This paper constructs an evaluation system that reflects dangerous driving behavior. The evaluation system has a three-layer structure model of “Evaluation Index-Performance Mode-Driving behavior score.” Verification of the feasibility of the model based on the relationship between the driver and the cause of the accident based on behavioral characteristics. First, the driving return survey data and accident form information of the real traffic accident cases of China In-Depth Accident Study (CIDAS) database are counted, and the character variables are converted into digital variables. Then, a three-tier structure of the dangerous driving behavior evaluation system is built, and the correlation between the driver and the cause of the accident is conducted to verify the feasibility of the model. The research shows that the individual characteristics of drivers with dangerous driving behavior are closely related to the cause of accidents, and the evaluation system constructed in this paper can quantify and describe this relationship effectively.

It has been challenging to efficiently and accurately reproduce pedestrian head/brain injury, which is one of the most important causes of pedestrian deaths in road traffic accidents, due to the limitations of existing pedestrian computational models, and the complexity of accidents. In this paper, a new coupled pedestrian computational biomechanics model (CPCBM) for head safety study is established via coupling two existing commercial pedestrian models. The head–neck complex of the CPCBM is from the Total Human Model for Safety (THUMS, Toyota Central R&D Laboratories, Nagakute, Japan) (Version 4.01) finite element model and the rest of the parts of the body are from the Netherlands Organisation for Applied Scientific Research (TNO, The Hague, The Netherlands) (Version 7.5) multibody model. The CPCBM was validated in terms of head kinematics and injury by reproducing three cadaveric tests published in the literature, and a correlation and analysis (CORA) objective rating tool was applied to evaluate the correlation of the related signals between the predictions using the CPCBM and the test results. The results show that the CPCBM head center of gravity (COG) trajectories in the impact direction (YOZ plane) strongly agree with the experimental results (CORA ratings: Y = 0.99 ± 0.01; Z = 0.98 ± 0.01); the head COG velocity with respect to the test vehicle correlates well with the test data (CORA ratings: 0.85 ± 0.05); however, the correlation of the acceleration is less strong (CORA ratings: 0.77 ± 0.06). No significant differences in the behavior in predicting the head kinematics and injuries of the tested subjects were observed between the TNO model and CPCBM. Furthermore, the application of the CPCBM leads to substantial reduction of the computation time cost in reproducing the pedestrian head tissue level injuries, compared to the full-scale finite element model, which suggests that the CPCBM could present an efficient tool for pedestrian brain-injury research.

Pedestrians are exposed to the traffic environment without protection and thereby easily suffer serious traffic injuries when involved in a motor vehicle collision. The aims of this study were to investigate the pedestrian kinematics and ground impact in 200 real-world accident cases with video recordings. The impact velocities, pedestrian kinematics and ground impact were analysed by utilising the video information. The highest frequency of the vehicle impact velocity was estimated to be between 30 and 50 km/h. Sedan impacts led to high rotation angles of pedestrians, and the rotation angles increased as the impact velocities increased. The highest occurring frequency of kinematics involved somersaults which accounted for 39% in sedan accidents. The pedestrian rotation angle and kinematics depends on a vehicle's front shape and impact velocity. Also, the pedestrian rotation angle and kinematics can influence the pedestrian landing mechanisms including the order of the body region landing to the ground and the pedestrians’ landing posture. The findings of the accident analysis will be helpful for future studies on pedestrian protection.