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Vehicle traffic accidents have been extensively studied in various countries, but any differences in traffic accidents the studied areas have not yet been adequately investigated. This paper aims to make a comparison study of head injury risks and kinematics of adult pedestrian accidents in Changsha, China, and Hannover, Germany, as well as correlate calculated physical parameters with injuries observed in real-world accidents of the two cities. A total of 20 passenger cars versus adult pedestrian accidents were collected from the two areas of study, including 10 cases from Changsha and 10 cases from Hannover. Virtual accident reconstructions using PC-Crash and MADYMO software were performed. The in-depth study focused on head injury risks while kinematics were conducted using statistical approaches. The results of the analysis of the Chinese data were compared with those of the German data.

Head injury is quite frequently occurred in car-to-pedestrian collisions, which often places an enormous burden to victims and society. To address head protection and understand the head injury mechanisms, in-depth accident investigation and accident reconstructions were conducted. A total of 6 passenger-cars to adult-pedestrian accidents were sampled from the in-depth accident investigation in Changsha China. Accidents were firstly reconstructed by using Multi-bodies (MBS) pedestrian and car models. The head impact conditions such as head impact velocity; position and orientation were calculated from MBS reconstructions, which were then employed to set the initial conditions in the simulation of a head model striking a windshield using Finite Element (FE) head and windshield models. The intracranial pressure and stress distribution of the FE head model were calculated and correlated with the injury outcomes.

The aim of the study was to investigate the difference between car-to-e-bikes and car-to-pedestrian accidents. The China In-depth Accident Study (CIDAS) database was searched from 2011 to 2013 for pedestrians and e-bikes struck by car, van and SUV fronts, which resulted in 104 pedestrian and 85 e-bike cases where information was sufficient for in-depth analysis. Reconstruction by PC-Crash was performed for all of the sampled cases. Pre-crash parameters were calculated by a MATLAB code. Focus was on prototypical accident scenarios and causes; speed as well as possible prevention countermeasures. It has been shown that traffic light violations, road priority violations, and unsure safety (these situations included misjudgments, unpreparedness, proximity to other road users, inappropriate speeds, etc.…) are the main causes in both the VRU groups. Distinctions were found for aspects of car collision speed, accident scenario, distribution of head contact points and so on.

The two-wheeler is a vehicle that runs on two wheels, which is classified as motorcycle, electric-bicycle, and bicycle in this research. China has the largest number of two-wheelers and relevant accidents in the world. The two-wheeler riders have a high level of vulnerability, creating a significant necessity to better understand the characteristics according to the road-user group. The objective of this paper is to study the characteristics and analyze the causes of two-wheeler accidents in China using the CIDAS (China In-Depth Accident Study) Database. 2012 cases of two-wheeler accidents with riders injured or dead were collected from the CIDAS Database from 5 cities (Changchun, Beijing, Weihai, Ningbo and Foshan) in China over a period of 5 years (2011.07-2016.06).

In China, nearly 25% of traffic fatalities are pedestrians. To avoid those fatalities in the future, rapid development of countermeasures within both passive and active safety is under way, one of which is autonomous braking to avoid pedestrian crashes. The objective of this work was to describe typical accident scenarios for pedestrian accidents in China. In-depth accident analysis was conducted to support development of test procedures for assessing Autonomous Emergency Braking (AEB) systems. Beyond that, this study also aims for estimating the mitigation of potential crash severity by AEB systems. The China In-depth Accident Study (CIDAS) database was searched from 2011 to 2014 for pedestrian accidents. A total of 358 pedestrian accidents were collected from the on-site in-depth investigation in the first phase of CIDAS project (2011-2014).