汽车工程学报2024，Vol.14Issue(5)：791-800,10.DOI:10.3969/j.issn.2095‒1469.2024.05.05
跟车工况下基于风险评估的人机共驾策略
Human Machine Co-driving Strategy Based on Risk Assessment Under Car Following Conditions
摘要
Abstract
To avoid unnecessary interventions by the driver assistance system,this paper combines collision risk and driving maneuverability to introduce the concept of a risk assessment zone in longitudinal following scenarios.The boundary of this zone is determined based on the normal distribution characteristics of the driving data.Subsequently,a new human-machine co-driving longitudinal driving rights allocation strategy is proposed,which takes the inverse time to collision(TTCi)as the basis for judgment.If the TTCi exceeds the threshold value,the upper boundary of the risk assessment zone represents the maximum deviation in driving maneuverability.The control rights of the assistance system are allocated according to the deviation in the driver's maneuverability.By combining Prescan,Matlab/Simulink and the Logitech G29 driving simulator,a driver-in-the-loop simulation platform was constructed.The platform simulated the reduced driver maneuverability due to distracted driving,thereby verifying the effectiveness of the strategy.The results show that the proposed human-machine co-driving strategy can effectively prevent collisions caused by reduced driver maneuverability under high-speed road following conditions.关键词
碰撞风险/驾驶操纵能力/风险评估区/正态分布/驾驶权分配Key words
collision risk/driver's manoeuvring ability/risk assessment area/normal distribution/distribution of driving rights分类
交通工程引用本文复制引用
刘平,沈跃,杨明亮,田云鹏,王硕翰..跟车工况下基于风险评估的人机共驾策略[J].汽车工程学报,2024,14(5):791-800,10.基金项目
四川省科技厅重点研发项目(2020YFG0130):轮毂驱动汽车多级主动减振控制及应用研究 （2020YFG0130）
