Driving style diversity in highway weaving areas: A drone-based analysis of population distribution patterns and operational parameter relationships.

ABSTRACT: Driving style heterogeneity significantly influences traffic safety and efficiency in highway weaving areas, yet how operational parameters systematically shape population-level behavioral patterns remains unclear. This study examines the relationships between weaving area operational characteristics and driving style population distribution patterns using drone-collected trajectory data from seven highway weaving areas, obtaining 12,707 complete vehicle trajectories. Six driving style features incorporating speed and acceleration metrics were extracted, and Gaussian Mixture Model clustering identified three distinct driving style types: aggressive (23.5%), moderate (58.9%), and conservative (17.6%). Population distribution characteristics were quantified using Shannon entropy, Gini coeffi

SUBMITTER: Yuan Z 

PROVIDER: S-EPMC12674577 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature