Pavement Deterioration Modeling and Network-Level Pavement Management Using Continuous Deflection Measurements

2021 ◽  
Vol 27 (3) ◽  
pp. 04021022
Author(s):  
Shivesh Shrestha ◽  
Samer W. Katicha ◽  
Gerardo W. Flintsch ◽  
Brian K. Diefenderfer
Keyword(s):  
Pavement Management ◽  
Pavement Deterioration

A semi-Markov formulation of the pavement maintenance optimization problem

1993 ◽  
Vol 20 (3) ◽  
pp. 436-447 ◽  
Author(s):  
Dale M. Nesbit ◽  
Gordon A. Sparks ◽  
Russell D. Neudorf
Keyword(s):  
Pavement Management ◽  
Maintenance Optimization ◽  
Infrastructure Management ◽  
Pavement Maintenance ◽  
Pavement Deterioration ◽  
Maintenance And Rehabilitation ◽  
Computationally Intensive ◽  
Asset Depreciation ◽  
Special Case ◽  
Project Level

The problem of determining optimal pavement maintenance and rehabilitation strategies is a special case of a more general problem termed the asset depreciation problem. Perhaps the most general formulation and solution of the asset depreciation problem is the semi-Markov formulation. This paper illustrates how the semi-Markov formulation and solution of the general asset depreciation problem can be applied to pavements. The semi-Markov formulation, like the Markov formulation, characterizes pavement deterioration probabilistically and represents human intervention (maintenance and rehabilitation) as slowing or modifying the basic probabilities of deterioration. The Markov formulation, first implemented for the state of Arizona, is shown to be a special case of the more general, less computationally intensive semi-Markov formulation. The application of the semi-Markov formulation is illustrated at the project level for a heavy-duty pavement in Manitoba. Key words: asset depreciation, infrastructure management, pavement management, probabilistic modelling, Markov, semi-Markov, maintenance optimization, project level.

scholarly journals ADAPTATION OF PAVEMENT DETERIORATION MODELS TO LITHUANIAN AUTOMOBILE ROADS

2002 ◽  
Vol 8 (3) ◽  
pp. 214-220
Author(s):  
Aivaras Braga ◽  
Donatas Čygas
Keyword(s):  
Management System ◽  
Pavement Management ◽  
System Modelling ◽  
Pavement Management System ◽  
Highway Design ◽  
Road Pavement ◽  
Progression Model ◽  
Incremental Model ◽  
Pavement Deterioration ◽  
Development And Management

The article presents three-system modelling of road pavement deterioration used in Lithuania: HDM-III (Highway Design and Maintenance Standards Model), HDM-4 (Highway Development and Management System) and DAVASEMA—Lithuanian pavement management system developed by Lithuanian Road Administration and based on HDM-III models. Using research data gathered in four years of the programme the authors analyse possibilities of adapting the pavement deterioration models to Lithuanian conditions. The article describes suggested procedures for calculating of calibration coefficients for the pavement deterioration models of the highest importance: road roughness component incremental model, structural cracking initiation model and structural cracking progression model.

scholarly journals HDM-4 Deterioration Modelling: Validation and Adoption for Flexible Pavements With Modified Bituminous Road Surfacing

2019 ◽  
Vol 14 (2) ◽  
pp. 208-226
Author(s):  
Sanjay Deori ◽  
Rajan Choudhary ◽  
Devesh Tiwari ◽  
Abhinay Kumar
Keyword(s):  
High Speed ◽  
Time Series Data ◽  
Asphalt Binder ◽  
Pavement Management ◽  
Series Data ◽  
Local Conditions ◽  
Pavement Distress ◽  
Pavement Deterioration ◽  
Modified Asphalt Binder ◽  
Student’S T

Highway Development and Management (HDM-4) is an internationally recognised tool to analyse pavement management and investment alternatives. The HDM-4 pavement deterioration models help to predict the initiation and progression of various pavement distresses under the different combinations of traffic, climate, pavement structure, and composition. Since the rate of initiation and propagation of each pavement distress is strongly dependent on local conditions, it is essential to calibrate and validate the HDM-4 models for local conditions before their use. Validation of the calibrated HDM-4 pavement deterioration models is needed to check the adequacy of the calibration factors before the model is put to use for future applications. Time series data collected consecutively for three years of 23 high-speed corridors sections constructed with modified binders in India was used to calibrate the HDM-4 distress models. The main aim of this paper is to discuss the validation aspects of the calibrated HDM-4 models, to compare the distresses predicted to those observed on test sections. In this study, a novel technique termed the “proximity to the line of equality” approach is used to validate the HDM-4 models. In addition, Student’s t-test is also used as a conventional validation technique. The advantage of the “proximity to the line of equality” approach is that it removes subjectivity associated with judging the nearness of best-fit straight line of predicted-observed data to the line of equality. Validation results show that distresses predicted by HDM-4 are statistically similar to those observed on the sections. Therefore, the calibrated HDM-4 models can be adopted for planning future maintenance strategies for flexible pavement sections with modified asphalt binder road surfacing.

scholarly journals INVESTIGATION OF AUTOMOBILE ROADS PAVEMENT DETERIORATION TRENDS IN LITHUANIA

2003 ◽  
Vol 9 (1) ◽  
pp. 3-9 ◽  
Author(s):  
Aivaras Braga ◽  
Virgaudas Puodziukas ◽  
Donatas Čygas ◽  
Alfredas Laurinavičius
Keyword(s):  
Input Data ◽  
Asphalt Pavement ◽  
Research Data ◽  
Pavement Management ◽  
Management Systems ◽  
Road Maintenance ◽  
Local Conditions ◽  
Maintenance And Repair ◽  
Pavement Management Systems ◽  
Pavement Deterioration

Currently there are three pavement management systems (PMS) used in Lithuania for planning and management of road maintenance and repair activities: HDM-III, HDM-4 and DAVASEMA (Lithuanian PMS). HDM pavement deterioration models are used in all of them. With the purpose of calibration and adaptation of those models in 1997 Lithuanian Pavement Deterioration Research Project was developed. The research data gathered in four years of the Project gives an opportunity to draw some conclusions on asphalt pavement deterioration in Lithuania. This article presents the main HDM asphalt pavement deterioration models, and describes the most important steps in adaptation of some input data to those models and calibration of the models to the local conditions.

Incorporating pavement deterioration uncertainty into pavement management optimization

2020 ◽  
pp. 1-12 ◽  
Author(s):  
Tatiana García-Segura ◽  
Laura Montalbán-Domingo ◽  
David Llopis-Castelló ◽  
Michael D. Lepech ◽  
M. Amalia Sanz ◽  
...  
Keyword(s):  
Pavement Management ◽  
Pavement Deterioration ◽  
Management Optimization

Investigation of Relationship Between Deterministic and Probabilistic Prediction Models in Pavement Management

1997 ◽  
Vol 1592 (1) ◽  
pp. 70-79 ◽  
Author(s):  
Ningyuan Li ◽  
Ralph Haas ◽  
Wei-Chau Xie
Keyword(s):  
Probabilistic Models ◽  
Prediction Models ◽  
Transition Probability ◽  
Model Development ◽  
Flexible Pavement ◽  
Pavement Management ◽  
Probabilistic Prediction ◽  
Deterministic Models ◽  
Pavement Deterioration ◽  
Probability Matrices

A good pavement management system should have the capacity to predict pavement structural and functional deterioration versus age or accumulated traffic loading. Basically, there are two types of performance prediction models in pavement management: deterministic and probabilistic. Although both performance models can be used to predict pavement deterioration, the inherent relationship between the two models has not been explored. An investigation was directed to find the relationship in terms of system conversion. Some of the findings related to system conversion, including the concepts and techniques applied in model conversion, the characteristics of model development, comparisons of prediction results between the two models, sensitivity analysis of the probabilistic models, and sample applications in real situations, are highlighted. The deterministic models that are to be converted to probabilistic models are the flexible pavement deterioration model used in the Ontario Pavement Analysis of Costs system and the flexible pavement design model recommended in the 1993 AASHTO design guide. The converted probabilistic models are time-related (nonhomogeneous) Markov processes, which are represented by a set of yearly transition probability matrices (TPMs). TPMs can be established for any individual pavement section in a road network.

Economic Value of Pavement for the Elderly: Case Study of Bangkok, Thailand

2018 ◽  
Vol 9 (11) ◽  
pp. 927-937
Author(s):  
Somskaow Bejranonda ◽  
◽  
Aekkapat Laksanacom ◽  
Waranan Tantiwat ◽  
◽  
...  
Keyword(s):  
Contingent Valuation Method ◽  
Economic Value ◽  
The Elderly ◽  
Pavement Management ◽  
Sustainable Urban Development ◽  
Public Facility ◽  
Average Value ◽  
Valuation Method ◽  
The People ◽  
The City

Based on the concept of a livable and global age-friendly city, pavements are a public facility that the city should provide to the people. Appropriate pavements will be beneficial for the people, particularly for good quality of life for the elderly to move around in the city. This study explored the behaviour of the elderly in the use of pavements and the problems confronted. The study also evaluated the value of the pavement walking area as it reflected the benefits of pavements to the elderly by applying the Contingent Valuation Method (CVM). During March-May 2017, data were collected using interviews with 601 elderly living in Bangkok. The study indicated that the main problem for senior citizens regarding their use of pavements was from being disturbed by motorbikes riding on the pavements. The average value of pavement for the elderly was about THB 160 (USD 5.30) per person per year. Thus, the benefits of pavements to the elderly in Bangkok was approximately THB 158 million (USD 5.2 million) per year. Thus, policy makers should make proper budget allocations for elderly-friendly pavement management and seriously address the problems confronting the elderly in using pavements, to maximize the usefulness of pavements not only for the elderly but also for the public and to support a sustainable urban development.

Local Calibration of Pavement Mechanistic-Empirical Faulting Reliability using Pavement Management Data

2021 ◽  
pp. 036119812110013
Author(s):  
Lucio Salles de Salles ◽  
Lev Khazanovich
Keyword(s):  
Model Calibration ◽  
Prediction Models ◽  
Plain Concrete ◽  
Performance Model ◽  
Pavement Management ◽  
Pavement Design ◽  
Reliability Model ◽  
Transverse Joint ◽  
Design Characteristics ◽  
And Performance

The Pavement ME transverse joint faulting model incorporates mechanistic theories that predict development of joint faulting in jointed plain concrete pavements (JPCP). The model is calibrated using the Long-Term Pavement Performance database. However, the Mechanistic-Empirical Pavement Design Guide (MEPDG) encourages transportation agencies, such as state departments of transportation, to perform local calibrations of the faulting model included in Pavement ME. Model calibration is a complicated and effort-intensive process that requires high-quality pavement design and performance data. Pavement management data—which is collected regularly and in large amounts—may present higher variability than is desired for faulting performance model calibration. The MEPDG performance prediction models predict pavement distresses with 50% reliability. JPCP are usually designed for high levels of faulting reliability to reduce likelihood of excessive faulting. For design, improving the faulting reliability model is as important as improving the faulting prediction model. This paper proposes a calibration of the Pavement ME reliability model using pavement management system (PMS) data. It illustrates the proposed approach using PMS data from Pennsylvania Department of Transportation. Results show an increase in accuracy for faulting predictions using the new reliability model with various design characteristics. Moreover, the new reliability model allows design of JPCP considering higher levels of traffic because of the less conservative predictions.

scholarly journals Exploiting Data Analytics and Deep Learning Systems to Support Pavement Maintenance Decisions

2021 ◽  
Vol 11 (6) ◽  
pp. 2458
Author(s):  
Ronald Roberts ◽  
Laura Inzerillo ◽  
Gaetano Di Mino
Keyword(s):  
Deep Learning ◽  
Management Practices ◽  
Prediction Models ◽  
Road Networks ◽  
Pavement Management ◽  
Efficient Operation ◽  
Pavement Maintenance ◽  
Goods And Services ◽  
Maintenance Decisions ◽  
Computational Systems

Road networks are critical infrastructures within any region and it is imperative to maintain their conditions for safe and effective movement of goods and services. Road Management, therefore, plays a key role to ensure consistent efficient operation. However, significant resources are required to perform necessary maintenance activities to achieve and maintain high levels of service. Pavement maintenance can typically be very expensive and decisions are needed concerning planning and prioritizing interventions. Data are key towards enabling adequate maintenance planning but in many instances, there is limited available information especially in small or under-resourced urban road authorities. This study develops a roadmap to help these authorities by using flexible data analysis and deep learning computational systems to highlight important factors within road networks, which are used to construct models that can help predict future intervention timelines. A case study in Palermo, Italy was successfully developed to demonstrate how the techniques could be applied to perform appropriate feature selection and prediction models based on limited data sources. The workflow provides a pathway towards more effective pavement maintenance management practices using techniques that can be readily adapted based on different environments. This takes another step towards automating these practices within the pavement management system.

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