Highway interchange section state discrimination method based on improved fuzzy C-means clustering algorithm

Wenyong Li; Wenyu Wang; Jiawei Li; Yuyao Liang; Guan Lian

doi:10.1117/12.3039518

28 August 2024 Highway interchange section state discrimination method based on improved fuzzy C-means clustering algorithm

Wenyong Li, Wenyu Wang, Jiawei Li, Yuyao Liang, Guan Lian

Author Affiliations +

Proceedings Volume 13251, Ninth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2024); 132515O (2024) https://doi.org/10.1117/12.3039518
Event: 9th International Conference on Electromechanical Control Technology and Transportation (ICECTT 2024), 2024, Guilin, China

Abstract

As an important transportation channel and traffic hub, the highway is frequently congested due to the rapid growth of traffic demand. Therefore, this paper adopts the Mahalanobis distance, which is more sensitive to the change relationship and discreteness between different dimensional data, to replace the traditional Euclidean distance to improve the algorithm, and constructs a traffic congestion discrimination model based on the improved fuzzy C-means clustering algorithm. The model takes the measured data of the highway interchange section as the input, and discriminates the highway operation condition according to the clustering results. Through empirical verification, the discrimination effect of the model is significantly better than the traditional clustering algorithm and the current speed threshold discrimination method, and has good applicability and accuracy.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wenyong Li, Wenyu Wang, Jiawei Li, Yuyao Liang, and Guan Lian "Highway interchange section state discrimination method based on improved fuzzy C-means clustering algorithm", Proc. SPIE 13251, Ninth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2024), 132515O (28 August 2024); https://doi.org/10.1117/12.3039518

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