scholarly journals Comparison of Pavement Performance Models for Urban Road Management System

2020 ◽  
Vol 15 (3) ◽  
pp. 111-129
Author(s):  
Igoris Kravcovas ◽  
Audrius Vaitkus ◽  
Rita Kleizienė
Keyword(s):  
Bearing Capacity ◽  
Management System ◽  
Condition Index ◽  
Performance Model ◽  
Pavement Management ◽  
Pavement Performance ◽  
Performance Models ◽  
Climate Conditions ◽  
Pavement Condition ◽  
Pavement Performance Model

The key factors for effective pavement management system (PMS) are timely preservation and rehabilitation activities, which provide benefit in terms of drivers’ safety, comfort, budget and impact on the environment. In order to reasonably plan the preservation and rehabilitation activities, the pavement performance models are used. The pavement performance models are usually based on damage and distress observations of rural roads, and can be applied to forecast the performance of urban roads. However, the adjustment of the parameters related to traffic volume, speed and load, climate conditions, and maintenance has to be made before adding them to PMS for urban roads. The main objective of this study is to identify the performance indicators and to suggest pavement condition establishment methodology of urban roads in Vilnius. To achieve the objective, the distresses (rut depth and cracks), bearing capacity, and international roughness index (IRI) were measured for fifteen urban roads in service within a two-year period. The distresses, rut depth and IRI were collected with the Road Surface Tester (RST) and bearing capacity of pavement structures were measured with a Falling Weight Deflectometer (FWD). The measured distresses were compared to the threshold values identified in the research. According to the measured data, the combined pavement condition indices using two methodologies were determined, as well as a global condition index for each road. The analysed roads were prioritized for maintenance and rehabilitation in respect to these criteria. Based on the research findings, the recommendations for further pavement condition monitoring and pavement performance model implementation to PMS were highlighted.

Development of Adaptive Performance Models for Oklahoma Airfield Pavement Management System

2003 ◽  
Vol 1853 (1) ◽  
pp. 44-54 ◽  
Author(s):  
Jie Yuan ◽  
Michael A. Mooney
Keyword(s):  
Management System ◽  
Condition Index ◽  
Pavement Management ◽  
General Aviation ◽  
Portland Cement Concrete ◽  
Performance Models ◽  
Pavement Management System ◽  
Pavement Condition ◽  
Maintenance And Rehabilitation ◽  
The Family

The Oklahoma airfield pavement management system (APMS) is a set of pavement management tools that can assist with pavement condition evaluation, as well as prioritization and scheduling of pavement maintenance and rehabilitation activities. Pavement performance models were developed to support the APMS for more than 70 Oklahoma general aviation airports. The family modeling method based on the pavement condition index was tailored to fit the deterioration characteristics of these airfield pavements. The statistical and engineering significance of seven levels of pavement factors was investigated, and pavement factors that affect pavement deterioration significantly were identified as family variables. Asphalt concrete pavement families were formed by sorting pavement function, distress cause, and pavement thickness, while portland cement concrete pavements were divided into families according to pavement function and climate zone. The family polynomial curves were able to reveal the expected deterioration patterns and are logical in engineering principle. Rooted by an adaptive database, the system accepts expert opinion and automatically integrates effects of major maintenance and rehabilitation activities into modeling. From the up-to-date database, the performance models update forecasts automatically.

DEVELOPMENT OF PAVEMENT PERFORMANCE MODEL FOR PROPER REHABILITATION AND MAINTENANCE USING FIRST ORDER MARKOV CHAIN

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Amjad Issa ◽  
Sameer Abu Eisheh
Keyword(s):  
Markov Chain ◽  
Condition Index ◽  
Performance Model ◽  
Pavement Performance ◽  
Pavement Condition ◽  
First Order ◽  
Order Markov Chain ◽  
Effective Manner ◽  
The Right ◽  
Pavement Performance Model

The development of pavement performance model is an important step in prediction the future condition of pavement section and accordingly identifying the right road rehabilitation and maintenance in the right time for the right section. The first order Markov chain probabilistic model is used to predict the degradation of flexible pavement in Palestine. A pilot study is conducted on part of the road network in Nablus City. Visual road condition assessment is performed, and the Pavement Condition Index (PCI) is used in rating pavement sections by dividing the roads each 100 m length. The prediction of the pavement condition rating for each section in the first five to ten years of section age will enhance the applying of preventive maintenance strategy and consequently urges the Local Governmental Units to use the limited allocated budgets specified for pavement maintenance in a cost-effective manner by applying maintenance actions such as crack sealing, surface patching, micro-surfacing, milling and overlay, etc.

scholarly journals Comparing of Data Collection for Network Level Pavement Management of Urban Roads and Highways

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Hui Wang ◽  
Zhoucong Xu ◽  
Lei Yue
Keyword(s):  
Data Collection ◽  
Prediction Models ◽  
Condition Index ◽  
Current Data ◽  
Performance Model ◽  
Pavement Management ◽  
Pavement Performance ◽  
Pavement Condition ◽  
Monitoring Frequency ◽  
Maintenance Decisions

Pavement condition data are collected by agencies to support pavement management system (PMS) for decision-making purpose as well as to construct performance model. The cost of pavement data collection increases with the increase of survey frequencies. However, a lower monitoring frequency could lead to unreliable maintenance decisions. It is necessary to understand the influence of monitoring frequencies on maintenance decision by considering the reliability of performance prediction models. Because of different maintenance conditions of urban roads and highways, their performance show different trends. In this paper, the influence of pavement monitoring frequency on the pavement performance models was investigated. The results indicate that low collection frequencies may result in delay in maintenance action by overestimating pavement performance. The collection frequency for Pavement Condition Index (PCI) can be reduced without compromising the accuracy of performance model, more work should be done to ensure the PCI data quality, thus to guarantee the rationality of maintenance decisions. Effect of frequency reduction on pavement performance (IRI) models of urban roads seems greater than on pavement performance (IRI) models of highways, which may lead to heavier monitoring work for urban roads management. This paper provided an example which demonstrated how a comparative analysis can be performed to determine whether the current data collection plan can provide sufficient data for time series analysis.

scholarly journals Proposal and Implementation of a Heliport Pavement Management System: Technical and Economic Comparison of Maintenance Strategies

2021 ◽  
Vol 13 (16) ◽  
pp. 9201 ◽  
Author(s):  
Paola Di Mascio ◽  
Alessio Antonini ◽  
Piero Narciso ◽  
Antonio Greto ◽  
Marco Cipriani ◽  
...  
Keyword(s):  
Management System ◽  
Condition Index ◽  
Pavement Management ◽  
Pavement Management System ◽  
Pavement Condition ◽  
Airport Pavement ◽  
Maintenance And Rehabilitation ◽  
Pavement Condition Index ◽  
Rotary Wing ◽  
Economic Comparison

Maintenance and rehabilitation (M&R) scheduling for airport pavement is supported by the scientific literature, while a specific tool for heliport pavements lacks. A heliport pavement management system (HPMS) allows the infrastructure manager to obtain benefits in technical and economic terms, as well as safety and efficiency, during the analyzed period. Structure and rationale of the APSM could be replicated and simplified to implement a HPMS because movements of rotary-wing aircrafts have less complexity than fixed-wing ones and have lower mechanical effects on the pavement. In this study, an innovative pavement condition index-based HPMS has been proposed and implemented to rigid and flexible surfaces of the airport of Vergiate (province of Varese, Italy), and two twenty-year M&R plans have been developed, where the results from reactive and proactive approaches have been compared to identify the best strategy in terms of costs and pavement level of service. The result obtained shows that although the loads and traffic of rotary-wing aircrafts are limited, the adoption of PMS is also necessary in the heliport environment.

scholarly journals Flexible Pavement Performance Evaluation in Ontario: an Overview

2021 ◽  
Author(s):  
Muzaffar Hassan
Keyword(s):  
Management System ◽  
Prediction Models ◽  
Pavement Management ◽  
Pavement Performance ◽  
Ride Quality ◽  
Physical Parameters ◽  
Pavement Management System ◽  
Pavement Condition ◽  
Pavement Distress ◽  
Verification Techniques

Measuring pavement performance is a major component of the pavement management system. It assists in decision-making for finding the optimum strategies to provide, evaluate, and maintain serviceability in an acceptable condition cost effectively. The Ontario Ministry of Transportation (MTO) has been systematically rating pavement performance since the mid-1960s. Pavement condition survey involves measurement of two physical parameters: ride quality of pavement surfaces, and the extent and severity of pavement distress manifestations. The pavement ride quality can be measured with an acceptable level of consistency and repeatability through automation. However, achieving consistency in the evaluation of pavement distress manifestations is a challenging task because the automation that could accurately and consistently detect, quantify and record surface distresses is not fully developed is spite of rapid advances in video imagery and non-contact sensing devices. This report evaluates the progress made over the past three decades in the key areas of Distress Manifestation Index, Riding Comfort Rating, Pavement Condition Index and second generation Pavement Management System (PMS2). A review of the Ministryʼs network-level pavement performance database is presented, emphasizing pavement condition surveys, prediction models and main factors influencing assessment of long-term pavement performance. Several key issues related to the quality control and quality assurance of the pavement roughness are discussed with reference to the verification techniques used by the MTO. Based on the literature review, future recommendations for possible improvements of the prediction models and techniques used for the evaluation of pavement performance are presented in order to obtain more consistent values.

scholarly journals IRI performance models for recently constructed low and medium-traffic two lane roads of the province of Biscay

2016 ◽  
Author(s):  
Heriberto Pérez Acebo ◽  
Hernán Gonzalo-Orden
Keyword(s):  
Prediction Models ◽  
Ride Comfort ◽  
Heavy Traffic ◽  
Performance Model ◽  
Pavement Management ◽  
Regional Government ◽  
Performance Models ◽  
Passenger Cars ◽  
Climate Conditions ◽  
On The Road

Reliable pavement prediction models are needed for pavement management systems (PMS), as they are a key component to forecast future conditions of the pavement and to prioritize maintenance, rehabilitation and reconstruction strategies. The International Roughness Index (IRI) is the most used parameter worldwide for calibrating pavement roughness and measures reasonably the ride comfort perceived by occupants of passenger cars. The Regional Government of Biscay also collects this value on the road network under its control These surveys are carried out regularly in the XXI century. Several IRI performance models have been proposed by different authors and administrations, varying greatly in their comprehensiveness, the ability to predict performance with accurancy and input data requirements. The aim of this paper is to develop a roughness performance model for Biscay's roads, based on availablbe IRI data, taking into account heavy traffic volume and the age of pavement. Local characteristics as climate conditions and average rainfall are not considered. IRI performance models have been suggested for regional two lane highways with low and medium heavy traffic constructed in the last 20 years in the province of Biscay, with no treatments during their life. They can be applied for flexible pavements, but no logical coherent results have been concluded for semi-rigid pavements.DOI: http://dx.doi.org/10.4995/CIT2016.2016.4108 

scholarly journals Flexible Pavement Performance Evaluation in Ontario: an Overview

2021 ◽  
Author(s):  
Muzaffar Hassan
Keyword(s):  
Management System ◽  
Prediction Models ◽  
Pavement Management ◽  
Pavement Performance ◽  
Ride Quality ◽  
Physical Parameters ◽  
Pavement Management System ◽  
Pavement Condition ◽  
Pavement Distress ◽  
Verification Techniques

Measuring pavement performance is a major component of the pavement management system. It assists in decision-making for finding the optimum strategies to provide, evaluate, and maintain serviceability in an acceptable condition cost effectively. The Ontario Ministry of Transportation (MTO) has been systematically rating pavement performance since the mid-1960s. Pavement condition survey involves measurement of two physical parameters: ride quality of pavement surfaces, and the extent and severity of pavement distress manifestations. The pavement ride quality can be measured with an acceptable level of consistency and repeatability through automation. However, achieving consistency in the evaluation of pavement distress manifestations is a challenging task because the automation that could accurately and consistently detect, quantify and record surface distresses is not fully developed is spite of rapid advances in video imagery and non-contact sensing devices. This report evaluates the progress made over the past three decades in the key areas of Distress Manifestation Index, Riding Comfort Rating, Pavement Condition Index and second generation Pavement Management System (PMS2). A review of the Ministryʼs network-level pavement performance database is presented, emphasizing pavement condition surveys, prediction models and main factors influencing assessment of long-term pavement performance. Several key issues related to the quality control and quality assurance of the pavement roughness are discussed with reference to the verification techniques used by the MTO. Based on the literature review, future recommendations for possible improvements of the prediction models and techniques used for the evaluation of pavement performance are presented in order to obtain more consistent values.

scholarly journals Condition Survey for Evaluation of Pavement Condition Index of a Highway

2019 ◽  
Vol 5 (6) ◽  
pp. 1367-1383
Author(s):  
Muhammad Saleem Zafar ◽  
Syed Naveed Raza Shah ◽  
Muhammad Jaffar Memon ◽  
Touqeer Ali Rind ◽  
Muhammad Afzal Soomro
Keyword(s):  
Management System ◽  
Structural Reliability ◽  
Condition Index ◽  
Pavement Management ◽  
Present Condition ◽  
Pavement Condition ◽  
Pavement Distress ◽  
Pavement Condition Index ◽  
The Common ◽  
Infrastructure Maintenance

Pavements are major means of highway infrastructure. Maintenance and rehabilitation of these pavements for the required serviceability is a routine problem faced by highway engineers and organizations. Improvement in road management system results in reduction of time and cost, the pavement condition survey plays a big role in the pavement management. The initial phase in setting up a pavement management system (PMS) is road network identification. A vital element of a PMS is the capacity to assess the present condition of a pavement network and anticipation of future condition. The pavement condition index (PCI) is a numerical index generally utilized for the assessment of the operational condition & structural reliability of pavements. Estimation of the PCI is dependent on the results of a visual inspection in which the type, severity, and quantity of distresses are distinguished. In this research, a pavement distress condition rating strategy was utilized to accomplish the goals of this study. The main targets of this research were to categorize the common types of distress that exist on “Lakhi Larkana National Highway (N-105)”, and to estimate the pavement condition index. Using these data, Average PCI for the highway section was calculated. PCI to assess the pavement performance, 10 out of 19 defects were recognized in the pavement, as stated by the PCI method. Results indicated that the common pavement distress types were depressions, polished aggregate, rutting, potholes, block cracking, and alligator cracking.

Pavement management with dynamic traffic and artificial neural network: a case study of Montreal

2016 ◽  
Vol 43 (3) ◽  
pp. 241-251 ◽  
Author(s):  
Md. Shohel Reza Amin ◽  
Luis E. Amador-Jiménez
Keyword(s):  
Neural Network ◽  
Linear Programming ◽  
Travel Demand ◽  
Learning Algorithm ◽  
Good Condition ◽  
Condition Index ◽  
Pavement Management ◽  
Pavement Performance ◽  
Pavement Condition ◽  
Demand Models

This study improves the pavement management system by developing a linear programming optimization for the road network of the City of Montreal with simulated traffic for a period of 50 years and deals with the uncertainty of pavement performance modeling. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. A backpropagation neural network (BPN) with a generalized delta rule learning algorithm is applied to develop pavement performance models without uncertainties. Linear programming of life-cycle optimization is applied to develop maintenance and rehabilitation strategies to ensure the achievement of good levels of pavement condition subject to a given maintenance budget. The BPN network estimated that PCI values were predominantly determined by the differences in pavement condition index, AADT, and equivalent single axle loads. Dynamic linear programming optimization estimated that CAD$150 million is the minimum annual budget required to keep most of the arterial and local roads in good condition in Montreal.

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