As the delta‐v‐based injury models used to evaluate intelligent driving systems are always fitted with European or American crash database, they cannot achieve wide application in those countries where limited in‐depth analysed crash data are recorded. An injury model which is based on easily accessible information, is urgently needed. In this study, a deformation depth based injury risk model is proposed to overcome the limitation of delta‐v. First, a correlation between the vehicle deformation depth and occupant injury risk is verified from the aspects of retrospective safety assessment and stiffness cluster analysis using German in‐depth accident study and national automotive sampling system–crashworthiness data system. Furthermore, injury risk‐deformation functions are regressed for different stiffness clusters using the crash data. The fitting accuracy reaches 97%, higher than the existing literature. A novel safety benefit assessment simulation platform is built with the regressed injury risk model. Based on this platform, an autonomous emergency braking system is evaluated. Only 1% error of the safety benefit exists between the proposed model and the delta‐v based one.
Vehicle deformation depth based injury risk function for safety benefit evaluation of crash avoidance and mitigation systems
IET Intelligent Transport Systems ; 12 , 5 ; 386-393
2018-06-01
8 pages
Article (Journal)
Electronic Resource
English
stiffness cluster analysis , sampling methods , safety benefit evaluation , crash avoidance , mitigation systems , retrospective safety assessment , national automotive sampling system‐crashworthiness data system , intelligent driving systems , German in‐depth accident study , intelligent transportation systems , vehicle deformation depth based injury risk function
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