基于有限元仿真和遗传神经网络的轿车-行人事故重构  

Car-pedestrian accident reconstruction based on finite element simulation and genetic neural network

作　　者：刘文君[1] 李奎[1] 苏森[1] 王雪蕊[2] 范箫翔 尹志勇[1] 

机构地区：[1]第三军医大学大坪医院野战外科研究所全军交通医学研究所创伤烧伤与复合伤国家重点实验室车辆/生物碰撞安全重庆市重点实验室,重庆400042 [2]解放军第十五医院医务处,乌苏833000 [3]重庆理工大学药学与生物工程学院,重庆400054

出　　处：《医用生物力学》2015年第2期125-130,共6页Journal of Medical Biomechanics

基　　金：国家自然科学基金项目(31170908);“十二五”国家科技支撑计划项目(2014BAG01B05)

摘　　要：目的为充分利用轿车-行人碰撞中行人损伤信息对事故过程进行重构,提出采用有限元仿真和遗传神经网络逆向推导轿车-行人事故中碰撞参数的新方法。方法利用Hyperworks和LS-DYNA软件进行不同碰撞速度(25、40、55 km/h)和接触角度(背面、左侧、正面、右侧)的碰撞仿真,获取行人头部伤害指标(head injury criterion,HIC)和胸壁最大运动速度。根据损伤生物力学判据分析行人头部及胸部的损伤程度,并以行人头部和胸部损伤程度以及位置信息作为预测变量,采用遗传神经网络求取碰撞参数的预测值。最后利用两起具有确切碰撞参数的轿车-行人视频案例对该方法进行验证。结果两起视频案例中轿车碰撞行人速度分别为54、49 km/h,行人接触轿车角度均为180°。根据行人损伤信息得到轿车碰撞行人速度的预测值分别为51、43 km/h,行人接触轿车角度的预测值分别为184°和169°,两起事故重构准确度分别为0.94和0.88。结论利用行人损伤信息可以准确有效地对轿车-行人事故中的碰撞参数进行预测,既能为轿车-行人交通事故成因分析及责任认定提供新的方法,也为进一步提高轿车-行人碰撞中行人头部及胸部损伤的防治效果提供了理论依据。Objective In order to fully reconstruct the accident by utilizing pedestrian injuries information gained from the car-pedestrian collision,a new method based on finite element simulation and genetic neural network to deduce the car-pedestrian collision parameters in reverse is proposed. Methods Crash simulations from different contact angles（ back,left,front,right） at different impact speeds（ 25,40,55 km / h） were conducted by using Hyperworks and LS-DYNA,so as to obtain the head injury criterion（ HIC） value and the maximum velocity of the thoracic wall. According to the criteria of injury biomechanics,the severities of the pedestrian head and thorax and corresponding injury locations were analyzed and set as predictors,and the predictive values of collision parameters were then acquired by using genetic neural network. Finally,this method was verified by two car-pedestrian accidents with the video and exact collision parameters. Results For both cases of the car-pedestrian accidents,the car speeds at the collision of pedestrian were 54 and 49 km / h,respectively,and the car-pedestrian contact angles were both 180°. While according to the pedestrian injuries information,the predictive values of the car speeds at the collision of pedestrian were 51 and 43 km / h,and the predictive values of the car-pedestrian contact angles were 184° and 169°,respectively. The reconstruction accuracies of two cases were 0. 94 and0. 88. Conclusions The proposed method in the study can be used to predict car-pedestrian collision parameters efficiently and accurately by utilizing the pedestrian injuries information,which provides a new method for cause analysis and responsibility recognition,as well as theoretical references for the treatment and protection of head and thoracic injuries occurred in the car-pedestrian collision.

关 键 词：有限元仿真 遗传神经网络 行人损伤 事故重构 损伤生物力学 

分 类 号：R318.01[医药卫生—生物医学工程]