Analysis of driving behaviour in highway confluence areas

Mei Zhang; Fang Yan; Xiaobin Xu; Cong Du; Bin Lv; Jianqing Wu

doi:10.1117/12.3024187

14 February 2024 Analysis of driving behaviour in highway confluence areas

Mei Zhang, Fang Yan, Xiaobin Xu, Cong Du, Bin Lv, Jianqing Wu

Proceedings Volume 13018, International Conference on Smart Transportation and City Engineering (STCE 2023); 130182I (2024) https://doi.org/10.1117/12.3024187
Event: International Conference on Smart Transportation and City Engineering (STCE 2023), 2023, Chongqing, China

Abstract

The confluence area of highways is a high-risk area for traffic accidents and congestion. By analysing vehicle trajectory data, the driving style and bad driving behaviour of drivers are identified, to take timely measures to prevent traffic accidents, alleviate traffic congestion, and improve traffic safety. This article is based on vehicle trajectory data to construct driving behaviour feature parameters. PCA is used to reduce the dimensionality of the feature parameter matrix to remove the linear correlation between the feature parameters. The principal component contribution rate reaches 96%, and the reduced feature matrix is used as input to the K-Means++ algorithm for clustering. The clustering center K is determined using the contour coefficient method. Compare the results with the K-Means results. According to literature experimental analysis, driving styles in confluence areas can be divided into three categories: aggressive, steady, and calm. The experimental results are scientifically reliable and provide important references for traffic management, road design, driver education, and intelligent transportation systems.

Citation Download Citation

Mei Zhang, Fang Yan, Xiaobin Xu, Cong Du, Bin Lv, and Jianqing Wu "Analysis of driving behaviour in highway confluence areas", Proc. SPIE 13018, International Conference on Smart Transportation and City Engineering (STCE 2023), 130182I (14 February 2024); https://doi.org/10.1117/12.3024187

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