CALIBRATION OF RUTTING AND ROUGHNESS DISTRESS MODELS OF HDM-4 FOR DEVELOPING PAVEMENT MAINTENANCE MANAGEMENT

2018 ◽  
Vol 5 (2) ◽  
Author(s):  
Aditya Singh ◽  
Tanuj Chopra
Keyword(s):  
Road Network ◽  
Local Conditions ◽  
Pavement Condition ◽  
Pavement Maintenance ◽  
The Road ◽  
The World Bank ◽  
Pavement Deterioration ◽  
Network Maintenance ◽  
Investment Programme ◽  
Development And Management

The Highway Development and Management model (HDM-4) is a tool developed by the World Bank to aid highway administrators and engineers in the process of decision making for preparing of road investment programme and determining the road network maintenance strategies. HDM-4 essentially models the interaction between the traffic volume, environment and pavement composition to predict the different kinds of distress that develop in pavements over time. Since distress is caused due to different conditions and progresses at different rates, therefore it is necessary to calibrate the HDM-4 model as per the local conditions. The aim of the study is to calibrate the HDM-4 pavement deterioration model in terms of rutting and roughness for the urban road network of Patiala (Punjab, India). In our study, we select 15 road sections and group them based on varying traffic and pavement age. The pavement condition data, which was measured starting from 2012 to the end of 2014, is fed as the input to the HDM-4 distress models. The calibration process is performed using statistical analysis between the observed and predicted value of the distress by keeping minimum Root Mean Square Error (RMSE) and maximum R-square (R2). The determined calibration factors are validated and further used for developing pavement deterioration models which prove to be helpful in building a Pavement Maintenance and Management system for Patiala.

scholarly journals Development of Roughness Prediction Models for Laos National Road Network

CivilEng ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 158-173
Author(s):  
Mohamed Gharieb ◽  
Takafumi Nishikawa
Keyword(s):  
Prediction Model ◽  
Road Network ◽  
Prediction Models ◽  
Parameter Analysis ◽  
Local Conditions ◽  
Pavement Condition ◽  
Analysis Technique ◽  
Roughness Prediction ◽  
National Road ◽  
Development And Management

The International Roughness Index (IRI) has been accepted globally as an essential indicator for assessing pavement condition. The Laos Road Management System (RMS) utilizes a default Highway Development and Management (HDM-4) IRI prediction model. However, developed IRI values have shown the need to calibrate the IRI prediction model. Data records are not fully available for Laos yet, making it difficult to calibrate IRI for the local conditions. This paper aims to develop an IRI prediction model for the National Road Network (NRN) based on the available Laos RMS database. The Multiple Linear Regression (MLR) analysis technique was applied to develop two new IRI prediction models for Double Bituminous Surface Treatment (DBST) and Asphalt Concrete (AC) pavement sections. The final database consisted of 83 sections with 269 observations over a 1850 km length of DBST NRN and 29 sections with 122 observations over a 718 km length of AC NRN. The proposed models predict IRI as a function of pavement age and Cumulative Equivalent Single-Axle Load (CESAL). The model’s parameter analysis confirmed their significance, and R2 values were 0.89 and 0.84 for DBST and AC models, respectively. It can be concluded that the developed models can serve as a useful tool for engineers maintaining paved NRN.

scholarly journals Pavement Deterioration Rate and Maintenance Cost for Low-Volume Roads

2020 ◽  
Vol 312 ◽  
pp. 06002
Author(s):  
Turki I Al-Suleiman ◽  
Subhi M Bazlamit ◽  
Mahmoud Azzama ◽  
Hesham S Ahmad
Keyword(s):  
Surface Defects ◽  
Condition Index ◽  
Maintenance Cost ◽  
Pavement Condition ◽  
Pavement Maintenance ◽  
Deterioration Rate ◽  
Pavement Deterioration ◽  
Pavement Condition Index ◽  
Traffic Volumes ◽  
Over Time

Allocated budgets for maintenance of road networks are normally limited. Therefore, not all roads receive the required attention they deserve in a timely manner. These roads are left to deteriorate until the next maintenance round. The cost associated with delayed maintenance is significantly excessive. A Pavement Maintenance Management System (PMMS) can be a useful tool for evaluation, prioritization of Maintenance and Rehabilitation (M&R) projects, and determination of funding requirements and allocations. The pavement condition is normally indexed using a parameter called Pavement Condition Index (PCI) which represents an overall assessment of surface defects by type, severity and extent. Periodic collections of PCI over time for different sections within the roadway network provide an approach to monitor changes in pavement serviceability over time and can produce useful data to predict and evaluate required maintenance solutions and their associated cost. The researchers intend to use available data collected over the span of a year and a half on sections within the roadway network at the campus of Al-Zaytoonah University of Jordan (ZUJ) to study the relation between the maintenance cost and the pavement deterioration rate. This study may incorporate variables such as pavement age, traffic volumes, maintenance history and pavement condition assessment results. The available records of PCI will be analyzed and the findings will be clearly presented. The practical inclusion of the findings within the current PMMS used at the university will also be detailed.

scholarly journals Developing An Optimization Model For Pavement Maintenance Planning And Resource Allocation In Hossana Town, Ethiopia

2021 ◽  
Vol 23 (08) ◽  
pp. 824-836
Author(s):  
Tarekegn Shirko Lachore ◽  
◽  
Dagimwork Asele Manuka ◽  
Keyword(s):  
Mathematical Optimization ◽  
Cost Effective ◽  
Optimization Method ◽  
Pavement Management ◽  
Maintenance Strategy ◽  
Pavement Maintenance ◽  
The Road ◽  
Network Maintenance ◽  
Collection Data ◽  
Optimal Maintenance

Pavement Management System is designed to provide objective information and useful data for analysis so that road managers can make more consistent, cost-effective, and defensible decisions related to the preservation of a pavement network. During the process of road network maintenance and rehabilitation, road authorities strive to select an optimum maintenance strategy from a number of alternatives. Mathematical optimization models, supported by suitable data, can assist decision making about allocating funds between alternative maintenance tasks and about the size of the maintenance budget. It can be done through the analysis of costs and benefits by comparing the various maintenance alternatives with the help of an optimization method known as solver. The road segment mainly included in study was road from Hosanna Menhariya to Wachemo University and other important access roads. These roads are divided into different sections in not more than 100m length. The Study involves data collection, data analysis and the selection of optimal maintenance strategy by using a method known as Solver (Add-ins in Microsoft excel). In this study, patching was selected as possible maintenance among the other alternatives. The result of solver analysis for patching indicates that as 74,574 birr allocated for the maintenance of pavement per kilometer in different three segments under the municipality having the constraint budget of 152,018.45 birr/km. The optimized solution shows that about 20962.5 birr would be saved in one year per km with in municipality.

scholarly journals Study of Site-Specific Roughness Progression for a Bitumen-Sealed Unbound Granular Pavement Network

2003 ◽  
Vol 1819 (1) ◽  
pp. 273-281 ◽  
Author(s):  
P. D. Hunt ◽  
J. M. Bunker
Keyword(s):  
Road Network ◽  
Network Performance ◽  
Comprehensive Evaluation ◽  
Average Rate ◽  
Pavement Management ◽  
Pavement Performance ◽  
Pavement Condition ◽  
Pavement Maintenance ◽  
Pavement Management Systems ◽  
Economic Analyses

Pavement management systems assist engineers in the analysis of road network pavement condition data and subsequently provide input to the planning and prioritization of road infrastructure works programs. The data also provide input to a variety of engineering and economic analyses that assist in determining the future road network condition for a range of infrastructure-funding scenarios. The fundamental calculation of future pavement condition is commonly based on a pavement age versus pavement roughness relationship. However, roughness–age relationships commonly do not take into account the pavement’s historical performance; rather, an “average” rate of roughness progression is assigned to each pavement based on its current age or current roughness measurement. Results of a research project are documented; the project involved a comprehensive evaluation of pavement performance by examining roughness progression over time with other related variables. A method of calculating and effectively displaying roughness progression and the effects of pavement maintenance was developed. The method provides a better understanding of pavement performance, which in turn led to a methodology of calculating and reporting road network performance for application to the pavement design and delivery system in Queensland, Australia. Means of using this information to improve the accuracy of roughness progression prediction were also investigated.

The Highway Development and Management System in Washington State

2005 ◽  
Vol 1933 (1) ◽  
pp. 52-61 ◽  
Author(s):  
Jianhua Li ◽  
Stephen T. Muench ◽  
Joe P. Mahoney ◽  
Nadarajah Sivaneswaran ◽  
Linda M. Pierce ◽  
...  
Keyword(s):  
Management System ◽  
Road Network ◽  
The United States ◽  
Washington State ◽  
Pavement Management ◽  
Portland Cement Concrete ◽  
Long Term Effects ◽  
Local Conditions ◽  
Development And Management

The Highway Development and Management System (HDM-4) developed by the World Bank is a powerful pavement management software tool capable of performing technical and economic appraisals of road projects, investigating road investment programs, and analyzing road network preservation strategies. Its effectiveness is dependent on the proper calibration of its predictive models to local conditions. Although significant work has been done in calibrating and applying HDM-4 worldwide (especially in developing nations), no substantial effort has been made within the United States. This paper describes the calibration and application of HDM-4 (Version 1.3) to the Washington State Department of Transportation's (WSDOT) road network. WSDOT hopes to use HDM-4 to supplement its existing Washington State Pavement Management System (WSPMS) in long-term pavement performance and financial needs. Significant findings are that ( a) HDM-4 can be used to analyze the WSDOT road network, ( b) HDM-4 was successfully calibrated for the network, ( c) the network requires calibration factors significantly different than HDM-4 default values, ( d) software issues seem to prevent use of HDM-4 portland cement concrete pavement analysis, and ( e) WSDOT can use HDM-4 to predict pavement preservation budgets quickly, select optimal preservation strategies under varying budget levels, and assist in determining the long-term effects of different funding scenarios on the road network.

scholarly journals Development of the Road Pavement Deterioration Model Based on the Deep Learning Method

Electronics ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 3 ◽  
Author(s):  
Seunghyun Choi ◽  
Myungsik Do
Keyword(s):  
Time Series Data ◽  
Condition Index ◽  
Traffic Load ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Pavement Condition ◽  
The Road ◽  
Road Pavement ◽  
Pavement Deterioration ◽  
Pavement Condition Index

In Korea, data on pavement conditions, such as cracks, rutting depth, and the international roughness index, are obtained using automatic pavement condition investigation equipment, such as ARAN and KRISS, for the same sections of national highways annually to manage their pavement conditions. This study predicts the deterioration of road pavement by using monitoring data from the Korean National Highway Pavement Management System and a recurrent neural network algorithm. The constructed algorithm predicts the pavement condition index for each section of the road network for one year by learning from the time series data for the preceding 10 years. Because pavement type, traffic load, and environmental characteristics differed by section, the sequence lengths (SQL) necessary to optimize each section were also different. The results of minimizing the root-mean-square error, according to the SQL by section and pavement condition index, showed that the error was reduced by 58.3–68.2% with a SQL value of 1, while pavement deterioration in each section could be predicted with a high coefficient of determination of 0.71–0.87. The accurate prediction of maintenance timing for pavement in this study will help optimize the life cycle of road pavement by increasing its life expectancy and reducing its maintenance budget.

scholarly journals Low Cost Road Health Monitoring System: A Case of Flexible Pavements

2021 ◽  
Vol 13 (18) ◽  
pp. 10272
Author(s):  
Shabir Hussain Khahro ◽  
Yasir Javed ◽  
Zubair Ahmed Memon
Keyword(s):  
Monitoring System ◽  
Health Monitoring ◽  
Road Network ◽  
Low Cost ◽  
Health Monitoring System ◽  
Pavement Maintenance ◽  
The Road ◽  
Country Road ◽  
Road Condition Monitoring ◽  
Road Health Monitoring

A healthy road network plays a significant role in the socio-economic development of any country. Road management authorities struggle with pavement repair approaches and the finances to keep the existing road network to its best functionality. It has been observed that real-time road condition monitoring can drastically reduce road and vehicle maintenance expenses. There are various methods to analyze road health, but most are either expensive, costly, time-consuming, labor-intensive, or imprecise. This study aims to design a low-cost smart road health monitoring system to identify the road section for maintenance. An automized sensor-based system is developed to assist the road sections for repair and rehabilitation. The proposed system is mounted in a vehicle and the data have been collected for a more than 1000 km road network. The data have been processed using SPSS, and it shows that the proposed system is adequate for detecting the road quality. It is concluded that the proposed system can identify the vulnerable sections to add to the pavement maintenance plan. In the future, the created application can be launched as a smart citizen app where each car driver can install this application and can monitor the road quality automatically.

scholarly journals Pavement Maintenance Management Application for Road Network in Romania

2019 ◽  
Vol 8 (2) ◽  
pp. 73-88
Author(s):  
Toma Mihai Gabriel ◽  
Mihai Dicu
Keyword(s):  
Road Network ◽  
Evaluation Process ◽  
Point Of View ◽  
Sufficient Information ◽  
Pavement Maintenance ◽  
The Road ◽  
Microsoft Access ◽  
Public Road ◽  
Technical Status

Abstract Maintaining the conditions for optimum exploitation of road networks is one of the primary activities of their administrators. The basic elements for establishing the decision-making act, are obtained by the correct evaluation, from the technical and financial point of view, of what is necessary for the normal unfolding, without interruptions, and in complete safety, of the car traffic. In the evaluation process, the managers must have at their disposal sufficient information, regarding the technical status of the road network from the administration, when and where it is appropriate to intervene and what maintenance and repairs operations should be performed. Only in this way, road managers will be able to adopt the appropriate strategy so that the investment reaches the highest rate of return and of course falls within the limits of the allocated funds. This paper presents A.D.T.S. (Automatic Determination of the Technical Status) application, designed using the Microsoft Access program. The application allows the determination of the technical status of the roads, storage, retrieval, updating and verification of information regarding the technical status of the roads. The information is kept in a road reference table, as a storage model in data banks, which can be used by public road administrators in their work, regarding the scheduling of works and justifying the need to finance road intervention works.

scholarly journals Cluster-Based Pavement Deterioration Models for Low-Volume Rural Roads

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
V. Sunitha ◽  
A. Veeraragavan ◽  
Karthik K. Srinivasan ◽  
Samson Mathew
Keyword(s):  
Maintenance Management ◽  
Road Maintenance ◽  
Rural Roads ◽  
Pavement Maintenance ◽  
The Road ◽  
Rural Road ◽  
Pavement Deterioration ◽  
Pavement Distresses ◽  
Low Volume ◽  
Nonhierarchical Clustering

The management of low-volume rural roads in developing countries presents a range of challenges to road designers and managers. Rural roads comprise over 85 percent of the road network in India. The present study aims at development of deterioration models for the optimum maintenance management of the rural roads under a rural road programme namely Pradhan Mantri Gram Sadak Yojana (PMGSY) in India. Visual condition survey along the selected low-volume rural roads considers parameters like condition of shoulders, drainage features, cross-drainage structures, and camber, and pavement distresses, namely, potholes, crack area, and edge break, are collected for a period of three years. The deterioration models have a significant role in the pavement maintenance management system. However, the performance of a pavement depends on several factors. Cluster analysis can be used to group the pavement sections so that the performance of pavements in different clusters can be studied. Nonhierarchical clustering technique of k-means clustering was considered. Separate deterioration models have been developed for each of the clusters. A comparison of the models developed with and without clustered sections reveals that the clustering of pavement sections are preferred for the efficient rural road maintenance management.

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