Thumbnail
Access Restriction
Open

Author Zou, Tiefang ♦ Yi, Liang ♦ Cai, Ming ♦ Hu, Lin ♦ Li, Yuelin
Editor Xu, Jun
Source Hindawi
Content type Text
Publisher Hindawi
File Format PDF
Copyright Year ©2018
Language English
Abstract The knowledge about the injury source and correlation of riders in car-electric bicycle accident will be helpful in the cross validation of traces and vehicle safety design. In order to know more information about such kind of knowledge, 57 true car-electric bicycle accidents were reconstructed by PC-Crash and then data on injury information of riders were collected directly from the reconstructed cases. These collected data were validated by some existing research results firstly, and then 4 abnormal cases were deleted according to the statistical method. Finally, conclusions can be obtained according to the data obtained from the remaining 53 cases. Direct injuries of the head and right leg are from the road pavement upon low speed; the source laws of indirect head injuries are not obvious. Upon intermediate and high speed, the injuries of the above parts are from automobiles. Injuries of the left leg, femur, and right knee are from automobiles; left knee injuries are from automobiles, the road pavement and automobiles, respectively, upon low, intermediate, and high speed. The source laws of indirect torso injuries are not obvious upon intermediate and low speed, which are from automobiles upon high speed, while direct torso injuries are from the road pavement. And there is no high correlation between all parts of the injury of riders. The largest correlation coefficient was the head-left femur and left femur-right femur, which was 0.647, followed by the head-right femur (0.638) and head-torso which was 0.617.
ISSN 11762322
Learning Resource Type Article
Publisher Date 2018-04-08
Rights License This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
e-ISSN 17542103
Journal Applied Bionics and Biomechanics
Volume Number 2018
Page Count 15


Open content in new tab

   Open content in new tab