汽车工程学报2025，Vol.15Issue(5)：638-653,16.DOI:10.3969/j.issn.2095-1469.2025.05.02
基于脑电信号的驾驶员意图与风险驾驶状态识别综述
A Review on EEG-Based Recognition of Driver Intention and Risky Driving States
摘要
Abstract
A driver's state and behavior directly affect road safety while driving.Electroencephalogram(EEG)activity reveals the driver's psychological and physiological conditions in real time,offering a new way to enhance driving safety and build a safer driving environment.This paper explores the current research status of driver EEG signals in the field of intelligent vehicle cockpits,aiming to promote their application and innovation.Firstly,it compares dry and wet electrodes across signal acquisition,preprocessing and feature extraction,and analyzes the scenarios where each works best.Secondly,it examines fatigue driving,distracted driving,and abnormal emotion detection,highlighting how energy ratios among the α,θ,and β bands and AI models identify these states.In terms of driving intention identification,combining EEG signals with multimodal data,such as electromyography and eye tracking,has significantly improved the accuracy of classifying actions like lane changes and braking.Finally,the challenges faced in current research are summarized,including individual differences that limit model generalization,the lack of validation in real-world driving,and the complexity of multimodal data fusion.The paper concludes by analyzing the future trends for integrating driver EEG signals into the intelligent cockpit systems.关键词
智能座舱/人机交互/脑机接口/辅助驾驶系统/驾驶安全Key words
intelligent cockpit/human-computer interaction/brain-computer interface/driver assistance system/driving safety分类
交通工程引用本文复制引用
唐帮备,朱明鑫,郭钢..基于脑电信号的驾驶员意图与风险驾驶状态识别综述[J].汽车工程学报,2025,15(5):638-653,16.基金项目
国家自然科学基金项目(52402444) （52402444）
重庆市博士后研究项目特别资助(2023CQBSHTB3133) （2023CQBSHTB3133）
重庆市教委科学技术研究项目(KJQN202201345) （KJQN202201345）
