【摘要】 道路交通事故造成的人员伤亡与经济损失仍是亟待解决的公共安全难题。自动驾驶汽车面临碰撞不可避免工况时，如何在极限时间窗口内充分利用车辆主动控制和乘员舱内约束系统的调节潜力，以降低乘员损伤风险，是当前主被动一体化安全研究的热点问题。本研究通过分析自动驾驶和人类驾驶员事故特征提取典型事故场景，在典型场景下遍历车辆轨迹确定研究域内的碰撞工况参数；基于车-车碰撞仿真模型和中国50百分位男性高生物逼真度有限元模型计算了64例有限元仿真，覆盖了较为典型的碰撞工况。研究结果分析了碰撞工况和约束系统参数对乘员损伤风险具有耦合作用：在所有碰撞工况下，后倾躺姿对乘员损伤风险影响最大，使头部HIC值增大87%,BrIC值增大59%；中高速碰撞工况且乘员正常坐姿情况下，优化碰撞工况比优化乘员安全带预紧力数对损伤风险的降低更有效，碰撞前横向调整车辆1.0 m位移优化碰撞角度和位置，有望将MAIS3+损伤风险降低10%以上，将胸部压缩量降低14%以上。本文基于碰撞损伤量化探索构建了主被动一体化的行车风险域概念，揭示了融合避撞策略和约束系统控制下的乘员预期损伤差异，为自动驾驶车辆临碰撞决策优化及乘员保护系统设计提供了量化依据。更多还原

【Abstract】 Road traffic accidents remain a critical public safety issue that demands urgent resolution due to the associated casualties and economic loss. When autonomous vehicles encounter unavoidable collision conditions, a key research focus in integrated active and passive safety is how to fully utilize the potential of vehicle active control and the adjustment capabilities of in-cabin restraint systems within extremely limited time windows to mitigate occupant injury risk. This study analyzes accident characteristics of both autonomous and human-driven vehicles to extract typical collision scenarios. Within these scenarios, vehicle trajectories are exhaustively examined to determine collision parameters across the research domain. Using a vehicle-to-vehicle collision simulation model and a high-biofidelity finite element model of a 50 th percentile Chinese male, 64 finite element simulations are conducted, covering representative collision conditions. The results show the coupled effect of collision conditions and restraint system parameters on occupant injury risk. Across all collision scenarios, a reclined seating posture most significantly increases injury risk, elevating Head Injury Criterion(HIC) by 87% and Brain Injury Criterion(BrIC) by 59%. In medium-to-high speed collisions with normally seated occupants, optimizing collision conditions prove more effective in reducing injury risk than adjusting seatbelt pretension force. A pre-crash lateral adjustment of 1.0 m to optimize collision angle and position reduces the risk of MAIS3+ injuries by over 10% and chest compression by over 14%. This study explores the concept of an integrated active-passive driving risk field based on quantitative collision injury assessment, revealing differences in expected occupant injuries under integrated collision avoidance strategies and restraint system control. The findings provide a quantitative basis for optimizing pre-crash decisionmaking in autonomous vehicles and designing occupant protection systems.更多还原