Performance Assessment of Flexible Pavements: Fuzzy Evidence Theory Approach

Shruti Wadalkar, Ravindra K. Lad, Rakesh K. Jain


Pavement performance evaluation is one of the most important steps of the pavement management system. It consists of identifying pavement condition according to various distresses occurs in the pavement surface. Data collection in performance assessment of road is done in several ways. An attempt has been made to address the problem and a new formalism is proposed for performance assessment of flexible pavements. Vagueness in the perception of expert for performance assessment of pavement based on techno-scientific parameters in linguistic terms for the domain base usage coupled with impression in parametric data calls for the application of fuzzy modeling. For this study fuzzy evidence theory weightage method “Dempster’s Shafer’s (D-S)” is applied to determine the Pavement Condition Distress Index (PCDI) of flexible pavement. D-S theory provides a designed framework to overcome the risk of uncertainty and ignorance. For the assessment of pavements five major structural indicators like longitudinal cracks, transverse cracks etc. and eleven major functional indicators like potholes, rutting, patching etc. are considered. Expert opinion is taken from the experts who are involved in the field of transportation engineering. Questionnaire Survey methodology has been adopted for the collection of experts opinions. Five linguistic terms are used for the same, which are, ‘Very important’, ‘Important’, ‘Average’, ‘Less important’ and ‘Not Important’. Based on PCDI, Pavement Condition Index (PCI) is calculated. The rating of flexible pavements is also done based on PCI. For the application of the model, five road segments of MIDC Chakan, Pune area is considered. PCI of all the road segments is determined by using the stated index. Based on PCI value, road segment 1 rated 5 with less PCI value and road segment 4 rated 1 with high PCI value. The defined method is also compared with the rating system given in Indian Road Congress (IRC -82-2015).


Pavement; Performance; Assessment; Distress Condition; Structural Indicators and Functional Indicators.


Huang, Y. H. “Pavement Analysis and Design” Prentice Hall Inc. (1993).

Singh, Ajit Pratap, Antriksh Sharma, Raunak Mishra, Makrand Wagle, and A.K. Sarkar. “Pavement Condition Assessment Using Soft Computing Techniques.” International Journal of Pavement Research and Technology 11, no. 6 (November 2018): 564–581. doi:10.1016/j.ijprt.2017.12.006.

N. O. Attoh-Okine. “Aggregating Evidence in Pavement Management Decision-Making Using Belief Functions and Qualitative Markov Tree” IEEE transactions on systems, man, and cybernetics—part c: applications and reviews (August 2002):243-251, doi: 10.1109/tsmcc.2002.804443.

Y. O. Adu-Gyamfi, Titus Tienaah, N. O. Attoh-Okine, Chandra Kambhamettu. “Functional Evaluation of Pavement Condition Using a Complete Vision System” Journal of Transportation Engineering, ASCE. (May 2014): 04014040-1- 04014040-10, doi: 10.1061/(asce)te.1943-5436.0000638

Ouma, Yashon O., J. Opudo, and S. Nyambenya. “Comparison of Fuzzy AHP and Fuzzy TOPSIS for Road Pavement Maintenance Prioritization: Methodological Exposition and Case Study.” Advances in Civil Engineering 2015 (2015): 1–17. doi:10.1155/2015/140189.

Sung Ho Park and Jae Hoon Kim “Comparative Analysis of Performance Prediction Models for Flexible Pavements” Journal of Transportation Engineering, Part B: Pavements, (March 2019). doi: 10.1061/jpeodx.0000090.

Moazami, Danial, Hamid Behbahani, and Ratnasamy Muniandy. “Pavement Rehabilitation and Maintenance Prioritization of Urban Roads Using Fuzzy Logic.” Expert Systems with Applications 38, no. 10 (September 2011): 12869–12879. doi:10.1016/j.eswa.2011.04.079.

Koduru Hari Krishan, Xiao Feipeng, Amir khanian Serji N. and Juang C. Hsein, “Using Fuzzy Logic and Expert System Approaches in Evaluating Flexible Pavement Distress: Case Study,’ Journal of Transportation Engineering, ASCE. (February 2010):149-157. doi:10.1061/(asce)0733-947x(2010)136:2(149).

Lu Sun and Wenjun Gu., “Pavement Condition Assessment Using Fuzzy Logic Theory and Analytic Hierarchy Process.” Journal of Transportation Engineering, ASCE. (September 2011): 648–655. doi: 10.1061/(asce)te.1943-5436.0000239.

Tsai Yichang James, Li Feng, Roger C. Purcelland Rabun J. T., (2012). “Reliable Statewide Pavement-Performance Study Using a Confidence Evaluation System.” Journal of Transportation Engineering ASCE (March 2012):339–347: doi: 10.1061/(asce)te.1943-5436.0000334.

Abdul Jaleel Ahmed, Lamia, and Ammar Fakhir Sabri. “Study the Using of Reed Mats in Asphalt Pavement Layers.” Civil Engineering Journal 4, no. 2 (March 6, 2018): 346. doi:10.28991/cej-030996.

Sebnem Karahancer , Ekinhan Erişkin , Nihat Morova and Mehmet Saltan (2017) “Pavement Performance Assessment by ANFIS approach Using Marine Corps Air Station Cherry Point, North Carolina Data” 8th International Advanced Technologies Symposium IATS’17. (October 2017):328-335.

Chen Don, Cavalline Tara and MastinNeil. “Development of Piecewise Linear Performance Models for Flexible Pavements Using PMS Data” Journal of Performance of Constructed Facilities, ASCE. (December 2015). doi:10.1061/(asce)cf.19435509 .0000647.

Heravi Gholamreza and Asghar Nezhadpour Esmaeeli. “Fuzzy Multicriteria Decision-Making Approach for Pavement Project Evaluation Using Life-Cycle Cost/Performance Analysis”, Journal of Infrastructure Systems, ASCE. (May 2017). doi: 10.1061/(asce)is.1943-555x.0000170.

Katkar S. R. and Nagrale P. P. “Defining Pavement Condition States to Quantify Road Quality for Designing of Pavement Maintenance Management System” International Journal of Application or Innovation in Engineering & Management (February 2014), Volume 3, Issue 2: 142-148.

Agawam Praveen and Kumar Naveen. “Fuzzy Model for Road Roughness Index” International Conference on Biological, Civil and Environmental Engineering (BCEE-2015) (February 2015):4-7.

Congliang W U, Chunge L I and xiaolanDuan, “The decision method of basic fuzzy soft set in the application of the asphalt pavement maintenance sorting”Int. Journal of Engineering Research and Applications: (February 2001): Vol. 5, Issue 2, pp 92-95.

Chen, Don, Tara Cavalline, and Neil Mastin. “Development of Piecewise Linear Performance Models for Flexible Pavements Using PMS Data.” Journal of Performance of Constructed Facilities 29, no. 6 (December 2015): 04014148. doi:10.1061/(asce)cf.1943-5509.0000647.

Mcheick, Hamid, and Atif Farid Mohammad. “The Evident Use of Evidence Theory in Big Data Analytics Using Cloud Computing.” 2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE) (May 2014). doi:10.1109/ccece.2014.6901158.

Merigo, José M., Kurt J. Engemann, and Daniel Palacios-Marques. “Decision Making With Dempster-Shafer Belief Structure and the Owawa Operator.” Technological and Economic Development of Economy 19, no. Supplement_1 (January 28, 2014): S100–S118. doi:10.3846/20294913.2013.869517.

George, J. Klir, and Yuan Bo. "Fuzzy sets and fuzzy logic: theory and applications." PHI New Delhi (1995): 443-455.

IRC 82-2015 Code of practices for maintenance of bituminous Road surfaces, 2015.

Full Text: PDF

DOI: 10.28991/cej-2020-03091562


  • There are currently no refbacks.

Copyright (c) 2020 Shruti Shashank Wadalkar, Dr. R K Lad, Dr. R. K. Jain

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.