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Application of Artificial Intelligence for Optimization in Pavement Management

Application of Artificial Intelligence for Optimization in Pavement Management

In 1998, Fwa et al. proposed the GA application to solve the network level pavement management planning by analyzing the time and type of maintenance or rehabilitation for every road section, the resource allocation by time and road section, and the total commitment of resources for each period of time [1]. One year later, Hoque et al. developed an algorithm for optimization of pavement management problems with multiple objectives by using a rank-based fitness alignment and two sets of GA (the simple and improved sets). The algorithms were tested with two objectives: maximizing the maintenance production in work days and minimizing the total maintenance costs. The simulations were also done with two additional objectives, i.e., maximizing the pavement condition and minimizing the total manpower requirements. According to the authors, the improved algorithm performed well for the former two objectives while having a reduced performance for the latter two objectives [9].
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An Energy Saving Pavement Management (ESPM) for Urban Roads in Madhya Pradesh

An Energy Saving Pavement Management (ESPM) for Urban Roads in Madhya Pradesh

The major aim of the study was to build up a pavement management system for Madhya Pradesh road network maintenance to serve as a decision support tool to help out to improve the effectiveness of making decisions, provide feedback as to the consequences of these decisions, make sure uniformity of conclusions made at various levels and get better the efficiency of all decisions in terms of efficiency of results. The specific objectives were to identify the main contributory factors in the road deterioration, use these factors to develop best implementation applications and develop an effective pavement management system to be used as a decision support tool.
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Review of remote sensing methodologies for pavement management and assessment

Review of remote sensing methodologies for pavement management and assessment

One of the most valuable, extensive, and important resources in the US and Europe is their roads. Assess- ment and monitoring is crucial to maintaining a safe and effective road system. There are multiple surface and sub- surface indicators of distress and defects which are observed using traditional, geotechnical engineering methods. While effective, many of these methods can be time consuming, laborious, destructive, costly, and provide information for only limited areas. The use of remote sensing techniques offers new potential for pavement managers to assess large areas, often in little time. Although remote sensing tech- niques can never entirely replace traditional geotechnical methods, they do provide an opportunity to reduce the num- ber or size of areas requiring site visits or manual methods. Employing remote sensing methods to evaluate pavement and transportation networks during and after natural or man- made disasters can also provide comprehensive information for emergency managers.
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Pavement Maintenance and Management of Urban Roads by Using HDM 4

Pavement Maintenance and Management of Urban Roads by Using HDM 4

The “Pavement/asphalt Life Cycle” a categorical depiction of how an asphalt interacts with encompassing systems throughout its life which includes several steps like, material production, pavement design, construction, maintenance and preservation and end of life. The pavement maintenance management system (PMMS) is an effective method for assessment and rating the asphalt condition in chosen sections. The system to perform a cost-effectiveness examination of different maintenance and restoration procedures. At last, the system prioritizes and prescribes asphalt restoration and maintenance to maximize results within a given estimated cost. The system implements illustration or computerized field inspection and evaluation of each street section which is then enter into a database. The information is analyzing using software, and gives recommendation and project future circumstances. The pavement management method generates a wear and tear curve for each section based on input then applied the most cost-effective preservation strategy based on circumstance, outer surface type and functional classification, and available fund.
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Application Of Markovian Probabilistic Process To Develop A Decision Support System For Pavement Maintenance Management

Application Of Markovian Probabilistic Process To Develop A Decision Support System For Pavement Maintenance Management

inclusion of pavement improvement resulting from maintenance and rehabilitation (M&R) actions. Kiyoshi Kobayashi et. al. (2008) reported a Bayesian Estimation Method to improve deterioration prediction for infrastructure system with Markov Chain Model wherein estimates of the deterioration process are based upon empirical judgments of Managers at early stages. Worm J. M. et. al. (1995) has designed a DSS for planning of road maintenance used to solve the maintenance problem within budget restrictions. Carnahan et. al. (1987) developed a procedure for making optimal maintenance decisions for a deteriorating system and a methodology is developed to ensure that pavements meet certain performance criteria while minimizing the expected maintenance cost. Literature review revealed that there are various approaches to develop optimal PMS such as mechanistic approach, empirical formulas, probabilistic approach, but to execute; these are quite lengthy and time consuming. There is fair chance of human errors as it includes lots of field work and manual data entry. Observations of pavement condition vary considerably even when such contributing factors are similar. In Indian scenario, where there are no sophisticated instruments and lack of skilled man power; it is highly difficult to assure the correctness of detailed data required by above mentioned processes or approaches. Here in this paper, the condition states are defined in such a way that it accommodates randomness of all depended variables to be incorporated into a pavement management system.
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Distress Identification, Cost Analysis and Pavement Temperature Prediction for the Long-Term Pavement Performance for Western Australia

Distress Identification, Cost Analysis and Pavement Temperature Prediction for the Long-Term Pavement Performance for Western Australia

Abstract—Collection and analysis of pavement distress data is a significant component for effective long-term pavement performance. Accurate, consistent, and repeatable pavement distress type’s evaluation can reduce a tremendous amount of time and money that has been spending each year on maintenance and rehabilitation of existing pavement distress. The main objective of this study is to identify and quantify of surface distress in a given segment of pavement, to perform details distress rating, to predict pavement temperature and cost analysis of individual pavement distress on heavily urban roads in Western Australia (WA). Field survey were conducted from three regions in WA and two approached were used to evaluate and analysis the pavement distress. First, the probabilistic network Marov-Chain Process method was used to predict the cost analysis for individual asphalt concrete surfaced pavement distress. Second, Statistical Downscaling Model (SDSM) was used to predict pavement temperature for asphalt concrete surface pavement. Meteorological data were collected from Perth, Kalgoorlie, and Albany region in WA, and data were used to develop and validation of the model. Different types of pavement distress level were identified and color photograph illustrated the asphalt concrete surfaced pavement. Results were performed and analysis. Results from this study will be useful resource to Main Roads Western Australia, Western Australia State Highways (WASH), and other pavement related users including to the National Highway System (NHS). In addition, results can be used for pavement management systems (PMSs) purpose.
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Data integration of pavement markings: A case in transportation asset management

Data integration of pavement markings: A case in transportation asset management

CONDITION DECISION TO PERFORM QUERIES AND DEVELOP STRATEGIES Recall that the goal of a TAM system is to provide managers with the best possible condition of the asset, either predicted or measured. The process presented here implements computing tools and enables managers to make decisions based on a state-wide condition assessment that was previously unavailable. With the inclusion of the visual inspection process the decision maker now has a clear and holistic view of the asset. Although not the primary focus of this paper this section summarizes the use of visual inspections and the integrated use of a pavement management system as shown outside the dashed line in Figure 1.
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GIS Based Pavement Maintenance Management Model for Local Roads in the UK

GIS Based Pavement Maintenance Management Model for Local Roads in the UK

The work of Chan et al (2004) seeks to justify the contradictions between jurisdiction levels of pavement management concerning several factors in varying degrees, which can be technical, social, economic, or political in nature. The usual scenario is a central authority that determines a policy that effectively incorporates all jurisdiction networks. In this way, the policy framework established for all network levels to carry out by themselves, constrains decision making within this set of parameters. It could be said that decision making criteria at project level are curtailed by higher management levels, which is observed as a process of succession optimisation. Typically, decision making at each management level is measured independently, thus the limitations at higher management levels are treated as set controls, which includes quality requirements and budget availability. In circumstances where several networks are linked by global funds, it is uncertain that M&R activities reach optimal levels.
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Comparison of Pavement Performance Models for Urban Road Management System

Comparison of Pavement Performance Models for Urban Road Management System

Kirbaş & Karaşahin (2016) used three different modelling approaches: Deterministic Regression, MARS and Artificial Neural Network (ANN) to predict pavement deterioration for urban roads. They used a PCI index to be used in PAVER system – the most commonly used system for pavement management in urban roads. The ANN method was found to be the most appropriate model for predicting deterioration in urban roads. Nevertheless, the three models had prediction accuracy close to each other. Osorio (2015) reached a conclusion that the Urban Pavement Condition Index (UPCI) could be used in many countries if the Urban Road Management System was properly implemented. Three UPCI models were obtained for asphalt pavements with manual and automated data collection.
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Development of An Artificial Neural Network Model for Asphalt Pavement Deterioration Using LTPP Data

Development of An Artificial Neural Network Model for Asphalt Pavement Deterioration Using LTPP Data

The LTPP test sections are classified into a number of studies; General Pavement Studies (GPS) and Specific Pavement Studies (SPS) sections. A GPS test site typically would have one test section, while an SPS test site would have multiple test sections incorporating a controlled set of experiment design and construction features [25]. The data is collected in a consistent manner at a specific level of accuracy and checked through a series of Quality Assurance (QA) criterions. In addition, M&R activities are monitored and recorded, thus addressing some of the possible sources of inconsistencies in historic performance data. Through a pavement management approach, LTPP data can be tailored to fit the structure of a network-level PMS database and used to develop base performance models, which can then be adjusted using local data from individual agencies to model the pavement performance in these agencies [5].
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Determination of a strategic planning approach for maintenance management of a major road network

Determination of a strategic planning approach for maintenance management of a major road network

These components are similar to those previously detailed when describing an asset management system. In the case of pavement management, a considerable part of this strategy could be considered a pavement preservation strategy. According to the Transportation Research Board (2011) pavement preservation is a long term strategy that enhances a pavements performance by using an integrated cost effective set of treatments to extend the pavement’s life. These strategies improve safety and fulfil the expectation of road users. Pavement preservation is based on undertaking the lower cost routine maintenance and periodic maintenance activities rather than letting the pavement deteriorate to unacceptable levels and undertaking more expensive pavement reconstruction. A preventative maintenance treatment is a treatment that is used in a preventative manner and applied to a pavement in good condition (Peshkin & Hoerner 2005). Pavement preservation is based on the philosophy that good roads cost less to maintain resulting in road user costs being minimised (Peshkin & Hoerner 2005).
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Highway Asset Management Framework for Longevity of Infrastructure – A Case Study for China-Pakistan Economic Corridor

Highway Asset Management Framework for Longevity of Infrastructure – A Case Study for China-Pakistan Economic Corridor

Abstract: Pavement management system (PMS) affords objective information and useful data analysis to make consistent, cost-effective, and defensible decisions related to the pavement preservation at network and project level. Pavement functional and structural evaluations using performance indicators such as international roughness index (IRI), surface distress, rutting, deflection data etc. are the key element of PMS. A departure from exiting stand-alone evaluation practices, this research presents project-level functional and structural evaluation and its integration into a PMS framework for more accurate and realistic forecasting of the pavement needs over the analysis period. A case study of an in-service pavement is presented to demonstrate the applicability of proposed framework. Owing to the non-availability of time-series performance data at present, pavement serviceability and structural capacity data before and after of an in-service pavement rehabilitation was explored for overlay treatments (conventional and crumb rubber- modified (CRM) asphalt mixtures) effectiveness analyses. Results of functional evaluation quantified the extent to which CRM improves the functional performance of the pavement, in terms of the drop in IRI. CRM asphalt mixture exhibited relatively superior functional performance in contrast to conventional asphaltic wearing course by a margin of 8% higher drop in IRI, on average. Non-destructive testing technique for pavement structural evaluation using falling weight deflectometer (FWD) data was employed to assess structural capacity of pavements. A computer-aided program was developed for estimation of structure number effective (SNeff) to be used as an input for overlay design using AASHTO empirical method. Moreover, mechanistic-empirical (M-E) design method was employed using evaluation of layer moduli and overlay design (ELMOD) program for overlay thickness design and pavement remaining service life (RSL). Comparison of pre- and post-rehabilitation deflection data endorsed roadbed soil stiffness and structural adequacy. RSL estimated through traffic data (truck load repetitions) validated the results obtained using empirical and M-E methods. Application of KENPAVE program for evaluation of pavement overlay thickness design was also demonstrated by conducting damage analysis. Integrating structural evaluation with functional evaluation into an overall framework of PMS is envisaged to provide systematic and objective procedures for monitoring and evaluating pavement performance, selecting optimal type of treatment and its thickness design.
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OFFLINE HANDWRITTEN SIGNATURE RECOGNITION USING HISTOGRAM ORIENTATION GRADIENT 
AND SUPPORT VECTOR MACHINE

OFFLINE HANDWRITTEN SIGNATURE RECOGNITION USING HISTOGRAM ORIENTATION GRADIENT AND SUPPORT VECTOR MACHINE

Particle Swarm Optimization (PSO) is a very popular technique in swarm intelligence. PSO has been applied to solve many problems that have single or multi-objectives. In fact, the multi-objectives optimization problems in real life are combinatorial in nature. Therefore, PSO has been developed to be able to handle large number of decision variables and reduce computational complexity. In this paper, a chaos multi objective PSO algorithm is developed for solving discrete (binary) optimization problems. The developed algorithm is applied to pavement management problem to find optimal maintenance and rehabilitation plan for flexible pavement with maximum pavement conditions and minimum maintenance cost. The results show that there is significant improvement in the solutions satisfying pavement conditions and maintenance cost objectives. It is required to a very short time of execution by the developed algorithm to reach a very good solution. In addition, it is found that it is able to converge to the solution faster than another PSO algorithm. Keywords: Multi-Objective Optimization, Pavement Maintenance, Particle Swarm Optimization, Chaotic
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Tempus Compendium 1990 91  Task Force: Human Resources Education, Training and Youth

Tempus Compendium 1990 91 Task Force: Human Resources Education, Training and Youth

JEP-1180-90 Title: EDIPAM - Educational developments in pavement management system Subject areas : Applied sciences, technologies and engineering Type of activities : Curriculum developm[r]

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Intelligent Road Inspection with Advanced Machine Learning; Hybrid Prediction Models for Smart Mobility and Transportation Maintenance Systems

Intelligent Road Inspection with Advanced Machine Learning; Hybrid Prediction Models for Smart Mobility and Transportation Maintenance Systems

Pavement maintenance has attracted growing attention of pavement engineers in recent years. Evaluation of pavement conditions is the most important factor for the effective and economical maintenance of the pavement network that can lead to the promotion of service life [3]. The condition of an in-service pavement is assessable in two categories including functional and structural. Both functional and structural conditions play an important role in pavement management at the network- level[4]. In most Pavement Management Systems (PMSs), non-structural indices such as Pavement Condition Index (PCI) are used as pavement indicators to select treatments [3,5] while ignoring the structural conditions of pavement [6]. It has recently been proven that there is a statistical relationship between functional and structural conditions [7]. Hence in recent years, various agencies around the world have attempted to use indices of structural capacity in PMS and decision-making processes [6].
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Cracking & Patching Modelling On Arterial Roads in Bangalore City

Cracking & Patching Modelling On Arterial Roads in Bangalore City

The study was planned to cover for a time period of five years for a stretch of 56 kms of road length in Bangalore city taken under the urban infrastructure for Indian Scenario. The deteriorating pavement condition variables such as rebound deflection, Cracking & Patching, etc., all were measured , collected through both visual and automated means of data collection. The Relative Deterioration Index was developed, validated based on the studies conducted on the selected stretches of road pavements in Bangalore city during different time periods of the year over a period of five years. The periodic structural evaluations were conducted using Benkelman Beam method and one time data regarding pavement section soil parameters and the pre-monsoon and post-monsoon performance data over a period of time was collected and finally Pavement Deterioration Models were developed based on the RDI developed. Pavement Performance Management is a process of maintaining the network of roads to ensure that the pavement conditions are maintained over the entire network. Although started as a design approach, later pavement management system encompassed all the activities that were included in providing the smooth and safe pavement for the road users as well as the goods that are being carried through it. When the network of roads were minimal, they were maintained in a non-systematic methods which was able to cover the burden, but as the network of roads have increased insurmountably, maintenance of these roads have also become complex, cumbersome, especially within a tight budget. Before moving to the different models of maintaining the roads, this chapter has discussed the various components of PMS, which throws light on how the system works. Flexible and rigid pavements are the two important typesofpavements.
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Development Of Optimum Maintenance & Rehabilitation Strategies For Urban Bituminous Concrete Surfaced Roads

Development Of Optimum Maintenance & Rehabilitation Strategies For Urban Bituminous Concrete Surfaced Roads

ABSTRACT: In India, the road traffic volume has increased manifolds during the post-independence period. The traffic axle loading may also in many cases be much heavier than the specified limit. As a result of which, the existing road network has been subjected to severe deterioration leading to premature failure of the pavements.In such a scenario, development of the effective pavement management strategies would furnish useful information to ensure the compatible and cost- effective decisions so as to keep the existing road network intact. The pavement deterioration models can prove to be an effective tool which can assist highway agencies to forecast economic and technical outcome of possible investment decisions regarding maintenance management of pavements. The optimum maintenance and rehabilitation strategies developed in this study would be useful in planning pavement maintenance strategies in a scientific manner and ensuring rational utilization of limited maintenance funds. Once this strategy for urban road network is implemented and made operational; this would serve as window to the other urban road network of different regions.
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Hybrid Machine Learning Model of Support Vector Machine and Fruit Fly Optimization Algorithm for Prediction of Remaining Service Life of Flexible Pavement

Hybrid Machine Learning Model of Support Vector Machine and Fruit Fly Optimization Algorithm for Prediction of Remaining Service Life of Flexible Pavement

Predicting future pavement conditions and estimating its service life is one of the fundamental tasks 46.. of pavement engineers in pavement management systems (PMSs), as the future net[r]

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UTILIZATION OF WASTE PLASTIC IN BITUMINOUS MIX

UTILIZATION OF WASTE PLASTIC IN BITUMINOUS MIX

We are thankful to International Conference on Recent Trends in Engineering Science & Management for giving us the opportunity to develop the paper. It is our humble thanks to all professors and members of International Journal of Advanced Technology in Engineering & Science for the co-operation and keen interest extended by them throughout our efforts in this paper. It is the base that they have built, which sustain such good job. It was possible due to their co-operation and help. I would like to place on record appreciation for all those who are connected with this paper publish. With great pleasure, I express my deep sense of gratitude to all respected professors of Engineering Department for the co-operation. This paper is not a copy-right form.
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Pavement marking degradation modeling and analysis

Pavement marking degradation modeling and analysis

Five major studies were reviewed that provide insight into pavement marking retroreflectivity performance. These five studies are by Andrady; Lee, et al.; Migletz, et al.; Abboud and Bowman; and Sarasua, et al. Each of the five studies evaluated pavement marking retroreflectivity performance over time and explored the performance characteristics of pavement markings so that predictive models, service life estimates, or degradation curves could be established. Thus, they are closely related to the work reported here. The researchers recognize that there are many ongoing studies regarding pavement marking retroreflectivity, most of which are focused on the relationship between safety and retroreflectivity. These five studies were the ones in the literature with a primary focus on pavement marking performance and modeling.
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