Pavement network reliability: a dual‐network based on fuzzy set methodology. Issue 3 (28th November 2018)

• Record Type: Journal Article
• Authors: Wang, Xingju; Gou, Yang; Han, Zhe; Zhang, Zhanmin
• Is Part Of: IET intelligent transport systems. Volume 13:Issue 3(2019)
• Page Start: 475
• Page End: 484
• Publication Date: 2018-11-28
• Subjects: roads -- reliability -- fuzzy set theory -- network theory (graphs) -- maintenance engineering; pavement network reliability estimation -- network maintenance -- Texas -- Travis County -- pavement links -- pavement management segments -- fuzzy condition model -- pavement route -- PMS -- pavement management system -- fuzzy set methodology -- dual‐network method; Intelligent transportation systems -- Periodicals; Electronics in transportation -- Periodicals; 388.31205
• DOI: 10.1049/iet-its.2018.5191
• Languages: English
• ISSNs: 1751-956X

Abstract

Abstract : Pavement Management System (PMS) is used to conduct efficient pavement management. Since the pavement network is generally large and complex in scale, the reliability of the pavement network cannot be easily determined by applying conventional serial or parallel reliability models, or even a combination of the two. The objective of this paper is to propose a novel model by employing fuzzy set theory and dual‐network method to calculate the relative importance of each pavement route and estimate the reliability of a pavement network. A fuzzy condition model is developed to describe the condition state of pavement management segments, pavement links, pavement routes, and eventually the whole network. The spatial weight of each pavement route is represented by the node degree of the corresponding dual‐network. A case study is conducted by using the pavement network of Travis County, Texas, to illustrate the applicability of the proposed methodology. The results show that the model is able to calculate the relative importance of each route and determine the reliability of the given pavement network. This paper could help transportation agencies obtain more insight information on relative importance of each roadway and make more effective decisions on pavement network maintenance with a limited budget.