arrow
返回

Multi-scenario driving style research based on driving behavior pattern extraction

delete2025-05-01
delete0
PRE
AI
贺宜 封面图
贺宜 (Yi He)
Y
Yingrui Hu
J
Jipu Li
K
Ke Sun
尹建华 封面图
尹建华 (Jianhua Yin) *
DOI:10.1016/j.aap.2025.107963delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Accurately analyzing drivers' driving styles is crucial for road safety and enhancing intelligent driving systems. However, existing studies have not fully explored the hidden information in driving sequences or considered the influence of driving environments on driving styles. Based on natural driving data from electric vehicles in Wuhan, a framework for driving style analysis based on driving behavior pattern extraction was proposed. Driving sequences were extracted under free-driving and car-following scenarios, where the convergence of driving features was verified using kernel density estimation and relative entropy. A driving propensity indicator based on a dynamic threshold was constructed, and combined with the Hierarchical Dirichlet Process Hidden Semi-Markov Model (HDP-HSMM) and K-means clustering algorithm, 4 and 5 types of driving behavior pattern were extracted under free-driving and car-following scenarios, respectively. Energy consumption distribution was introduced to verify the validity of driving pattern extraction. Jensen-Shannon (JS) divergence was utilized to calculate the difference in the distribution of the driving propensity indicator among different drivers. By quantifying behavioral differences, drivers were categorized into aggressive, moderate, and conservative types. The results show that the statistical characteristics of driving patterns are consistent with the distribution of energy consumption, with the highest energy consumption occurs in aggressive acceleration and high-speed steady-state patterns, and the highest braking energy recovery occurs in aggressive deceleration pattern. Furthermore, the driving environment influences driving styles to certain degree while exhibiting consistent or diverse driving styles in different driving scenarios and patterns.
Keyword:
Automobile driving
Driving style
Semi-hidden Markov model
Electric vehicle
Driving patterns

期刊

A
Accident Analysis and Prevention
IF:
6.2
论文数:
7.6K
被引数:
3.2W

机构

W
Wuhan University of Technology
学者数:
3.4W
论文数: 2.4W
被引数: 4.4W
引用论文

引用论文

Prevention of Resist Pattern Collapse by Flood Exposure during Rinse Process
err1994-12-01
err0
PREAI
errToshihiko Tanaka; Mitsuaki Morigami; Hiroaki Oizumi; Taro Ogawa Taro Ogawa; Shou-ichi Uchino Shou-ichi Uchino
err分享
err收藏
A Review of Driving Style Recognition Methods From Short-Term and Long-Term Perspectives短期和长期视角下的驾驶风格识别方法综述
err2023-11-01
err14
errOAAI
errChu, Hongqing; Zhuang, Hejian; Wang, Wenshuo; Na, Xiaoxiang; Guo, Lulu; Zhang, Jia; Gao, Bingzhao; Chen, Hong
err分享
err收藏
err
IF0
err
err0
PREAI
err
err分享
err收藏
Blockade of TRPM7 Channel Activity and Cell Death by Inhibitors of 5-Lipoxygenase
err2010-06-17
err0
errOAAI
errHsiang-Chin Chen; Jia Xie; Zheng Zhang; Li-Ting Su; Lixia Yue; Loren W. Runnels
err分享
err收藏
What is the level of volatility in instantaneous driving decisions?
err2015-09-01
err85
errOAAI
errWang, Xin; Khattak, Asad J.; Liu, Jun; Masghati-Amoli, Golnush; Son, Sanghoon
err分享
err收藏
err分享
err收藏
学者 查看更多内容