Utility-Based Road Maintenance Prioritization Method Using Pavement Overall Condition Rating
DOI:
https://doi.org/10.7250/bjrbe.2020-15.464Keywords:
decision, distress, maintenance, pavement, road, utilityAbstract
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.
References
ASTM. (2008). Standard Practice for Roads and Parking Lots Pavement Condition Index Surveys (D 6433 – 07).
Abu Dabous, S. (2017). Assessing transition probability of bridge deterioration using Dempster – Shafer theory of evidence. Bridge Structures, 12(3-4), 97–106. https://doi.org/10.3233/BRS-170105
Abu Dabous, S. & Al-Khayyat, G. (2018). A Flexible Bridge Rating Method Based on Analytical Evidential Reasoning and Monte Carlo Simulation. Advances in Civil Engineering, 2018, 1–13. https://doi.org/10.1155/2018/1290632
Abu Dabous, S., Zeiada, W., Al-Ruzouq, R., Hamad, K., & Al-Khayyat, G. (2019). Distress-based evidential reasoning method for pavement infrastructure condition assessment and rating. International Journal of Pavement Engineering, 1–12. https://doi.org/10.1080/10298436.2019.1622012
Babashamsi, P., Golzadfar, A., Yusoff, N. I. M., Ceylan, H., & Nor, N. G. M. (2016). Integrated fuzzy analytic hierarchy process and VIKOR method in the prioritization of pavement maintenance activities. International Journal of Pavement Research and Technology, 9(2), 112–120. https://doi.org/10.1016/j.ijprt.2016.03.002
Chang, J. R. (2013). Particle Swarm Optimization Method for Optimal Prioritization of Pavement Sections for Maintenance and Rehabilitation Activities. Applied Mechanics and Materials, 343, 43–49. https://doi.org/10.4028/www.scientific.net/AMM.343.43
Chouinard, B. L. E., Andersen, G. R., & Torrey, V. H. (1996). Ranking Models Used for Condition Assessment of Civil Infrastructure Systems. Journal of Infrastructure Systems, 2(1), 23–29. https://doi.org/10.1061/(asce)1076-0342(1996)2:1(23)
Dempster, A. (1968). A generalisation of Bayesian inference. Journal of Royal Statistical Society, Series B, 30(2), 205–247.
El-rayes, K., & Kandil, A. (2005). Time-Cost-Quality Trade-Off Analysis for Highway Construction. Journal of Construction Engineering and Managementment, 131(4), 477–486. https://doi.org/10.1061/(asce)0733-9364(2005)131:4(477)
Fwa, T. F., & Chan, W. T. (1993). Priority Rating Of Highway Maintenance Needs By Neural Networks. Journal of Transportation Engineering, 119(3), 419–432. https://doi.org/10.1061/(asce)0733-947x(1993)119:3(419)
Fwa, T. F., Chan, W. T., & Hoque, K. Z. (1998). Analysis of Pavement Management Activities Programming by Genetic Algorithms. Transportation Research Record, 1643, 1–6. https://doi.org/10.3141/1643-01
Gao, L., Xie, C., & Zhang, Z. (2012). Network-Level Road Pavement Maintenance and Rehabilitation Scheduling for Optimal Performance Improvement and Budget Utilization. Computer-Aided Civil and Infrastructure Engineering, 27(4), 276–287. https://doi.org/10.1111/j.1467-8667.2011.00733.x
Haas, R., Hudson, W. R., & Zaniewski, J. (1994). Modern pavement management.
Malabar, FL: Krieger. Hudson, W. R., Haas, R., & Pedigo, R. D. (1979). Pavement management system development. Washington: Transportation Research Board.
Moazami, D., Behbahani, H., & Muniandy, R. (2011). Pavement rehabilitation and maintenance prioritization of urban roads using fuzzy logic. Expert Systems With Applications, 38(10), 12869–12879. https://doi.org/10.1016/j.eswa.2011.04.079
Ouma, Y. O., Opudo, J., & Nyambenya, S. (2015). Comparison of Fuzzy AHP and Fuzzy TOPSIS for Road Pavement Maintenance Prioritization: Methodological Exposition and Case Study. Advances in Civil Engineering, 2015, 1–17. https://doi.org/10.1155/2015/140189
Reddy, B. B., & Veeraragavan, A. (2001). Priority ranking model for managing flexible pavements at network level. Journal of Indian Road Congress, 62, 379–394.
Shafer, G. (1976). A Mathematical Theory of Evidence. Princeton, NJ, USA: Princeton University Press.
Shah, Y. U., Jain, S. S., & Parida, M. (2014). Evaluation of prioritization methods for effective pavement maintenance of urban roads. International Journal of Pavement Engineering, 15(3), 238–250. https://doi.org/10.1080/10298436.2012.657798
Sun, L., & Gu, W. (2011). Pavement Condition Assessment Using Fuzzy Logic Theory and Analytic Hierarchy Process. Journal of Transportation Engineering, 137(9), 648–655. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000239
Tayebi, N. R., Moghadasnejhad, F., & Hassani, A. (2010). Analysis of pavement management activities programming by particle swarm optimization. International Journal on Communication.
Temesgen Girmay. (2016). Asphalt Road Pavement Rehabilitation and Maintenance: Case Study in Addis Ababa City Roads Authority. The Ohio Department of Transportation and U.S. Department of Transportation, F. H. A. (1998). Review of PCR Methodology.
Torres-machí, C., Chamorro, A., Videla, C., Pellicer, E., & Yepes, V. (2014). An Iterative Approach for the Optimization of Pavement Maintenance Management at the Network Level. The Scientific World Journal, 2014, 1–11. https://doi.org/10.1155/2014/524329
Wang, Y. M., & Elhag, T. M. S. (2008). Evidential reasoning approach for bridge condition assessment. Expert Systems with Applications, 34(1), 689–699. https://doi.org/10.1016/j.eswa.2006.10.006
Wang, Y., Yang, J.-B., & Xu, D.-L. (2006). Environmental impact assessment using the evidential reasoning approach. European Journal of Operational Research, 174(3), 1885–1913. https://doi.org/10.1016/j.ejor.2004.09.059
Xiong, Y., & Kuang, Y. P. (2007). Time-cost trade-off of construction project based on ant colony algorithm. System Engineering Theory and Practice, 27, 105–111.
Yang, J.-B., & Xu, D.-L. (2002). On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty. IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, 32(3), 289–304. https://doi.org/10.1109/TSMCA.2002.802746
Zheng, D. X. M., & Ng, S. T. (2005). Stochastic Time–Cost Optimization Model Incorporating Fuzzy Sets Theory and Nonreplaceable Front. Journal of Construction Engineering and Management, 131(2), 176–186. https://doi.org/10.1061/(asce)0733-9364(2005)131:2(176)
Zheng, D. X. M., Ng, S. T., & Kumaraswamy, M. M. (2004). Applying a Genetic Algorithm-Based Multiobjective Approach for Time-Cost Optimization. Journal of Construction Engineering and Management, 130(2), 168–176. https://doi.org/10.1061/(ASCE)0733-9364(2004)130:2(168)
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Copyright (c) 2020 Saleh Abu Dabous, Ghadeer Al-Khayyat, Sainab Feroz
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