Evaluation of traffic congestion degree: An integrated approach

Nannan Hao, Yixiong Feng, Kai Zhang, Guangdong Tian, Lele Zhang and Hongfei Jia

International Journal of Distributed Sensor Networks, 2017, vol. 13, issue 7, 1550147717723163

Abstract: Intersection traffic congestion evaluation is essential for effective intelligent transportation system planning, and an objective and precise assessment of traffic congestion is vital to ensure the smooth circulation of traffic. Multiple criteria decision-making is a method for evaluating the degree of traffic congestion. A hybrid multiple criteria decision-making method integrating the fuzzy analytic hierarchy process, techniques for order preference by similarity to an ideal solution, and gray correlation techniques are presented in this work. The proposed method applied fuzzy analytic hierarchy process to determine the weight of the evaluation index; subsequently, gray correlation techniques for order preference by similarity to an ideal solution were integrated to construct the hybrid decision-making method. A case study of traffic congestion at intersections with five evaluation indexes verified the effectiveness of the hybrid method. The evaluation results of the different methods show that the proposed method overcomes the one-sidedness of analytical hierarchy process–techniques for order preference by similarity to an ideal solution and analytical hierarchy process–gray correlation. Thus, the proposed hybrid decision-making model provides a more accurate and reliable method for evaluating the degree of traffic congestion.

Keywords: Fuzzy analytic hierarchy process; gray correlation; techniques for order preference by similarity to an ideal solution; multi-objective decision-making; intelligent transportation system congestion evaluation; decision analysis (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:13:y:2017:i:7:p:1550147717723163

DOI: 10.1177/1550147717723163

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