As a study method of traffic flow, dynamics models were developed and applied in the last few decades. However, there exist some flaws in most existing models. In this note, a new dynamics model is proposed by using c...As a study method of traffic flow, dynamics models were developed and applied in the last few decades. However, there exist some flaws in most existing models. In this note, a new dynamics model is proposed by using car-following theory and the usual connection method of micro-macro variables, which can overcome some ubiquitous problems in the existing models. Numerical results show that the new model can very well simulate traffic flow conditions, such as congestion, evacuation of congestion, stop-and-go phenomena and phantom jam.展开更多
为了提高驾驶辅助系统的跟车性能,基于神经网络方法建立了一种集成式驾驶员跟车模型。通过真实交通环境下的驾驶员实验获得了稳定跟车状态数据,并利用K a lm an滤波器对数据进行了处理和估计。设计了以BP神经网络为核心的集成式模型结构...为了提高驾驶辅助系统的跟车性能,基于神经网络方法建立了一种集成式驾驶员跟车模型。通过真实交通环境下的驾驶员实验获得了稳定跟车状态数据,并利用K a lm an滤波器对数据进行了处理和估计。设计了以BP神经网络为核心的集成式模型结构,该模型以前车速度为输入,计算跟车过程中的两个特性参数并输入神经网络以模拟驾驶员控制的自车加速度。利用处理后的数据样本对网络进行了训练,并对该模型进行了仿真验证。仿真结果表明:神经网络模型具有模拟驾驶员跟车行为的能力,模型体现出较为准确的跟踪特性,并对不同的前车工况具有良好的适应性。展开更多
Lower limb injures are frequently observed in passenger car traffic accidents.Previous studies of the injuries focus on long bone fractures by using either cadaver component tests or simulations of the long bone kinem...Lower limb injures are frequently observed in passenger car traffic accidents.Previous studies of the injuries focus on long bone fractures by using either cadaver component tests or simulations of the long bone kinematics,which lack in-depth study on the fractures in stress analysis.This paper aims to investigate lower limb impact biomechanics in real-world car to pedestrian accidents and to predict fractures of long bones in term of stress parameter for femur,tibia,and fibula.For the above purposes,a 3D finite element(FE) model of human body lower limb(HBM-LL) is developed based on human anatomy.The model consists of the pelvis,femur,tibia,fibula,patella,foot bones,primary tendons,knee joint capsule,meniscus,and ligaments.The FE model is validated by comparing the results from a lateral impact between simulations and tests with cadaver lower limb specimens.Two real-world accidents are selected from an in-depth accident database with detailed information about the accident scene,car impact speed,damage to the car,and pedestrian injuries.Multi-body system(MBS) models are used to reconstruct the kinematics of the pedestrians in the two accidents and the impact conditions are calculated for initial impact velocity and orientations of the car and pedestrian during the collision.The FE model is used to perform injury reconstructions and predict the fractures by using physical parameters,such as von Mises stress of long bones.The calculated failure level of the long bones is correlated with the injury outcomes observed from the two accident cases.The reconstruction result shows that the HBM-LL FE model has acceptable biofidelity and can be applied to predict the risk of long bone fractures.This study provides an efficient methodology to investigate the long bone fracture suffered from vehicle traffic collisions.展开更多
基金the National Natural Science Foundation of China (Grant No. 19872062).
文摘As a study method of traffic flow, dynamics models were developed and applied in the last few decades. However, there exist some flaws in most existing models. In this note, a new dynamics model is proposed by using car-following theory and the usual connection method of micro-macro variables, which can overcome some ubiquitous problems in the existing models. Numerical results show that the new model can very well simulate traffic flow conditions, such as congestion, evacuation of congestion, stop-and-go phenomena and phantom jam.
文摘为了提高驾驶辅助系统的跟车性能,基于神经网络方法建立了一种集成式驾驶员跟车模型。通过真实交通环境下的驾驶员实验获得了稳定跟车状态数据,并利用K a lm an滤波器对数据进行了处理和估计。设计了以BP神经网络为核心的集成式模型结构,该模型以前车速度为输入,计算跟车过程中的两个特性参数并输入神经网络以模拟驾驶员控制的自车加速度。利用处理后的数据样本对网络进行了训练,并对该模型进行了仿真验证。仿真结果表明:神经网络模型具有模拟驾驶员跟车行为的能力,模型体现出较为准确的跟踪特性,并对不同的前车工况具有良好的适应性。
基金supported by National Hi-tech Research and Development Program of China (863 Program,Grant No. 2006AA110101)"111 Program" of Ministry of Education and State Administration of Foreign Experts Affairs of China (Grant No. 111-2-11)+1 种基金General Motors Research and Development Center (Grant No. RD-209)Project of State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body,Hunan University,China (Grant No. 60870004)
文摘Lower limb injures are frequently observed in passenger car traffic accidents.Previous studies of the injuries focus on long bone fractures by using either cadaver component tests or simulations of the long bone kinematics,which lack in-depth study on the fractures in stress analysis.This paper aims to investigate lower limb impact biomechanics in real-world car to pedestrian accidents and to predict fractures of long bones in term of stress parameter for femur,tibia,and fibula.For the above purposes,a 3D finite element(FE) model of human body lower limb(HBM-LL) is developed based on human anatomy.The model consists of the pelvis,femur,tibia,fibula,patella,foot bones,primary tendons,knee joint capsule,meniscus,and ligaments.The FE model is validated by comparing the results from a lateral impact between simulations and tests with cadaver lower limb specimens.Two real-world accidents are selected from an in-depth accident database with detailed information about the accident scene,car impact speed,damage to the car,and pedestrian injuries.Multi-body system(MBS) models are used to reconstruct the kinematics of the pedestrians in the two accidents and the impact conditions are calculated for initial impact velocity and orientations of the car and pedestrian during the collision.The FE model is used to perform injury reconstructions and predict the fractures by using physical parameters,such as von Mises stress of long bones.The calculated failure level of the long bones is correlated with the injury outcomes observed from the two accident cases.The reconstruction result shows that the HBM-LL FE model has acceptable biofidelity and can be applied to predict the risk of long bone fractures.This study provides an efficient methodology to investigate the long bone fracture suffered from vehicle traffic collisions.
