ارایه مدل پیش‌بینی شاخص وضعیت روسازی با استفاده از مقادیر شاخص بین‌المللی ناهمواری مطالعه موردی آزادراه‌های منتخب ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

• سید عظیم حسینی ¹
• مسعود صبائی ¹
• سید امیر سعادتجو ²
• سعید فاطمی ³
• سید علی ضیائی ⁴

¹ دانشکده مهندسی عمران، دانشگاه آزاد اسلامی واحد تهران جنوب، تهران، ایران.

² دانشکده مهندسی عمران، دانشگاه علم و صنعت ایران

³ گروه مهندسی عمران، دانشکده مهندسی، دانشگاه فردوسی مشهد، مشهد، ایران

⁴ گروه مهندسی عمران، دانشکده مهندسی، دانشگاه فردوسی مشهد، مشهد، ایران.

10.22067/jfcei.2022.73899.1097

چکیده

یکی از مؤلفه‌های مهم در یک سیستم مدیریت روسازی و برنامه­ریزی منابع مالی جهت ترمیم و نگهداری آن­ها، ارزیابی قابل اعتماد و دقیق از وضع موجود شبکه روسازی است که شامل محاسبه پارامترهای خدمت رسانی مانند شاخص بین‌المللی ناهمواری (IRI) و شاخص وضعیت روسازی (PCI)، در طول دوره عملکرد روسازی می‌باشد. محاسبه میدانی شاخص PCI و تا حدودی شاخص IRI کمی دشوار و پیچیده است. لذا استفاده از مدل­های عددی جهت تخمین این پارامترها ضرورت دارد. در این مطالعه، مقادیر اندازه‌گیری شده شاخص‌های PCI و IRI مربوط به پنج آزادراه مختلف در ایران مورد استفاده قرار گرفت و دقت ارزیابی مدل­های مختلف ریاضی ارائه شده در نقاط مختلف جهان بر روی آن­ها بررسی گردید. سپس برای پیش بینی داده­های PCI با استفاده از مقادیر ورودی IRI، یک مدل ریاضی جدید معرفی گردید. نتایج بررسی‌ دقت پیش بینی مدل‌ها نشان داد برای تمامی آزادراه­های مورد مطالعه، مدل پیشنهادی از تمام مدل­هایی که تا کنون توسط محققین مختلف در دنیا ارائه شده‌است عملکرد بهتری از خود نشان داد. استفاده از این مدل می­تواند پیش بینی پارامتر PCI با استفاده از مقادیر ورودی شاخص IRI را برای شبکه آزادراهی کشور میسر سازد و مدیریت روسازی آزادراه­ها و برنامه ریزی عملیات ترمیم و نگهداری آن‌ها را با هزینه کم­تری تسهیل نماید.

کلیدواژه‌ها

• شاخص وضعیت روسازی
• شاخص بین‌المللی ناهمواری
• مدیریت روسازی
• ترمیم و نگهداری

20.1001.1.27832805.1400.34.4.6.4

---

عنوان مقاله [English]

A Prediction Model for the Pavement Condition Index Using the International Roughness Index: A Case Study of 5 Selected Freeways in Iran.

نویسندگان [English]

• Seyed Azim Hosseini ¹
• Masoud Sabaee ¹
• Seyed Amir Saadatjoo ²
• Saeed Fatemi ³
• Seyed Ali Ziaee ⁴

¹ Department of Civil Engineering, Faculty of Engineering, Qom University of Azad university, south branch ,Tehran,, Iran

² Faculty of Civil Engineering, Iran University of Science and Technology

³ Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

⁴ Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.

چکیده [English]

Reliable and accurate assessment of the condition of the pavement network such as International Ruggedness Index (IRI) and pavement condition index (PCI) is one of the most important components in a pavement management system. This issue is very effective in managing and planning financial resources to maintain road pavement. However, calculating PCI and IRI parameters are difficult and complicated. Therefore, it is necessary to use numerical models to estimate these parameters. In this study, PCI and IRI data related to five different freeways in Iran were used and different mathematical models were investigated. Afterwards, a model for estimating PCI data from IRI was introduced, which had an acceptable correlation between these data in all the freeways studied and Showed better performance than out of all the models presented by various researchers in the world which mentioned in this article. The use of this model can make it possible to estimate the PCI parameter for the freeway networks, and as a result, the management of freeway pavements and planning for maintenance operations will be facilitated at a lower cost.

کلیدواژه‌ها [English]

• Pavement Condition Index
• International Roughness Index
• Pavement Management
• Repair and Maintenance

مراجع

1. Adeli, S, Salehfard, R., and Amini, B., "The Influence of Asphalt Mixture Components on Pavement Skid Resistance and Accident Rate in Urban Un-Signalized Intersections", International Journal of Pavement Research and Technology, 43, pp 1–11 (2021).
2. Wotring, D. C., Baladi, G. Y., Buch, N., and Bower, S., "Pavement Distress and Selection of Rehabilitation Alternatives: Michigan Practice", Transportation research record, Vol. 1629(1), pp 214–25, (1998).
3. ASTM, D., "Standard Practice for Roads and Parking Lots Pavement Condition Index Surveys.", (2009).
4. Shah, Y. U., Devesh Tiwari, S. J., and Jain, M. K., "Development of Overall Pavement Condition Index for Urban Road Network", Procedia-Social and Behavioral Sciences, Vol. 104, pp 332–341 ,(2013).
5. Olidis, C., and Hein, D., "Guide for the Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures Materials Characterization: Is Your Agency Ready", Annual Conference of the Transportation Association of Canada, Citeseer, (2004).
6. Perera, R. W, and S D Kohn., "Issues in Pavement Smoothness", NCHRP Web Document 42, (2002).
7. Robbins, M., and Tran, N., "A Synthesis Report: Value of Pavement Smoothness and Ride Quality to Roadway Users and the Impact of Pavement Roughness on Vehicle Operating Costs", National Center for Asphalt Technology (NCAT) at Auburn University, NCAT Report 16-03, pp 3–16, (2016).
8. Mactutis, J. A., Alavi, H., and Ott,W., "Investigation of Relationship between Roughness and Pavement Surface Distress Based on WesTrack Project", Transportation research record, Vol. 1699(1), pp 107–13, (2000).
9. Yousefzadeh, M., Azadi, S., and Soltani, A., "Road Profile Estimation Using Neural Network Algorithm", Journal of mechanical science and technology, Vol. 24(3), pp 743–54, (2010).
10. Lin, J.D., Yau, J.T., and Hsiao, L.H., "Correlation Analysis between International Roughness Index (IRI) and Pavement Distress by Neural Network", In 82nd Annual Meeting of the Transportation Research Board, ???, pp 12–16, (2003).
11. Vidya, R., Santhakumar, M., and Mathew, S., "Estimation of IRI from PCI in Construction Work Zones", International Journal on Civil and Environmental Engineering, Vol. 3(1), pp 1-5, (2013).
12. Abdelaziz, N., El-Hakim, R.T., El-Badawy, S., and Afify, H., "International Roughness Index Prediction Model for Flexible Pavements", International Journal of Pavement Engineering, Vol. 21(1), pp 88–99, (2020).
13. El-Hakim, R.T., Abd, H., "Validation and Improvement of Pavement ME Flexible Pavement Roughness Prediction Model Using Extended LTPP Database", (2017).
14. Shahin, M., and Kohn, S., "Development of a Pavement Condition Rating Procedure for Roads, Streets, and Parking Lots. Volume I. Conditions Rating Procedure", Construction Engineering Research Lab Champaign, (1979).
15. Di Mascio, P., Piccolo, I., and Cera, L., "Automated Distress Evaluation", In Proceedings of 4th International SIIV Congress, Palermo, Italy, 17(2), pp12–14, (2007).
16. Wang, K., "Network Level Pavement Evaluation with 1 Mm 3D Survey System", Journal of traffic and transportation engineering (English edition), Vol. 2(6), pp 391–98, (2015).
17. Dewan, S.A., Smith, R.E., "Estimating IRI from Pavement Distresses to Calculate Vehicle Operating Costs for the Cities and Counties of San Francisco Bay Area", Transportation Research Record, (2002).
18. Park, K., Thomas, N.E., and Lee, K., "Applicability of the International Roughness Index as a Predictor of Asphalt Pavement Condition", Journal of Transportation Engineering, Vol. 133(12), pp 706–9, (2007).
19. Arhin, S.A., Williams, L., Ribbiso, A., and Anderson, M., "Predicting Pavement Condition Index Using International Roughness Index in a Dense Urban Area", Journal of Civil Engineering Research, Vol. 5(1), pp 10–17, (2015).
20. Elhadidy, A., El-Badawy, H., and Elbeltagi, E., "A Simplified Pavement Condition Index Regression Model for Pavement Evaluation" International Journal of Pavement Engineering, 22(5), pp 1–10, (2019).
21. Adeli, S., "Development of a Relationship between Pavement Condition Index and International Roughness Index in Rural Road Network", Advances in Civil Engineering, (2021).
22. Gilani, V., Hosseinian, S.M., Behbahani, H., and Hamedi, G., "Prediction and Pareto-Based Multi-Objective Optimization of Moisture and Fatigue Damages of Asphalt Mixtures Modified with Nano Hydrated Lime", Construction and Building Materials 261 120509, (2020).
23. Behbahani, H., Hamedi, G., and Gilani, V., "Predictive Model of Modified Asphalt Mixtures with Nano Hydrated Lime to Increase Resistance to Moisture and Fatigue Damages by the Use of Deicing Agents", Construction and Building Materials 265: 120353, (2020).