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Zehong Xuan

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Proceedings Article | 22 May 2024 Paper

Assessment of road safety performance based on CRITIC-TOPSIS-Kmeans model

Sophia Ding, Yuyang He, Haoyuan Sun, Kunyu Song, Zehong Xuan, Jianwei Zhang, Mingshu Zhang

Proceedings Volume 13176, 1317634 (2024) https://doi.org/10.1117/12.3029065

KEYWORDS: Safety, Roads, Performance modeling, Machine learning, Transportation

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The study assesses road safety performance in the Southeast Asian region by using the CRITIC-TOPSIS-Kmeans model. First, the weight of each indicator is obtained by CRITIC. Then, the obtained weights are embedded into the TOPSIS model. Furthermore, the TOPSIS sores are put into the K-means unsupervised machine learning model. The proposed CRITIC-TOPSIS-Kmeans model is utilized to rank and group the road safety performance of Southeast Asian countries. Finally, radar and bar plots are utilized to deconstruct indicators and TOPSIS scores, providing valuable references for policymakers. Overall, the development of the CRITIC-TOPSIS-Kmeans model not only establishes a fresh foundation for evaluating road safety achievements but also offers potential solutions for other MCDM challenges.

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