驾驶风险监测与干预技术研究综述  

Review on driving risk monitoring and intervention technologies

作　　者：李国法[1,2] 欧阳德霖 陈晨 聂冰冰[1] 张伟[3] 禹慧丽[4] 刘斌 张强 王文军[1] 成波 李升波[1] LI Guofa;OUYANG Delin;CHEN Chen;NIE Binging;ZHANG Wei;YU Huili;Liu Bin;ZHANG Qiang;WANG Wenjun;CHENG Bo;LI Shengbo(School of Vehicle and Mobility,Tsinghua University,Beijing 100084,China;College of Mechanical and Vehicle Engineering,Chongqing University,Chongqing 400044,China;Suzhou Automotive Research Institute,Tsinghua University,Suzhou 215200,China;Chongqing Changan Automobile Co.,Ltd,Chongqing 400023,China;China FAW Group Corporation R&D Institute,Changchun 130000,China;China Automotive Engineering Research Institute Co.,Ltd,Chongqing 401122,China.)

机构地区：[1]清华大学车辆与运载学院,北京100084 [2]重庆大学机械与运载工程学院,重庆400044 [3]清华大学苏州汽车研究院,苏州215200 [4]重庆长安汽车股份有限公司,重庆400023 [5]中国第一汽车股份有限公司研发总院,长春130000 [6]中国汽车工程研究院股份有限公司,重庆401122

出　　处：《汽车安全与节能学报》2025年第2期181-196,共16页Journal of Automotive Safety and Energy

基　　金：国家自然科学基金项目(52272421);智能绿色车辆与交通全国重点实验室开放基金课题(KFZ2409)。

摘　　要：安全是道路交通运输一直以来的热点问题,是保障中国道路交通运输通畅、支持国民经济健康发展的重要基础。驾驶风险监测与干预是保障车辆驾驶安全的关键技术,特别是感知技术和信息技术的快速发展,为驾驶风险的监测和干预提供了坚实的数据基础和新的应用路径。该文针对驾驶风险监测与干预技术的研究进展进行系统性的综述。首先,从车内和车外两个角度对驾驶风险监测技术发展现状进行了梳理;其次,从离线和在线两方面对驾驶风险干预策略方案进行了综述,研究表明视听触觉融合干预有效提高驾驶员响应时间,触觉预警系统则能帮助降低驾驶员误操作率;在此基础上,介绍风险监测与干预技术在高级驾驶辅助系统(ADAS)、自动驾驶系统、车联网与车辆保险等方面的实际落地方向与具体应用,研究表明基于车路云协同的智能系统可提升风险预警实时性,ADAS的应用能有效降低交通事故率和基于用户使用情况的保险(UBI)损失率;最后,面向未来自动驾驶应用,从模型轻量化、大数据应用、云控平台和自动驾驶大模型等方面探讨了未来风险监测与干预技术的发展方向。Safety has always been a critical concern in road transportation,serving as a fundamental pillar for ensuring traffic efficiency and supporting economic development.Driving risk monitoring and intervention are key technologies for enhancing vehicle safety,particularly with advancements in perception and information technology,which provide a robust data foundation and new avenues for implementation.This paper systematically reviews the research progress of driving risk monitoring and intervention techniques.Firstly,it examines the current state of driving risk monitoring from both of in-vehicle and external perspectives.Secondly,it reviews intervention strategies from both offline and online approaches.Studies have shown that interventions integrating visual,auditory,and haptic feedback can significantly improve driver response times,while haptic warning systems can help reduce the rate of driver errors.Then it is explored that the integration of risk monitoring and intervention technologies into Advanced Driver Assistance Systems(ADAS),autonomous driving systems,connected vehicle systems,and automated driving platforms.Studies have shown that intelligent systems based on vehicle-road-cloud collaboration can improve the real-time performance of risk warnings.The application of ADAS has been proven effective in reducing traffic accident rates and lowering Usage-Based Insurance(UBI)loss ratios.Finally,future research directions are discussed,including model optimization for lightweight deployment,big data applications,cloud-based control platforms,and the role of large-scale autonomous driving models in advancing risk monitoring and intervention technologies.

关 键 词：自动驾驶 风险监测 风险干预 驾驶安全 车路云一体化 

分 类 号：U46[机械工程—车辆工程]