Comparison of Pavement Performance Models for Urban Road Management System

Igoris Kravcovas, Audrius Vaitkus, Rita Kleizienė


The key factors for effective pavement management system (PMS) are timely preservation and rehabilitation activities, which provide benefit in terms of drivers’ safety, comfort, budget and impact on the environment. In order to reasonably plan the preservation and rehabilitation activities, the pavement performance models are used. The pavement performance models are usually based on damage and distress observations of rural roads, and can be applied to forecast the performance of urban roads. However, the adjustment of the parameters related to traffic volume, speed and load, climate conditions, and maintenance has to be made before adding them to PMS for urban roads. The main objective of this study is to identify the performance indicators and to suggest pavement condition establishment methodology of urban roads in Vilnius. To achieve the objective, the distresses (rut depth and cracks), bearing capacity, and international roughness index (IRI) were measured for fifteen urban roads in service within a two-year period. The distresses, rut depth and IRI were collected with the Road Surface Tester (RST) and bearing capacity of pavement structures were measured with a Falling Weight Deflectometer (FWD). The measured distresses were compared to the threshold values identified in the research. According to the measured data, the combined pavement condition indices using two methodologies were determined, as well as a global condition index for each road. The analysed roads were prioritized for maintenance and rehabilitation in respect to these criteria. Based on the research findings, the recommendations for further pavement condition monitoring and pavement performance model implementation to PMS were highlighted.


bearing capacity; international roughness index; pavement condition index; pavement distress; pavement management system; pavement performance model

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AASHTO. (1993). AASHTO Guide for Design of Pavement Structures.

AASHTO. (2004). Chapter 6: HMA Rehabilitation of Existing Pavement. In Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures, Part 3.

Adlinge, S. S., & Gupta, A. K. (2013). Pavement Deterioration and Its Causes. Journal of Mechanical & Civil Engineering, 9–15.

Baladi, G. Y., Dawson, T., Musunuru, G., Prohaska, M., & Thomas, K. (2017). Pavement Performance Measures and Forecasting and the Effects of Maintenance and Rehabilitation Strategy on Treatment Effectiveness (Revised). Publication No. FHWA-HRT-17-095. In Distribution (Issue September).

COST. (2008). COST Action 354. Performance Indicators for Road Pavements. Final Report. (Issue July).

Ellingwood, B. R. (2005). Risk-informed condition assessment of civil infrastructure: state of practice and research issues. Structure and Infrastructure Engineering, 1(1), 7–18.

Gavilán, M., Balcones, D., Marcos, O., Llorca, D. F., Sotelo, M. A., Parra, I., Ocaña, M., Aliseda, P., Yarza, P., & Amírola, A. (2011). Adaptive road crack detection system by pavement classification. Sensors, 11(10), 9628–9657.

Haas, R., Hudson, W. R., & Falls, L. C. (2015). Pavement Asset Management.

Huang, Y. H. (2004). Pavement analysis and design (2nd edition).

Huidrom, L., Das, L. K., & Sud, S. K. (2013). Method for Automated Assessment of Potholes, Cracks and Patches From Road Surface Video Clips. Procedia – Social and Behavioral Sciences, 104, 312–321.

Ismail, N., Ismail, A., & Atiq, R. (2009). An Overview of Expert Systems in Pavement Management. European Journal of Scientific Research, 30(1), 99–111.

Kirbaş, U., & Karaşahin, M. (2016). Performance Models for Hot Mix Asphalt Pavements in Urban Roads. Construction and Building Materials, 116, 281–288.

Koch, C., & Brilakis, I. (2011). Pothole Detection in Asphalt Pavement Images. Advanced Engineering Informatics, 25(3), 507–515.

Lietuvos automobilių kelių direkcija. (2017). Valstybinės reikšmės kelių pažaidų matavimo ir nustatymo tvarkos aprašas. 6, 25.

Lietuvos automobilių kelių direkcija. (2018). Valstybinės reikšmės kelių dangos būklės vertinimo tvarkos aprašas. 16(V).

Lovas, T., Kertész, I., Fi, I., & Barsi, A. (2008). Photogrammetric pavement detection system. In I. L. Al-Qadi, T. Scarpas, A. Loizos (Eds.), Pavement Cracking: Mechanisms, Modeling, Detection, Testing and Case Histories (pp. 873–880, Figure 2).

Marcelino, P., Lurdes Antunes, M. de, & Fortunato, E. (2018). Comprehensive performance indicators for road pavement condition assessment. Structure and Infrastructure Engineering, 14(11), 1433–1445.

Matini, N., Tabatabaee, N., & Abbasghorbani, M. (2018). Protocol for FWD Data Collection at Network-Level Pavement Management in Iran. Transportation Research Record, 2672(40), 68–77.

Osorio, A. (2015). Development of Performance Models and Maintenance Standards of Urban Pavements for Network Management (Doctoral thesis). University of Waterloo.

Pinkofsky, L., & Jansen, D. (2018). Structural pavement assessment in Germany. Frontiers of Structural and Civil Engineering, 12(2), 183–191.

Ragnoli, A., De Blasiis, M. R., Di Benedetto, A., Blasiis, M. R. De, & Benedetto, A. Di. (2018). Pavement Distress Detection Methods: A Review. Infrastructures, 3(4), 58.

Savivaldybės įmonė “Vilniaus planas”. (2009). Vilniaus miesto savivaldybės teritorijos bendrasis planas iki 2015 metų.

Shah, Y. U., Jain, S. S., Tiwari, D., & Jain, M. K. (2013). Development of Overall Pavement Condition Index for Urban Road Network. Procedia – Social and Behavioral Sciences, 104, 332–341.

Singh, A. P., Sharma, A., Mishra, R., Wagle, M., & Sarkar, A. K. (2018). Pavement condition assessment using soft computing techniques. International Journal of Pavement Research and Technology, 11(6), 564–581.

Singh, A., & Chopra, T. (2018). Development of Pavement Maintenance Management System for the Urban Road Netwrok By Calibrating the HDM-4 Distress Models. In International Conference on Pavements and Computational Approaches (ICOPAC) (pp. 239–241).

Sivilevičius, H., & Vansauskas, V. (2013). Research and evaluation of ruts in the asphalt pavement on Lithuanian highways. Journal of Civil Engineering and Management, 19(5), 609–621.

Sohail, F., Dossey, T., & Hudson, W. R. (1996). Implementation of the Urban Roadway Management System. Report.

Stampley, B. E., Miller, B., Smith, R. E., & Scullion, T. (1995). Pavement management information system concepts, equations, and analysis models. TX-96/1989-1. Report No. TX-96/1989-1.

Sun, L., & Gu, W. (2011). Pavement condition assessment using fuzzy logic theory and analytic hierarchy process. Journal of Transportation Engineering, 137(9), 648–655.

The Ohio Department of Transportation. (2006). Pavement condition rating system.

TKTI. (1994). Asfaltbetonio dangų defektų nustatymo metodika.

Wang, T., Gopalakrishnan, K., Smadi, O., & Somani, A. K. (2018). Automated shape-based pavement crack detection approach. Transport, 33(3), 598–608.

Xu, B., & Huang, Y. (2005). Automatic inspection of pavement cracking distress. Applications of Digital Image Processing XXVIII, 5909(22), 590901.

Ziliute, L., Laurinavicius, A., & Kleiziene, R. (2011). Investigation and analysis of heavyweight traffic running loads in streets of Vilnius city. In 8th International Conference on Environmental Engineering (pp. 1261–1267).

DOI: 10.7250/bjrbe.2020-15.487


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