scholarly journals Pavement Maintenance Decision Making Based on Optimization Models

2021 ◽  
Vol 11 (20) ◽  
pp. 9706
Author(s):  
Shitai Bao ◽  
Keying Han ◽  
Lan Zhang ◽  
Xudong Luo ◽  
Shunqing Chen
Keyword(s):  
Decision Making ◽  
Optimization Model ◽  
Linear Optimization ◽  
Condition Index ◽  
Maintenance Costs ◽  
Pavement Condition ◽  
Pavement Maintenance ◽  
Linear Optimization Model ◽  
Decision Making Problem ◽  
Pavement Condition Index

Pavement maintenance prioritization considering both quality and cost is an important decision-making problem. In this paper, the actual pavement condition index of city roads was calculated using municipal patrol data. A linear optimization model that maximized maintenance quality with limited maintenance costs and a multi-objective optimization model that maximized maintenance quality while minimizing maintenance costs were developed based on the pavement condition index. These models were subsequently employed in making decisions for actual pavement maintenance using sequential quadratic programming and a genetic algorithm. The results showed that the proposed decision-making models could effectively address actual pavement maintenance issues. Additionally, the results of the single-objective linear optimization model verified that the multiobjective optimization model was accurate. Thus, they could provide optimal pavement maintenance schemes for roads according to actual pavement conditions. The reliability of the models was investigated by analyzing their assumptions and validating their optimization results. Furthermore, their applicability in pavement operation-related decision making and preventive maintenance for roads of different grades was confirmed.

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.

Investigating Pavement Maintenance and Rehabilitation Requirement Based on Material Types and Traffic Levels through an Application of Probabilistic Approach for Ontario Highways

2019 ◽  
Vol 2673 (11) ◽  
pp. 561-572
Author(s):  
Gulfam Jannat ◽  
Susan L. Tighe
Keyword(s):  
Probabilistic Approach ◽  
Condition Index ◽  
Probability Of Failure ◽  
Pavement Management ◽  
Deterministic Approach ◽  
Pavement Management System ◽  
Pavement Condition ◽  
Pavement Maintenance ◽  
Maintenance And Rehabilitation ◽  
Pavement Condition Index

In a pavement management system (PMS), time to maintenance is generally estimated based on the predicted condition of the pavement. Usually a deterministic approach is applied in the PMS to estimate the time to maintenance by following the deterioration equation of the performance index. However, it is necessary to be aware of the probability of failure to investigate whether the estimated time to maintenance by the deterministic approach is reasonably probable. For this reason, a probabilistic approach is applied in this study to estimate the probability of failure over the estimated time to maintenance. In this approach, the probability of failure is estimated from the distribution of the mean time to maintenance by considering both the overall condition of the pavement and individual instances of distress. These mean times to failure or maintenance are calculated from the overall condition of pavement in relation to the pavement condition index (PCI) when the trigger value becomes 65 or less. A pavement may be expected to fail, however, because of any specific distress before it reaches the PCI trigger value for maintenance. For this reason, the probability of failure of each specific distress is also investigated by using a Monte Carlo simulation. It is found that the survival probability up to the fifth year is approximately 80% to 90% for each category of traffic and material type based on the overall condition, and the probability of failure for individual distress is very low over the performance cycle.

Universal Pavement Distress Evaluator Based on Fuzzy Sets

1997 ◽  
Vol 1592 (1) ◽  
pp. 180-186 ◽  
Author(s):  
Samir N. Shoukry ◽  
David R. Martinelli ◽  
Jennifer A. Reigle
Keyword(s):  
Decision Making ◽  
Condition Index ◽  
Functional Condition ◽  
Pavement Management ◽  
Ride Quality ◽  
Membership Functions ◽  
Pavement Condition ◽  
Pavement Maintenance ◽  
Maintenance Policies ◽  
Management Database

Setting priorities for pavement maintenance and rehabilitation depends on the availability of a universal scale for assessing the condition of every element in the network. The condition of a pavement section has traditionally been assessed by several condition indexes. The present serviceability index (PSI) is one common evaluator used to describe the functional condition with respect to ride quality. Pavement condition index is another index commonly used to describe the extent of distress on a pavement section. During the decision-making process, both classes of indexes are needed to evaluate the overall status of a pavement section in comparison to other sections in the network. Traditionally, regression techniques were used for the development of functions that relate condition indexes to the information recorded in the pavement management database. This approach produces mathematical functions that are limited to a particular database. The functions so developed may also suffer from inaccuracies due to errors in data collection and recording. There is a need for a more generalized approach for the evaluation of pavement conditions to enable efficient management of large transportation networks. The development of a universal measure capable of formally assessing the condition of a pavement section within the universe of pavement conditions is described. This is accomplished by the fusion of a set of fuzzy membership functions that describe different parameters in the database with the perception of each parameter’s significance. The model output is the fuzzy distress index (FDI), which combines the extent of structural distress with traditional performance parameters such as roughness to describe the overall status of the pavement section. The behavior of FDI over time is examined for a random sample of pavement sections and is compared with trends in the corresponding PSI values (PSI was used only because it was readily available in the database). The results indicate that the flexible, universal FDI is a consistent and accurate measure of the overall pavement condition. The set of generated membership functions describing the different extents of every distress type can be easily standardized over the 50 states, allowing the model to be implemented on any pavement at any location. Also, the parameter weights used in the assessment may be easily adjusted (increased or decreased) to reflect changes in maintenance policies or budget availability at the local, state, or national decision-making level. Moreover, the concept allows for the omission of any number of parameters that might not be available in a particular pavement management database.

VALIDITY OF GARBER MODEL IN PREDICTING PAVEMENT CONDITION INDEX OF FLEXIBLE PAVEMENT IN KERBALA CITY

2018 ◽  
Vol 09 (02) ◽  
pp. 139-151
Author(s):  
Hussein Ewadh ◽  
◽  
Raid Almuhanna ◽  
Saja Alasadi ◽  
◽  
...  
Keyword(s):  
Condition Index ◽  
Flexible Pavement ◽  
Pavement Condition ◽  
Pavement Condition Index

scholarly journals An Investigation of Geography and Climate Induced Distresses Patterns on Airfield Pavements at US Air Force Installations

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Lauren K. Sahagun ◽  
Moses Karakouzian ◽  
Alexander Paz ◽  
Hanns de la Fuente-Mella
Keyword(s):  
Air Force ◽  
Condition Index ◽  
Portland Cement Concrete ◽  
Climate Zones ◽  
Pavement Condition ◽  
Pavement Distress ◽  
Western Us ◽  
Us Air Force ◽  
Pavement Condition Index ◽  
Predominant Factor

This study investigated climate induced distresses patterns on airfield pavements at US Air Force installations. A literature review and surveys of Pavement Condition Index indicated that the predominant factor contributing to the development of pavement distress was climate. Results suggested that, within each type of pavement distress, a geographic pattern exists which is strongly correlated to conventional US climate zones. The US Air Force Roll-Up Database, housing over 50,000 records of pavement distress data, was distilled using a process designed to combine similar distresses while accounting for age and size of samples. The process reduced the data to a format that could be used to perform krig analysis and to develop pavement behavior models for runways built with asphalt cement (AC) and Portland cement concrete (PCC). Regression and krig analyses were conducted for each distress type to understand distress behavior among climate zones. Combined regression and krig analyses provided insight into the overall pavement behavior for AC and PCC runways and illustrated which climate zone was more susceptible to specific pavement distresses. Distress behavior tends to be more severe in the eastern US for AC and in the western US for PCC runway pavements, respectively.

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