Prediction of Pavement Maintenance Performance Using an Expert System
The pavement experiences deterioration due to traffic and environment, i.e., unsatisfactory riding quality and structural inadequacy, over time. Thus, predicting pavement performance over time is one of the key elements of any pavement maintenance management system (PMMS). It can be used as an effic...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-05-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/12/10/4802 |
| _version_ | 1797501915839332352 |
|---|---|
| author | Abdullah Al-Mansour Kang-Won Wayne Lee Abdulraaof H. Al-Qaili |
| author_facet | Abdullah Al-Mansour Kang-Won Wayne Lee Abdulraaof H. Al-Qaili |
| author_sort | Abdullah Al-Mansour |
| collection | DOAJ |
| description | The pavement experiences deterioration due to traffic and environment, i.e., unsatisfactory riding quality and structural inadequacy, over time. Thus, predicting pavement performance over time is one of the key elements of any pavement maintenance management system (PMMS). It can be used as an efficient tool to program/schedule the maintenance applications and expenditures, and thus the necessary funds can be allocated. Using a combination of independent variables for any selected pavement section can generate section-wise condition assessment and prediction models. Moreover, these models can be used to select the most cost-effective maintenance alternative to be applied to that pavement section. The present study developed an expert system based on pavement performance models which combines the available maintenance data with the knowledge acquired from the experts of the General Administration of Operation and Maintenance in Riyadh, Saudi Arabia. Eight regression models were first developed for four maintenance and rehabilitation (M&R) strategies, i.e., no maintenance, routine maintenance, overlay, and reconstruction for low and high traffic. Then, a practical expert system was developed to aid pavement maintenance engineers in finding the most effective and efficient M&R strategies and suitable time for the application. The regression models revealed that the effect of routine maintenance and reconstruction is greater in low traffic than in high traffic, while the effect of overlay is greater in high traffic than in low traffic. Based on this initial system, another improved one can be developed using the machine learning technique. |
| first_indexed | 2024-03-10T03:25:26Z |
| format | Article |
| id | doaj.art-783036aa5abf4e93bf93446a6a7d9f62 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T03:25:26Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-783036aa5abf4e93bf93446a6a7d9f622023-11-23T09:53:24ZengMDPI AGApplied Sciences2076-34172022-05-011210480210.3390/app12104802Prediction of Pavement Maintenance Performance Using an Expert SystemAbdullah Al-Mansour0Kang-Won Wayne Lee1Abdulraaof H. Al-Qaili2Civil Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi ArabiaCivil and Environmental Engineering Department, College of Engineering, University of Rhode Island, Kingston, RI 02881, USACivil Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi ArabiaThe pavement experiences deterioration due to traffic and environment, i.e., unsatisfactory riding quality and structural inadequacy, over time. Thus, predicting pavement performance over time is one of the key elements of any pavement maintenance management system (PMMS). It can be used as an efficient tool to program/schedule the maintenance applications and expenditures, and thus the necessary funds can be allocated. Using a combination of independent variables for any selected pavement section can generate section-wise condition assessment and prediction models. Moreover, these models can be used to select the most cost-effective maintenance alternative to be applied to that pavement section. The present study developed an expert system based on pavement performance models which combines the available maintenance data with the knowledge acquired from the experts of the General Administration of Operation and Maintenance in Riyadh, Saudi Arabia. Eight regression models were first developed for four maintenance and rehabilitation (M&R) strategies, i.e., no maintenance, routine maintenance, overlay, and reconstruction for low and high traffic. Then, a practical expert system was developed to aid pavement maintenance engineers in finding the most effective and efficient M&R strategies and suitable time for the application. The regression models revealed that the effect of routine maintenance and reconstruction is greater in low traffic than in high traffic, while the effect of overlay is greater in high traffic than in low traffic. Based on this initial system, another improved one can be developed using the machine learning technique.https://www.mdpi.com/2076-3417/12/10/4802pavement maintenance management systemexpert systempavement performancecost-effective maintenance alternatives |
| spellingShingle | Abdullah Al-Mansour Kang-Won Wayne Lee Abdulraaof H. Al-Qaili Prediction of Pavement Maintenance Performance Using an Expert System Applied Sciences pavement maintenance management system expert system pavement performance cost-effective maintenance alternatives |
| title | Prediction of Pavement Maintenance Performance Using an Expert System |
| title_full | Prediction of Pavement Maintenance Performance Using an Expert System |
| title_fullStr | Prediction of Pavement Maintenance Performance Using an Expert System |
| title_full_unstemmed | Prediction of Pavement Maintenance Performance Using an Expert System |
| title_short | Prediction of Pavement Maintenance Performance Using an Expert System |
| title_sort | prediction of pavement maintenance performance using an expert system |
| topic | pavement maintenance management system expert system pavement performance cost-effective maintenance alternatives |
| url | https://www.mdpi.com/2076-3417/12/10/4802 |
| work_keys_str_mv | AT abdullahalmansour predictionofpavementmaintenanceperformanceusinganexpertsystem AT kangwonwaynelee predictionofpavementmaintenanceperformanceusinganexpertsystem AT abdulraaofhalqaili predictionofpavementmaintenanceperformanceusinganexpertsystem |