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.

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.

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 A weighted multi-output neural network model for the prediction of rigid pavement deterioration

2020 ◽  
Author(s):  
Fengdi Guo ◽  
Xingang Zhao ◽  
Jeremy Gregory ◽  
Randolph Kirchain
Keyword(s):  
Neural Network ◽  
Longitudinal Crack ◽  
Condition Index ◽  
Prediction Performance ◽  
Pavement Management ◽  
Pavement Condition ◽  
Single Output ◽  
Rigid Pavements ◽  
Model Training ◽  
Condition Metric

A novel weighted multi-output neural network (NN) model is proposed for predicting the deterioration of rigid pavements based on Iowa pavement management system data. This first-of-a-kind model simultaneously predicts four pavement condition metrics concerning rigid pavements, including IRI, faulting, longitudinal crack and transverse crack. It provides an opportunity to efficiently evaluate pavement conditions and to make treatment decisions based on multi-condition metrics, such as the pavement condition index (PCI) for budget allocation models. Compared to traditional single-output NN models, this multi-output model is capable of incorporating correlations among different condition metrics. During model training, each condition metric is assigned a weight to reflect its relative importance. When the weights equal to those in the formula for the multi-condition metric, the prediction performance for PCI is optimal (13% lower MSE than optimal, single-output models). The multi-output model improves on the prediction performance for three of the four individual condition metrics compared to optimal single-output models. Results show that the consideration of correlations could improve the prediction performance for single and multi-condition metrics. Finally, variable weighting is critical for achieving the optimal balance of prediction performance among the various metrics as dictated by the needs of the decisionmaker.

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 APCI Evaluation Method for Cement Concrete Airport Pavements in the Scope of Air Operation Safety and Air Transport Participants Life

2020 ◽  
Vol 17 (5) ◽  
pp. 1663 ◽  
Author(s):  
Mariusz Wesołowski ◽  
Paweł Iwanowski
Keyword(s):  
Evaluation Method ◽  
Load Capacity ◽  
Human Life ◽  
Good Condition ◽  
Surface Damage ◽  
Condition Index ◽  
Air Transport ◽  
Actual Condition ◽  
Pavement Condition ◽  
Pavement Condition Index

Many factors have an impact on flight operation safety and air transport participants life. This article presents one of them, which is maintenance of the airport infrastructure in a good condition, with proper infrastructure management, in particular of cash and human resources. At the beginning of the article, attention is paid to the aspect of safety and human life in air transport. Also, an overview of world experience in the field of assessment of the technical condition of airport pavements was presented, including the standard method of the Pavement Condition Index (PCI) estimation. Then, the authors propose an innovative method of assessing the condition of airport pavements based on the Airfield Pavement Condition Index (APCI), taking into account, apart from the extent of surface damage, such parameters as load capacity, evenness, roughness, and bond strength. This approach gives a broader picture of the actual condition of the airport pavement, which has a great importance on flight operation safety, including passengers and cruel life. Next the described research method is experimentally verified in real conditions at Polish airports. Finally, an example of using the APCI method in the assessment of selected airport pavements from Polish airports is presented. The results of tests performed on five functional elements of a military airfield are presented. A satisfactory result is obtained for three elements, an adequate—for two.

Estimation of Pavement Serviceability Index Through Android-Based Smartphone Application for Local Roads

2017 ◽  
Vol 2639 (1) ◽  
pp. 129-135 ◽  
Author(s):  
Waleed Aleadelat ◽  
Khaled Ksaibati
Keyword(s):  
Smartphone Application ◽  
Condition Index ◽  
Pavement Management ◽  
Pavement Condition ◽  
Explanatory Variables ◽  
Pavement Condition Index ◽  
Local Roads ◽  
Series Acceleration ◽  
The Difference ◽  
The Cost

The Wyoming Technology Transfer Center is in the process of developing a pavement management system (PMS) for county paved roads in Wyoming. This PMS uses the present serviceability index (PSI) as a main pavement performance parameter. This PMS depends on pavement condition index, international roughness index, and pavement rutting as explanatory variables to estimate PSI. This study researched new explanatory variables measured by using smartphones’ sensors to estimate PSI. It was found that the variance of the signals (time series acceleration data) acquired by smartphones’ accelerometers could work as a very good explanatory variable to estimate PSI. Two models were developed with high significance ( R2 higher than .9) to predict PSI using the variance of smartphone signals. The initial validation results suggested that using these models could predict, with high certainty, the actual PSI values. The difference between the predicted and the actual PSI values was not statistically different. The study was performed on 20 roadway segments extracted from the Wyoming county roads’ PMS database. In addition, the selected segments had various lengths and geometric features reflecting various roadway segments under any PMS. The proposed methodology is intended to lower the cost of measuring county roads’ pavement conditions by estimating PSI directly without the reliance on the direct measurement of pavement condition parameters.

scholarly journals Assessment of the road based on PCI and IRI roadroid measurement

2018 ◽  
Vol 195 ◽  
pp. 04006 ◽  
Author(s):  
Donny A. Putra ◽  
Mamok Suprapto
Keyword(s):  
Good Condition ◽  
Visual Assessment ◽  
Condition Index ◽  
Assessment Method ◽  
Visual Methods ◽  
International Roughness Index ◽  
Pavement Condition ◽  
The Road ◽  
Roughness Index ◽  
Pavement Condition Index

There are two methods of road assessment, ie, visually and using tools. Visual assessment makes use of the PCI (Pavement Condition Index), while assessment with the Roadroid app can be used to obtain the value of IRI (International Roughness Index) with less cost. Functional assessment of roads in the field more use of visual methods. This method is influenced by the subjectivity of surveyors. Therefore, the assessment using the visual method should be correlated with the assessment method using tools, in order to reduce the subjectivity of road assessment. The research location used is Magetan District Road consisting of 5 road segments. The result shows that the r road assessment using the PCI method has a very good condition, and using IRI Roadroid has a Medium condition. There is a negative (r) correlation between PCI and IRI Roadroid, valued at -0.23. The negative correlation shows that both judgments reversed. Comparison of PCI assessment with IRI Roadroid has a low correlation value and with ttest, yields no comparison of correlation. This result is because the PCI and IRI equally assess the pavement, using different methods.

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 Assessment of Al-Amarah street within the Al-kut city using pavement condition index (PCI) and GIS technique

2018 ◽  
Vol 162 ◽  
pp. 01033
Author(s):  
Mohammed Al-Neami ◽  
Rasha Al-Rubaee ◽  
Zainab Kareem
Keyword(s):  
Condition Index ◽  
Pavement Management ◽  
Pavement Condition ◽  
The Road ◽  
Gis Technique ◽  
Gis Data ◽  
Pavement Condition Index ◽  
Specific Sign ◽  
Maintenance Process

The capabilities of geographical system and their spatial analysis is considered the most appropriate tools to enhance pavement management operations, with features such as graphical display of pavement condition. In Iraq, most of transportation agencies do not have a tool that is used as a database for road deteriorations, so there is a need for road surveying and storing the collected information in GIS to know the condition of every road with details. Furthermore, these data can be used for maintenance process and estimation of prior cost. This research has been carried out to estimate of flexible pavement condition through visual surveys using the Pavement Condition Index (PCI) method; so it can provide an easy way to calculate the PCI based on GIS data with Micro PAVER software 5.2. Al-Amarah Street, which is internal road in Al-Kut city in the eastern part of Iraq, is used as a case study. The average pavement condition index of the selected case study is found to be “64” using Micro PAVER 5.2 software which mean “Fair” pavement condition. Arc Map 9.3 has been applied in this study to make an integrated maintenance system for each road in the region demonstrating the annual road deteriorations and the resulting change in the PCI values which occurs every year. The study provides an easy and simplified way of presentation the details of deteriorations on the satellite or the geographical map of the road in which each type of distress has been symbolized with specific sign and each PCI value has been represented with specific color.

scholarly journals Evaluation of Asphalt Concrete Airport Pavement Conditions Based on the Airfield Pavement Condition Index (APCI) in Scope of Flight Safety

Aerospace ◽  
2020 ◽  
Vol 7 (6) ◽  
pp. 78
Author(s):  
Mariusz Wesołowski ◽  
Paweł Iwanowski
Keyword(s):  
Quality Management System ◽  
Condition Index ◽  
Assessment Method ◽  
Technical Condition ◽  
Pavement Management ◽  
Infrastructure Development ◽  
Pavement Condition ◽  
Airport Pavement ◽  
Pavement Condition Index ◽  
High Level

Airoport infrastructure development requires care to maintain it in proper technical condition. Due to this, airport pavements should be constantly monitored, and, above all, correctly managed. High-level airport pavement management requires access to reliable information about their current technical condition as well as proper forecasting of this condition in the future. Obtaining good quality information about the technical condition of airport pavement should be based on a proven methodology, taking into account the introduced quality management system. The authors propose a method of technical pavement condition assessment based on the Airfield Pavement Condition Index (APCI), taking into account not only the results of the surface deterioration inventory, but also repair overviews, load bearing capacity, evenness and roughness of the surface, as well as the surface tensile bond strength. The method was developed during long-term work financed by the Ministry of Science and Higher Education. At the beginning of the article, the authors focus on reviewing the currently available methods of assessing the technical condition of the pavement. Then they briefly present the most popular surface assessment method based on the PCI indicator. Afterwards, a proprietary asphalt pavement assessment method based on the APCI indicator is proposed and an example of how to use the method is presented. Finally, they discuss the results and summarize the work done, and present further directions of work.

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