scholarly journals Utility-Based Road Maintenance Prioritization Method Using Pavement Overall Condition Rating

2020 ◽  
Vol 15 (1) ◽  
pp. 126-146 ◽  
Author(s):  
Saleh Abu Dabous ◽  
Ghadeer Al-Khayyat ◽  
Sainab Feroz
Keyword(s):  
Resource Constraints ◽  
Road Maintenance ◽  
Service Levels ◽  
Pavement Condition ◽  
Pavement Maintenance ◽  
Condition Rating ◽  
Prioritization Method ◽  
Maintenance And Rehabilitation ◽  
The Given ◽  
Utility Approach

Pavement maintenance and rehabilitation are expensive activities and the available budget to manage the existing pavement infrastructure is limited. Managers require a prioritization method to assist them in selecting the most appropriate maintenance options. Maintenance prioritization is necessary to maintain pavement sections at acceptable service levels within the given budget and resource constraints. In this paper, a utility approach is proposed for maintenance prioritization purposes based on the condition assessment results of the pavement sections. A pavement network of five sections is considered in this study, and a numerical example is illustrated considering one section to show the implementation of the utility approach for section ranking. The overall assessment of various pavement sections was provided by the inspector as degrees of belief in seven assessment grades, which are: A (Good), B (Satisfactory), C (Fair), D (Poor), E (Very poor), and F (Serious). The assessment of pavement condition and the estimated grade utilities are used to calculate maximum, minimum, and average utilities for each of the five pavement sections. Based on the results, the pavement sections are ranked for maintenance and rehabilitation actions.

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.

scholarly journals Improvement of road pavement maintenance models and technologies

2016 ◽  
Vol 11 (3) ◽  
pp. 242-249 ◽  
Author(s):  
Audrius Vaitkus ◽  
Donatas Čygas ◽  
Algirdas Motiejūnas ◽  
Algis Pakalnis ◽  
Dainius Miškinis
Keyword(s):  
Traffic Safety ◽  
Performance Indicators ◽  
Road Maintenance ◽  
Pavement Condition ◽  
Pavement Maintenance ◽  
Road Pavement ◽  
Condition Evaluation ◽  
High Level ◽  
Ongoing Support ◽  
Whole Life Cycle

The roads as main national assets maintenance costs increase dramatically but budgets stays as it is or even decrease over the years. However, at the same time, it is required to maintain road pavements condition at high level. These trends make asset owners and administrators to search for new ways and methods for more efficient roads maintenance management. As the new road is build or old one reconstructed performance indicators should be identified for whole life cycle as it is defined by design. Pavement condition evaluation by indicating present performance indicators level should be done timely and accurate at road level and whole network level. Ongoing support of pavement condition under network level, with a long-term strategy, allows to prolong the life of the pavement, improve traffic safety and meet public expectations. The comprehensive analysis of road maintenance and management systems recommendations for their improvement and application are presented in the article.

scholarly journals Rutting Model for HMA Overlay Treatment of Composite Pavements

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Mohammad Abdullah Nur ◽  
Mohammad Jamal Khattak ◽  
Mohammad Reza-Ul-Karim Bhuyan
Keyword(s):  
Pavement Management ◽  
Management Tool ◽  
Performance Models ◽  
Factors Affecting ◽  
Pavement Condition ◽  
Pavement Maintenance ◽  
Treatment Performance ◽  
Maintenance And Rehabilitation ◽  
Pavement Service Life ◽  
Good Agreement

Timely rehabilitation and preservation of pavement systems are imperative to maximize benefits in terms of driver’s comfort and safety. However, the effectiveness of any treatment largely depends on the time of treatment and triggers governed by treatment performance models. This paper presents the development of rutting model for overlay treatment of composite pavement in the State of Louisiana. Various factors affecting the rutting of overlay treatment were identified. Regression analysis was conducted, and rut prediction model is generated. In order to better predict the pavement service life, the existing condition of the pavement was also utilized through the model. The developed models provided a good agreement between the measured and predicted rut values. It was found that the predictions were significantly improved, when existing pavement condition was incorporated. The resulting rutting model could be used as a good pavement management tool for timely pavement maintenance and rehabilitation actions to maximize LADOTD benefits and driver’s comfort and safety.

Establishing optimal project-level strategies for pavement maintenance and rehabilitation – A framework and case study

2012 ◽  
Vol 44 (5) ◽  
pp. 565-589 ◽  
Author(s):  
Muhammad Irfan ◽  
Muhammad Bilal Khurshid ◽  
Qiang Bai ◽  
Samuel Labi ◽  
Thomas L. Morin
Keyword(s):  
Pavement Maintenance ◽  
Maintenance And Rehabilitation ◽  
Project Level

Detection of Pavement Maintenance Treatments using Deep-Learning Network

2021 ◽  
pp. 036119812110078
Author(s):  
Lu Gao ◽  
Yao Yu ◽  
Yi Hao Ren ◽  
Pan Lu
Keyword(s):  
Deep Learning ◽  
Measurement Errors ◽  
Short Term Memory ◽  
Learning Networks ◽  
Pavement Maintenance ◽  
Time Period ◽  
Learning Techniques ◽  
Maintenance And Rehabilitation ◽  
History Of ◽  
Deep Learning Network

Pavement maintenance and rehabilitation (M&R) records are important as they provide documentation that M&R treatment is being performed and completed appropriately. Moreover, the development of pavement performance models relies heavily on the quality of the condition data collected and on the M&R records. However, the history of pavement M&R activities is often missing or unavailable to highway agencies for many reasons. Without accurate M&R records, it is difficult to determine if a condition change between two consecutive inspections is the result of M&R intervention, deterioration, or measurement errors. In this paper, we employed deep-learning networks of a convolutional neural network (CNN) model, a long short-term memory (LSTM) model, and a CNN-LSTM combination model to automatically detect if an M&R treatment was applied to a pavement section during a given time period. Unlike conventional analysis methods so far followed, deep-learning techniques do not require any feature extraction. The maximum accuracy obtained for test data is 87.5% using CNN-LSTM.

scholarly journals Performance and Microstructure of Cold Recycled Mixes Using Asphalt Emulsion with Different Contents of Cement

Materials ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 2548 ◽  
Author(s):  
Yanhai Yang ◽  
Ye Yang ◽  
Baitong Qian
Keyword(s):  
Low Temperature ◽  
Temperature Stability ◽  
Hydration Products ◽  
High Temperature Stability ◽  
Asphalt Emulsion ◽  
Moisture Susceptibility ◽  
Pavement Maintenance ◽  
Maintenance And Rehabilitation ◽  
Low Temperature Cracking ◽  
Temperature Crack

Cold recycled mixes using asphalt emulsion (CRME) is an economical and environmentally-friendly technology for asphalt pavement maintenance and rehabilitation. In order to determine the optimum range of cement contents, the complex interaction between cement and asphalt emulsion and the effects of cement on performance of CRME were investigated with different contents of cement. The microstructure and chemical composition of the fracture surface of CRME with different contents of cement were analyzed in this paper as well. Results show that the high-temperature stability and moisture susceptibility of CRME increased with the contents of cement increasing. The low-temperature crack resistance ability gradually increased when the content of cement is increased from 0% to 1.5%. However, it gradually decreased when the content of cement is increased from 1.5% to 4%. Cold recycled mixes had better low-temperature cracking resistance when the contents of cement were in the range from 1% to 2%. The results of microstructure and energy spectrum analysis show that the composite structure is formed by hydration products and asphalt emulsion. The study will be significant to better know the effects of cement and promote the development of CRME.

Development of Structural Condition Index to Support Pavement Maintenance and Rehabilitation Decisions at Network Level

2003 ◽  
Vol 1827 (1) ◽  
pp. 10-17 ◽  
Author(s):  
Zhanmin Zhang ◽  
German Claros ◽  
Lance Manuel ◽  
Ivan Damnjanovic
Keyword(s):  
Evaluation Method ◽  
Surface Condition ◽  
Condition Index ◽  
Structural Condition ◽  
Pavement Management ◽  
Structural Deformation ◽  
Pavement Maintenance ◽  
State Highway ◽  
Structural Reinforcement ◽  
Maintenance And Rehabilitation

Every year, state highway agencies apply large amounts of seal coats and thin overlays to pavements to improve the surface condition, but these measures do not successfully address the problem. Overall pavement condition continues to deteriorate because of the structural deformation of pavement layers and the subgrade. To make effective decisions about the type of treatment needed, one should take into consideration the structural condition of a pavement. Several different structural estimators can be calculated by using falling weight deflectometer data and information stored in the Pavement Management Information System (PMIS) at the Texas Department of Transportation. The analysis considers pavement modulus and structural number as the structural estimators of a pavement. The evaluation method is based on the sensitivity of the structural estimators to deterioration descriptors. The deterioration per equivalent single-axle load of all major scores stored in the Texas PMIS is proposed as the primary indicator of pavement deterioration. In addition, the use of the structural condition index is recommended as a screening tool to discriminate between pavements that need structural reinforcement and those that do not. This index is calibrated for use in maintenance and rehabilitation analysis at the network level.

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