put a dynamic load on existing pavement and the response of the pavement to the load was measured. The deflection values thus obtained were used in the KGPBACK software to determine the elastic moduli of the modelled layers of the pavement. The in-situ elastic moduli obtained were further used in IITPAVE software for overlay design of the pavement. Data obtained from the study was also used as the input parameter in the HDM-4 model to predict the deterioration of the pavement with time due to the prolonged application of traffic loads. The HDM-4 model was also used to check the effect of bituminous overlay maintenance on the distress models and all four distress (cracking, ravelling, rutting and roughness) were found to decrease. Therefore, the study provided in this paper presents a guideline methodology that could be used by administrators in order to estimate when and how much of funding would require to preserve and maintain the Indian Highway road network.

Distress and profile data analysis for condition assessment in pavement management systems

Pavement data collection is the most expensive and time consuming component of Pavement Management System (PMS). Thus, possible methods of minimizing the need of such data might be critical in reducing pavement condition monitoring costs. Also the ability to relate pavement performance prediction models (frequently roughness based) to hot mix asphalt field performance models (distress based) provides valuable conclusions and input in pavement design, performance assessment, maintenance and rehabilitation strategies. Objective of this study was to examine whether specific distresses can influence roadway profile so as to be able to relate the two. The influence of pavement distresses on road profile has been investigated over the years. However, past studies provided conflicting conclusions. Thus, in this study an alternative approach was considered due to the availability of high quality and detailed distress data collected with the Laser Crack Measurement System (LCMS) of the Automatic Road Analyzer, ARAN. As it was expected, specific distresses have higher impact in longitudinal roughness since they are present on the roadway surface at regular intervals (i.e., specific frequencies). For this reason, instead of using summary indexes (i.e., International Roughness Index (IRI), Pavement Condition Index (PCI)), the Power Spectral Density (PSD) of the roadway profile at specific frequency bandwidths was considered along with distresses. The analysis indicated that a specific subset of distresses is affecting roughness at definite wavelength frequencies. Alligator cracking and rutting standard deviation provided the best correlation. IRI was correlated better with distress (e.g. rutting standard deviation) at lower profile frequencies. At high frequency domain (i.e., below 0.8 m wavelengths) better correlation between IRI and high severity cracking was observed through the PSD. Considering multiple frequencies in the regression models between roughness and distresses, the goodness of fit has not necessarily improved. However, the role of different bandwidths was evident. In addition to the specific results, the methodology presented in this study can be used elsewhere to assess potential relations between pavement roughness and distress components.

Bus Ride Index – a refined approach to evaluating road surface irregularities

The road surface quality can be assessed with ride comfort indices because of their strong correlation. Many studies on ride comfort have focused on cars and trucks, but their results are not applicable to buses, which are characterised by inherently different vehicle dynamics. In this study, a quarter-vehicle simulation concept was used to develop a Bus Ride Index (BRI) for evaluating the effect of road irregularities on bus ride comfort. A BRI model was developed to optimise ride comfort depending on seat configuration and air suspension and validated according to technical data. The results show a good regression relationship between BRI and the International Roughness Index (IRI). New IRI thresholds with regard to ride comfort and bus operating speeds were established to serve as a benchmark to develop better pavement maintenance strategies for bus lanes and to estimate road quality based on acceleration data.

Incorporating Dynamic Traffic Distribution into Pavement Maintenance Optimization Model

An optimal pavement maintenance strategy can keep the pavement performance at a high level under budget constraint. However, the impact of changes in traffic distribution caused by maintenance actions on user costs is rarely investigated in existing approaches. This research aims to solve the optimization of pavement maintenance strategy using a multi-stage dynamic programming model combined with the stochastic user equilibrium model, which can simulate the dynamic traffic distribution in the life cycle. To deal with the proposed model, a heuristic iterative algorithm is put forward. Ultimately, a hypothetical network is established to test the model and algorithm. The testing results prove that the proposed framework has an advantage in assessing user costs comprehensively and can provide an effective and optimal pavement maintenance strategy in a 30-year life cycle, which improves the efficiency of budget and pavement conditions. Additionally, this research provides quantitative evidence of interdependency in a road network, i.e., pavement maintenance actions on links can interfere with the user costs and traffic flow distribution in the whole network, which should be taken into account in pavement maintenance decision-making.

Integration of optimization methodology to evaluate pavement maintenance strategies for deteriorated low-volume roads

Low-volume roads (LVRs) are restricted with limited maintenance funding due to the recent national economic downturn. Only few selected LVRs with deteriorated pavements are typically rehabilitated in which poor LVRs are expected to continue deteriorating to extreme levels of distress. Colorado Department of Transportation (CDOT) is evaluating pavement treatments on LVRs to find the most cost-effective maintenance strategies. As part of these efforts, a comprehensive optimization analysis is adopted in this paper to investigate alternative maintenance strategies and define the capital improvement plans for deteriorated LVRs with marginal pavement conditions. A proposed strategy was found to enhance the effectiveness of current policies followed by CDOT. However, the results emphasize the need for additional resources at network level for dealing with deteriorated LVRs. The optimization procedure described in this paper can be followed by other agencies nationwide to identify strategies and establish funding needs that secure higher funding from decision makers.

Assessment of pavement condition index: a case of flexible road pavements on the university of agriculture Makurdi Campus

This study assessed the Pavement Condition Index (PCI) of flexible road pavements on the University of Agriculture Makurdi (UAM) Campus. The ASTM D6433 standard manual for assessing flexible road pavement condition manually was adopted. Analysis of results using descriptive statistics revealed that over 65% of the road pavement on the UAM campus were rated within the range of poor to failed state. Some segments at different routes were rated as fair and above (up to good) conditions, these routes and their corresponding percentages for fair and above conditions included; the Ring Road (RR) at 69.3%, University Entrance Gate - Clinic Junction (GCJ) route at 42.9%, Hostel Junction - Water Works (HJWW) at 33.3%, Clinic Junction - Ring Road Junction (CRRJ) at 26.7%, Staff Quarters Street (SQS) at 25%, South Core Bus Station – Entrance Gate Junction (SCG) at 9.1% and South Core Bus Station - Veterinary Auditorium (SCV) at 0%. The RR route had relatively high percentage of fair to good road pavement segments, while the SCV route had relatively high fraction of pavement with worse condition. Timely and total rehabilitation of flexible road pavement on the UAM campus were recommended since over 65% of the road network is at deplorable state, the prompt rehabilitation of the worse routes such as the SCV and SCG routes (having the least % for fair and above conditions) should be given priority. Also, the patching of potholes at this stage of deterioration is essential to prevent further damages and thereby reducing cost of rehabilitation in the future. Keywords: Flexible road pavement, Pavement Condition Index (PCI), maintenance strategies, pavement rehabilitation, surface distress and University of Agriculture Makurdi

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.

A multi-objective optimisation approach for sustainable pavement management

Addressing the multidimensional challenges involved in advancing the sustainability of pavement systems requires the development of optimisation-based decision support system (DSS) for pavement management with the capability to identify optimally sustainable pavement maintenance and rehabilitations (M&R) strategies. The main objective of this research work is to develop a multi-objective optimisation framework that hosts a comprehensive and integrated pavement life cycle costs–life cycle assessment model that covers the pavement’s whole life cycle, from the extraction and production of materials to construction and maintenance, transportation of materials, work-zone traffic management, usage and end-of-life. The capability of the proposed DSS is analysed in a case study aiming at investigating, from a full life cycle perspective, the extent to which a number of pavement engineering solutions are efficient in improving the environmental and economic aspects of pavement sustainability, when applied in the management of a road pavement section. Multiple bi-objective optimisation analyses considering accordingly agency costs, user costs and greenhouse gas emissions were conducted based on a multi-objective genetic algorithm. Pareto fronts were obtained for each analysis, originating a set of non-dominated maintenance and rehabilitation solutions. Posteriorly, a multi-criteria decision analysis method was used to find the best compromise solution for pavement management.

Mathematical programming framework for modeling and comparing network-level pavement maintenance strategies

This study proposes a mathematical programming framework to model and quantitatively compare different maintenance strategies for network-level highway pavements. The study develops mixed-integer linear programming models for various maintenance strategies that are commonly adopted in practice and in the literature. In developing these models, traffic, pavement age, and maintenance actions with heterogeneous effects are considered. The strategies include optimization-based, worst-first, best-first, and threshold-based strategies. To demonstrate the flexibility of the framework and present a practical situation in which engineering judgment is sometimes incorporated in pavement maintenance strategies, we further develop a mixed strategy. A solution procedure combining the off-shelf mixed-integer programming solver, greedy algorithms, and Lagrangian relaxation algorithms is developed to efficiently solve the models. Finally, a numerical example of a hypothetical network is established. Different maintenance strategies are applied given different budget levels, traffic loadings, and initial pavement conditions. The results of the numerical example are reasonable, and they provide insights into the efficient implementation of maintenance strategies. Results also show that the framework has the potential to aid maintenance agencies in evaluating maintenance strategies before they are implemented, improving pavement conditions, and reducing the budget for transportation infrastructure.

Soft Computing Models to Predict Pavement Roughness: A Comparative Study

Pavement roughness as a critical determinant of public satisfaction can potentially play a major role in road or highway resource allocation to competing pavement resurfacing projects. With this in mind, the aim of the present paper is to develop an accurate model for the prediction of pavement roughness in terms of the International Roughness Index (IRI) using artificial neural networks (ANNs) and support vector machines (SVMs). The modeling is based on pavement roughness data collected periodically for a high‐volume motorway during a seven‐year period, on a yearly basis. The comparative study of the developed models concludes that the performance of the ANN model is slightly better compared to the SVM in terms of prediction accuracy. Further, the analysis results produce evidence in support of the statement that both models are capable to predict accurately pavement roughness; hence, they are deemed useful for supporting decision making of pavement maintenance and rehabilitation strategies.

Investigating influences on the strain : axle load relationship in pavement using Finite Element Modelling

Current pavement maintenance strategies are reliant oninvasive measurements or visual inspection. Fibre-WIM sensors can improve this by measuring strain,which can be used to calculate axle loads. However,this process is not simple. Finite Element Modelling isused to study several circumstantial influences on thestrain – axle load relationship. These factors arecombined into a predicting function, which can berefined so that it can be used to calculate axle loads.This allows for more insight in pavement deterioration.Other than describing the results of the Finite ElementModel, the implications for sustainable pavementmaintenance are discussed.

An innovative Primary Surface Profile-based three-dimensional pavement distress data filtering approach for optical instruments and tilted pavement model-related noise reduction

The automatic pavement management system has the advantage of providing reliable pavement maintenance and rehabilitation strategies aiming at prolonging existing pavement service life. Therefore, the quality of noise reduction results, which is an unavoidable process of automatic pavement assessment evaluation, has a significant influence on the reliability of pavement maintenance operations suggested. The primary purpose of this paper is to propose an innovative three-dimensional (3D) pavement image-based data filtering protocol, thereby maintaining a highly functional pavement surface. First, a 3D pavement depth data collection system was developed using laser light and a charge-coupled device camera. After that, based on the analysis of Positive Noise and Negative Noise, which are optical instrument-related noises, and tilted pavement model noise, the Primary Surface Profile (PSP)-based raw data filtering approach was proposed which aims at improving the noise reduction quality. Validation experiments were conducted using both the proposed approach and the traditional data filtering method, and the results show that for the not tilted pavement surface model, the PSP-based filter method can achieve the highest noise reduction value (NRV), whereas for the tilted pavement surface model, with a slightly lower NRV than that of biphasic standard deviation average filtering, which demonstrates that the proposed data filtering method has self-adaptive and robust data filter advantages which can be incorporated into a high-performance pavement performance evaluation and management system.

An adaptive hybrid genetic algorithm for pavement management

The pavement maintenance and rehabilitation (M&R) strategy selection problem is an exceedingly hard problem to solve optimally. In this paper, a novel Adaptive Hybrid Genetic Algorithm (AHGA) is proposed which incorporates Local Search (LS) techniques into Genetic Algorithms (GA) to improve the overall efficiency and effectiveness of the search. Specifically, it contains two dynamic learning mechanisms to guide and combine the exploration and exploitation search processes adaptively. The first learning mechanism aims to assess the worthiness of conducting an LS reactively and to control the computational resources allocated to the application of this search technique efficiently. The second learning mechanism uses instantaneously learned probabilities to select from a set of pre-defined LS operators which compete against each other for selection which is the most appropriate at any particular stage of the search to take over from the evolutionary-based search process. The new AHGA is compared to a non-hybridized version of the GA by applying the algorithms to several case studies in order to determine the best pavement M&R strategy that minimizes the present value of the total M&R costs. The results show that the proposed AHGA statistically outperforms the traditional GA in terms of efficiency.

Prioritization-Optimization Process Algorithm to Manage Pavement Networks During the Non-Availability of Historical Data

Abstract A common practice followed to rate the pavement surface condition is to use the ASTM D5340-12 procedure and estimate the pavement condition index (PCI) that helps prioritize maintenance needs and assists developing a pavement management system (PMS). However, ASTM-PCI that is dependent on time-based evaluation may not be suitable where there is a lack of historical records and it is being undertaken for the first time. To estimate a pavement's current PCI during the non-availability of historical data and establish a PMS incorporated with prioritized maintenance and optimized budget, a rational engineering criteria (EC) based methodological approach is required that is as robust as ASTM D5340-12. Thus, the objective of this study was to develop a rational EC-based prioritization-optimization process PMS (POPMS) algorithm for a network that prioritizes maintenance strategies for identified pavement distresses and hence optimizes maintenance costs depending on budgetary allocations. An EC-based POPMS algorithm was based on a network length of 100.55 km, which followed prioritization-optimization process for single to multi-year programs. EC-PCI of pavement sections were estimated on the basis of segmented maintenance strategies including preventive and routine maintenance and reconstruction. EC-PCI was found to be rational since three distinct threshold zones were considered that could directly assign pavement maintenance strategies, which was straightforward and circularly referenced. Overall, POPMS algorithm facilitates practitioners to modify the threshold EC-based parameters that will estimate an optimal single/multiyear budget for maintenance as per the newly set threshold level, thus creating a whole new promising approach in the areas of roadway network level maintenance programs.