期刊文献+

自动驾驶汽车中乘员在不同座椅朝向下的损伤风险及规避策略 被引量:6

Injury Risk and Evasion Strategy of Occupants in Different Seating Orientations in Autonomous Vehicles
原文传递
导出
摘要 在高度自动化车辆(Highly Automated Vehicle,HAV)中,由于不再需要驾驶人,乘客之间可以实现面对面的交流,这给车辆座椅的布置提供了更大的灵活性。为提高HAV的碰撞安全性,提出使用旋转座椅来改变人体朝向与碰撞方向相对位置的规避策略,其基本思路是在碰撞发生前通过主动改变座椅朝向来降低乘员损伤。首先,利用尸体试验数据对所建立的碰撞模型进行验证;然后,基于4种不同的座椅朝向,利用THUMS^TM人体模型进行初始速度为56km·h^-1h的正面碰撞模拟试验,以确定相对安全的座椅朝向位置;最后,预测座椅旋转过程本身以及旋转至某位置后发生碰撞的乘员损伤风险。在静态正面碰撞中,选择0°、90°、135°和180°四种不同的座椅朝向进行乘员损伤预测和比较,结果表明180°朝向时的乘员损伤风险最小。在此基础上,模拟了200ms内将座椅旋转±45°和±90°,以及分别在0ms和100ms时间延迟后引入碰撞的试验过程。研究结果表明:200ms能够将乘员旋转±45°和±90°而不引起额外的人体损伤,并且在无时间延迟时,旋转至背对碰撞方向的乘员损伤,比正面碰撞中0\90°和135°座椅朝向的乘员损伤更低,证明了该损伤风险规避策略的有效性。 In a highly automated vehicle (HAV),face-to-face communication between passengers is achieved because the driver is no longer needed,which provides greater flexibility in the configuration of the vehicle seat.This paper presents an evasive strategy using a rotating seat to change the relative position of human orientation and impact direction to improve the safety of HAV collisions.The basic idea is to reduce occupant injury by actively changing the seat orientation before a collision occurs.The study consists of three parts.First,the impact model with THUMS^TM was validated using PMHS data.Second,based on four preferred seat orientations,static frontal impact simulations with an initial speed of 56 km·h^-1 were conducted using THUMS^TM human model to determine the relatively safe seat orientation.Finally,the injury risk of occupant from the impact after the rotating seat to this position was predicted.In the static frontal collision,four different seat orientations of 0°,90°,135° and 180° were selected for occupant injury prediction and comparison,and the results show that the occupant injury risk in the 180° orientation was minimal.On this basis,the experiment was carried out by simulating the seat rotation by ±45° and ±90° in 200 ms and introducing a collision after a time delay of 0 ms and 100 ms,respectively.Studies show that 200 ms is enough to rotate the occupant by ±45° and ±90° without introducing additional injuries,and injury risk in the rear-facing impacting after rotation without time delay is lower than that of 0°,90° and 135° seating orientations,demonstrating the effectiveness of this evasive strategy.
作者 武和全 侯海彬 胡林 黄晶 WU He-quan;HOU Hai-bin;HU Lin;HUANG Jing(Key Laboratory of Lightweight and Reliability Technology for Engineering Vehicle,Education Department of Hunan Province,Changsha University of Science and Technology,Changsha 410004,Hunan,China;Bioengineering Center,Wayne State University,Detroit MI48201,Michigan,USA;School of Mechanical and Transportation Engineering,Hunan University,Changsha 410082,Hunan,China)
出处 《中国公路学报》 EI CAS CSCD 北大核心 2019年第6期206-215,225,共11页 China Journal of Highway and Transport
基金 国家自然科学基金项目(51405035,51875049) 湖南省自然科学杰出青年基金项目(2019JJ20017) 湖南省自然科学基金项目(2018JJ2432) 湖南省教育厅科学研究项目(16B015)
关键词 汽车工程 乘员规避策略 有限元方法 座椅朝向 损伤风险 自动驾驶汽车 碰撞模拟 automotive engineering occupant avoidance strategy finite element method seat orientations injury risk autonomous vehicle impact simulation
  • 相关文献

参考文献6

二级参考文献53

  • 1高忠义.私家车购买影响因素分析[J].市场研究,2006(10):24-26. 被引量:2
  • 2蔡自兴,Durkin J,龚涛.高级专家系统:原理、设计及应用[M].北京:科学出版社,2006.
  • 3Liao S H.Expert system methodologies and applications-A decade review from 1995 to 2004[J].Expert Systems with Applications.2005,28(1):93-103.
  • 4Prasad R,Ranjan K R,Sinha A K.AMRAPALIKA:An expert system for the diagnosis of pests,diseases,and disorders in Indian mango[J].Knowledge-Based Systems,2006,19(1):9-21.
  • 5Lyu J J,Chen M N.Automated visual inspection expert system for multivariate statistical process control chart[J].Expert Systems with Applications,2009,36(3):5113-5118.
  • 6Wang Y D,Lim E P,Hwang S Y.Efficient mining of group patterns from user movement data[J].Data & Knowledge Engineering,2006,57 (3):240-282.
  • 7Zheng H F,Chen L D,Han X Z,et al.Classification and regression tree (CART) for analysis of soybean yield variability among fields in Northeast China:The importance of phosphorus application rates under drought conditions[J].Agriculture,Ecosystems & Environment,2009,132(1):98-105.
  • 8Shiue W,Li S T,Chen K J.A frame knowledge system for managing financial decision knowledge[J].Expert Systems with Applications,2008,35(3):1068-1079.
  • 9Dibuz S.A frame-based approach to conformance testing[J].Microprocessing and Microprogramming,1993,39(2):191-194.
  • 10Sorenson D,Grissom C K,Carpenter L,et al.A frame-based representation for a bedside ventilator weaning protocol[J].Journal of Biomedical Informatics,2008,41 (3):461-468.

共引文献192

同被引文献363

引证文献6

二级引证文献27

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部