Methodologic Recommendations to Implement Pavement Management Systems and Eco-Sustainable Solutions for Local Road Administrations

Le xington, in central Kentucky, is the second largest city in the state. Local government is by a mayor and council of elected representatives from twelve districts and three at-large representatives. The Department of Public Works headed by a Commissioner, who reports to the mayor and city-county council, administers the streets and roads system. The street and road network in Lexington consists of approximately 720 centerline miles. Approximately 100 miles are rural in nature and 620 miles are urban. Approximately 95 percent are bituminous surfaced roads; a majority of the remainder is constructed of portland cement concrete. Increasing costs for constructing and maintaining the street and road network was a stimulus to implement a systematic pavement and road surface management system. Available alternatives were reviewed, and it was decided to maximize in-house resources of the Lexington-Fayette Urban County Government. Meetings with public works officials were used to establish criteria for implementation of a management program: (a) program for visual condition survey of pavements, (b) procedure(s) to determine structural deficiencies for critical pavements identified in the visual condition survey, and (c) utilization of the above information to estimate rehabilitation strategies and their associated costs. The paper describes and documents three phases of implementation of a pavement and road surface management system. Phase I included development of a system­ wide inventory of pavements and a pavement condition rating system for both flexible and rigid pavements. Phase II dealt with the modifications to a microcomputer program to process pavement condition ratings for ranking pavements on the basis of need and also to estimate pavement maintenance and rehabilitation costs. Phase III included administrative and training activities necessary for implementation of the pavement management program. Training generally addressed three areas: (1) collection of pavement condition and distress information, (2) operation of the microcomputer program for data processing and analyses, and (3) interpretation and utilization of results of the analyses, Finally, the paper describes current research and development relating to refinements and modifications for the Lexington situation.

Pavements constructed for the purpose of meeting the demand of highways which were emerged with the improving technological developments increased. And consequently, more resources were demanded to be directed to pavement maintenance and rehabilitation. Hereby, the concept of pavement management emerged. Although project-level analyses were found adequate previously, network-level evaluations were needed in order to do detailed planning as a result of resource allocation and transfer problems that were emerged later. Therefore, pavement management system has become compulsory for all pavements to be controlled together. In this framework, programming is needed in order to schedule maintenance–rehabilitation and develop costs with respect to budget. In the study carried out, a mode was developed in order to program the routine network maintenance activities in terms of Pavement Maintenance and Management Systems, and it was concluded that this problem can be solved through ant colony, using Visual Basic.

Nine pavement and asset managers from the United States participated in the International Scan on Managing Pavements and Monitoring Performance. The scan team sought input on processes for implementing sustainable performance-based programs; effective communication methods for garnering upper management and legislative support; agency cultures that support performance-based programs; and techniques, tools, analyses, and reporting that support performance-based management. The team traveled to New Zealand, Australia, Sweden, the Netherlands, and England and gathered information from 14 agencies. The agencies selected for consultation had experience with managing their pavement networks under constrained budgets. Although the initial focus of the scan was on pavement management, the team found that some of the agencies conducted pavement management within an asset management framework. The findings are thus equally applicable to assets other than pavements. The key findings are (a) agency culture supports a long-term view toward managing pavements, (b) elected officials understand their responsibilities as stewards of public funds, (c) the road network is managed as a service provided to the traveling public, (d) agency priorities are known and agency personnel are held accountable for their actions, (e) the agencies recognize the importance of building internal capacity and capabilities, and (f) efficiency and value drive program delivery approaches. The scan team selected four implementation strategies for moving scan findings into practice: communicating scan findings, developing guidelines for asset management plans and long-term financial plans, encouraging use of recurring program assessments, and developing agency capabilities in the areas of engineering, contract administration, economics, and accounting.

Being able to undertake more efficient maintenance and renewal planning of road networks has seen a number of pavement management systems (PMS) being developed between the 80s to mid-90s. During the initial years, there was a significant focus on substantiating the need and demonstrating the benefits of using these tools to assist in the investment planning for roads. Today, with substantial experience, and legislative support such as MAP-21 and PASS-55, the use of PMS in the asset management cycle of roads is a given. The challenge these days is to effectively use these tools and ensure robust outcomes are achieved from the overall PMS process. The success of any PMS is determined by a number of factors including having skilled resources, institutional support, and legislative and funding drivers demanding evidence-based forecasted investment needs. Asset managers also realize the importance of having technical robustness in the process to ensure likely outcomes. This paper documents the evolutionary development pathway of the New Zealand PMS that has now been in use across the entire country for more than 18 years. It shows how by always challenging the status quo it has resulted in consistently increasing the overall robustness of the system. In particular, it shows how different validation techniques have been used to improve the practicality and appropriateness of long-term forecasting capabilities.

Nowadays the safety of computer networks becomes more important than other characteristics. The services which are used by a huge number of users entice hacker. Especially, online payment services are often the main target of malicious software. In the article, the computer virus SpyEye spread via Internet resources is considered. The Petri-object model of propagation process is created with the use of Petri-object simulation software written in Java. The model reproduces the events of damaging website, infecting user’s resource, sending information about vulnerabilities and sending personal data. It was suggested that users are connected when they use the same website. The investigation of the spreading time for different kinds of users’ connections topology is presented. It was considered not only well-known star and chain topologies but also their combinations and the topology with random connections. Simulation results confirm the virus spreading time dependence on user’s connections topology.

This paper describes the development of a cracking prediction model for Portuguese conditions which is expected to integrate the Pavement Management System (PMS) of Estradas de Portugal. The World Bank's highway development and management (versions III and 4) and PARIS models are used as reference for the development of a deterministic (mechanistic-empirical) model, using pavement condition data from sections of the main road network. A two-phase distress evolution model is proposed where the initiation of cracking (1st phase) is ruled by a different equation than the progression of cracking (2nd phase). Cracking initiation is predicted on a traffic basis, from the annual traffic load and the structural capacity of the pavement. An absolute model is presented and recommended for the maintenance and rehabilitation (M&R) programming in the long-term and for the analysis of non-cracked segments. Absolute and relative type models were obtained for cracking progression. The relative model shows better agreement to data and is proposed for short- to medium-term analysis on segments with cracking history, while the absolute model is proposed for the M&R programming in the long-term and the analysis of non-cracked segments. Finally, the recommended model is evaluated based on the application to a set of pavement structures defined in the Portuguese pavement design guide.

This study examines the applicability to developing countries of a pavement management system (PMS) with less data (two-point) requirement to complement current practice. Due to limited capacity, many developing countries like Uganda have adopted a PMS after specified intervals regardless of deterioration rate (i.e. time-dependent policy). Maintenance planning based on deterioration rate (i.e. condition-dependent policy), as proposed, would be more ideal because pavement deterioration is stochastic. A PMS was developed using the Markov hazard model and then an empirical study was conducted for surveyed Ugandan national road network comparing both policies considering a basic plan and a fixed budget. A greedy algorithm was used to select sections for repair based on worst condition first (for time-dependent) or fastest deterioration first (for condition-dependent). A shift to the condition-dependent policy increased percentages of network in good and fair condition by 8.6% and 2.5%, respectively, and reduced percentages in poor and bad condition by 8.5% and 2.6%, respectively. Additionally, maintenance plans with and without preventive maintenance were compared considering a fixed budget. Preventive maintenance further increased percentage in good condition by 27.4% and reduced percentages in poor and bad condition by 11.6% and 4.2%, respectively, with a 53.5% reduction in life cycle costs.

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.

National roads are one of the main networks of a country’s transportation system. To maintain the performance level of national roads requires a well-structured pavement management system (PMS). The decision support system (DSS) is inseparable in the modern PMS, which required the development of a new approach for the DSS in support of national road network maintenance. The proposed model integrates data mining (DM) and geographical information system (GIS) to construct a simple DSS. DM is used to developed road maintenance optimization models, and then integrated with DSS with the help of GIS as an interface application. Historical data on the national road network in West Java, Indonesia is used as a case study. Examples show that the proposed model can determine a decision support solution efficiently. In addition, a userfriendly computer interface is developed so that PMS stakeholders can plan pavement maintenance simply and effectively.

Governments are faced with countless challenges to maintain conditions of road networks. This is due to financial and physical resource deficiencies of road authorities. Therefore, low-cost automated systems are sought after to alleviate these issues and deliver adequate road conditions for citizens. There have been several attempts at creating such systems and integrating them within Pavement management systems. This paper utilizes replicable deep learning techniques to carry out hotspot analyses on urban road networks highlighting important pavement distress types and associated severities. Following this, analyses were performed illustrating how the hotspot analysis can be carried out to continuously monitor the structural health of the pavement network. The methodology is applied to a road network in Sicily, Italy where there are numerous roads in need of rehabilitation and repair. Damage detection models were created which accurately highlight the location and a severity assessment. Harmonized distress categories, based on industry standards, are utilized to create practical workflows. This creates a pipeline for future applications of automated pavement distress classification and a platform for an integrated approach towards optimizing urban pavement management systems.

Natural disasters can cause severe damage to infrastructure such as the road network. Currently, a Pavement Management System (PMS) does not incorporate flooding in a Life Cycle Analysis (LCA). A few Road Deterioration (RD) models have addressed flooding, but they have limitations. As a result, there are not any comprehensive RD models that can incorporate flooding in pavement performances. In addition, no optimum life-cycle road maintenance strategy is available. No study investigated the pavement performances because of a loss in Modulus of Resilience (Mr) at granular and subgrade layers during extreme moisture intrusion. The derivation of pre- and post-flood road maintenance strategies and a flood risk assessment should also be incorporated in a PMS.As a case study, this research has considered the January 2011 flood of Queensland, Australia, and has used 34,000 km road database of the Queensland’s main roads authority. The major objectives of this study are to derive: i) network and project level roughness and rutting-based RD models with flooding, ii) pavement performances due to Mr loss at granular and subgrade layers, iii) flood-resilient pavements, iv) optimum road maintenance strategies at without flood, pre- and post-flood scenarios, and v) pavements’ flood risks. The current scope covered the pavements that are affected after a flood, but are not washed away completely and need rehabilitation for structural strengthening.This research has used a probabilistic approach for deriving the RD models, which are valid at both network and project levels. Moreover, the proposed RD models can estimate road deterioration after a flood at different probabilities of flooding.The actual roughness and rutting vs. time data are assessed for the representative road groups or site specific roads to get the transition probability matrices for with and without flooding conditions, which are used in a Monte Carlo simulation. The new RD models show significant pavement deterioration at different probabilities of flooding events. The results are found valid with actual data for about 2 to 3 years after the January 2011 flood. A t-test also supports this match. A pavement’s performance due to Mr losses at granular layers is checked using the two renowned roughness models, which results are found close match with the actual after flood data and RD models.All these results are used estimating pavements flood resilience from three techniques, i.e., i) using the RD modelling results and an indicator of Change in International Roughness Index (∆IRI) in year 1 over the probability of flooding (∆IRI/Pr); ii) with the indicator of ∆IRI in year 1 over Mr loss (∆IRI/MrL); and iii) using the flood-risk consequences. Expectedly, a flood-resilient pavement performed better in the life-cycle.The study has derived optimum pavement maintenance strategies at without flood, pre- and post-flood conditions for the Queensland roads authority as a case-study. About $17.8bn is needed in the next 20 years at normal condition to maintain its flexible and composite roads at 4.0 IRI. The post-flood strategy framework uses the new RD models for predicting after flood deterioration and the Highway Development and Management model (HDM-4) for getting optimum solutions. The unconstrained budget solution requires $49.7bn to keep the network at an excellent condition, while the constrained one provided a reasonable solution with about $26.1bn in life-cycle. The pre-flood maintenance strategy considered an effective approach by upgrading a pavement’s structural strength now with a thin overlay, and then evaluating pavement life-cycle performance if a flood comes in different years for predicting after-flood deterioration using the RD models and selecting cost effective treatments utilising the HDM-4. The total pre-flood strategy cost varied within the range of $37bn to $38bn. Comparing to a post-flood strategy, the pre-flood strategy can maintain the network better and provides positive economic benefits.Finally, the current study aimed to evaluate pavement performances before and after a flood. The roughness vs. time data were used to get a flood and the time gap between two floods was considered as likelihood. Distribution changes of roughness data before and after a flood have been used to calculate flood consequences, and then risk results. The flood consequence and risk results were validated with actual data for two road groups.A road authority can use the RD models for an after flood road deterioration prediction to select appropriate post-flood treatments. Moreover, pavements flood-resilience, life-cycle performances and approaches for the pre- and post-flood strategies may be used for efficiently managing roads with flooding. Any road authority may plan converting flood prone roads into resilience ones for better life-cycle performances. The pavement’s flood resilience has addressed one of the major challenges of climate change and could be used for an innovative pavement design. The research findings are useful for sound strategic planning and sustainable road asset management, as it addresses the impact of flooding events in LCA. All these help in improving a PMS incorporating flooding.

Local road authorities in Belgium manage about 90% of all roads but these municipalities often only dispose of a very limited budget for road maintenance. Preventative maintenance actions have to prevail for optimising the use of the budget. For this, only an objective observation of the current network condition allows decision making and planning of the most cost-effective and technically efficient maintenance works at the right time. In this contribution we present a pavement management system (PMS) for assistance on technically sound decision making that needs very little of the limited financial and human resources of the local authorities. The approach consists of simple tools for the set-up of an inventory, a method and tools for visual inspection at network level, the definition of a “visual index” and the categorisation of the inspected road sections by the use of thresholds, a first straightforward interpretation of maintenance planning for road sections, simple prediction models, and advanced analysis techniques and software for the technical and financial optimisation of road maintenance with long term planning. In the paper we will show that this stepwise approach is feasible and sound, and that it can be applied in an autonomous way by the technical staff of a local authority as well as by service providers. We will discuss the immediate technical benefits (improved network conditions, reduced number of urgent local repairs) and the long term financial benefits. We will describe hurdles, challenges and organisational advantages encountered when introducing this PMS approach.

The use of neural networks (NNs) has increased tremendously in several areas of engineering over the last three decades. This paper is intended to provide a state-of-the-art survey of NN applications in pavement engineering over the last three decades. The reported studies are briefly summarized under eight different categories: (1) prediction of pavement condition and performance, (2) pavement management and maintenance strategies, (3) pavement distress forecasting, (4) structural evaluation of pavement systems, (5) pavement image analysis and classification, (6) pavement materials modeling, and (7) other miscellaneous transportation infrastructure applications. To maintain consistency, the review was primarily based on archival journal publications although novel application-oriented NN implementations published in peer-reviewed conference proceedings and edited books were also considered. Recent publications focusing on the development and use of hybrid neural systems in pavement engineering were also included in the review. The increasing number of publications in this area of research in combination with other soft computing techniques every year definitely indicates that more and more students, researchers, and practitioners are interested in exploring the use of NNs in the study of pavement engineering problems.

Long-reach passive optical network (LR-PON) is a cost-effective solution for providing broadband access spanning large areas. LR-PON extends the coverage span of PONs from the traditional 20 km range to 100 km and consolidates the multiple optical line terminals (OLTs) and central offices, thus reducing the operational cost and serving many more users. There are two type of LR-PONs: “tree-and-branch” and “ring-and-spur” LR-PON. To “green” the LR-PON and make it energy-efficient, we study a network planning approach based on user behaviors. By considering the different network usage behaviors of different kind of users (i.e., daily bandwidth demand profiles), we can assign users (e.g., business and residential users) efficiently to different wavelengths in “tree-and-branch” or “ring-and-spur” LR-PONs at networking planning stage and achieve high network utilization at all times. Heuristic searches can provide such assignments and their approximate solutions are very close to the lower bound. The behavior-aware user assignment achieves significant improvement over the traditional method in terms of used wavelengths and could thus saves the energy consumed by the LR-PON.

This study mainly aimed at assessing asphalt road pavement rehabilitation and maintenance practices in West Showa Zone with particular reference to the roads from Ambo to Gedo which covers over 64kms. The study aimed at identifying pavement distresses and causes of pavement distresses. According to data collection and analysis, it was found that the material properties and composition (28.1%), construction quality (18.8%), and road maintenance standards (15.6%) were perceived to be the major causes of pavement distresses on the roadway under study. On the other hand, the result of survey condition data obtained from ERA was analyzed and major distresses were identified including longitudinal joint crack, bleeding and tripping, potholes, generalized marked fretting, deformation, subsidence, rutting, patch, wide block crack, isolated scabbing, low shoulder and wheel path rutting. Besides, limited skilled man power (x=3.78), lack of appropriate pavement management system (x =3.93), budget constraint (x=4.43), absence of appropriate machineries (x=3.53), and lack of monitory and quality control (x=3.75) were among the major challenges related to effective pavement work, road maintenance and rehabilitation practices on the roadway under study.