Abstract

With the rapid development of China's transportation and the improvement of people's living standards, China's highways have entered the peak maintenance period. According to the old road conditions and financial conditions, how to choose the appropriate maintenance technology to meet the technical and economic requirements of highway maintenance and construction projects has become a difficult problem faced by highway maintenance management departments. Therefore, based on the principle of index selection, this study comprehensively considered the impact of various factors on maintenance decision-making, determined four evaluation indexes, and systematically studied the compre-hensive decision-making system of asphalt pavement recycling maintenance. Based on the subjective-objective linkage and probability statistics method, the eigenvalue of the applicability of recycling mode was transformed to the same scale of 0 to 100, and the fuzzy scoring interval of the four bids was proposed. The calculation method of pavement quality recovery index (PQRI) and the analysis basis of economic benefits were clarified. Finally, the weight of each index was calculated by analytic hierarchy process, and the multi-index comprehensive decision-making method of pavement maintenance is constructed and used to theoretically verify and guide the actual road section. Results demonstrate that the proposed PQRI can realize the operability of quantifying the later operation of pavement. The weight of each index from big to small is PQRI > economic benefit > applicability of recycling mode. The recycled pavement quality recovery indices and applicability of the four recycling modes have small differences, and the proposed four bids interval makes the decision-making evaluation process more simple and explicit. The decision evaluation results of actual road section verify the rationality and practicability of the decision method. The conclusions are important for the maintenance and management of asphalt pavement recycling technology. Keywords: road engineering, recycling maintenance, intelligent decision-making, fuzzy evaluation

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