Driving Style Tendency Quantification Method Based on Short-Term Lane Change Feature Extraction

Yanfeng Jia, Zhi Zhang, Xiantong Li, Xiufeng Chen and Dayi Qu ()
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Yanfeng Jia: School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China
Zhi Zhang: School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China
Xiantong Li: China Academy of Transportation Sciences, Beijing 100029, China
Xiufeng Chen: School of Civil Engineering, Qingdao University of Technology, Qingdao 266520, China
Dayi Qu: School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China

Sustainability, 2025, vol. 17, issue 8, 1-22

Abstract: To enhance road safety and optimize intelligent driving systems, this study introduces the concept of “driving style tendency” to characterize short-term driver behavior, particularly lane-changing patterns. A multidimensional framework is established to analyze driving roles and behaviors, utilizing a Hidden Semi-Markov Model and Hierarchical Dirichlet Process for the unsupervised segmentation of driving trajectory data into behavioral primitives. By systematically analyzing driver behaviors in leading and following scenarios, characteristic thresholds are derived through distribution fitting, enabling the development of a non-parametric Bayesian-based scoring method for driving style tendency. The K-means clustering algorithm is employed to transform primitive segments into quantifiable semantic information, facilitating the interpretation of driver behavior preferences. This research contributes to improved collision risk prediction in complex traffic environments, supports the design of personalized driving assistance systems, and provides valuable insights for autonomous driving technology development.

Keywords: short-term lane change characteristics; driving style tendency; HSMM-HDP (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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