A. Kalra, Vishal Gupta, M. Shen, X. Jin, C. Chou, King H. Yang
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Pedestrian safety: an overview of physical test surrogates, numerical models and availability of cadaveric data for model validation
Numerous efforts have been made to replicate pedestrian-car crashes experimentally or numerically to study the pedestrian injury biomechanics for developing countermeasures for pedestrian protection. This overview summarises such efforts towards pedestrian safety and available surrogates used in optimisation of pedestrian-friendly vehicle designs. This paper provides not only available physical surrogates (impactors and pedestrian dummies) used by different regulatory agencies, but also a collection of various numerical models used to predict injury responses in car-pedestrian impacts. Additionally, an overview of many reported cadaveric experiments performed as sustained by pedestrians in car crashes is presented. A validation matrix is proposed for correlating existing/future numerical models with available cadaveric test data. This is to ensure development of high predictive quality FE whole body human models to assess injury risk to pedestrians in car crashes, and in turn for continued improvement over design of pedestrian friendly vehicle front-end and effective countermeasures for pedestrian protection.
期刊介绍:
The IJVS aims to provide a refereed and authoritative source of information in the field of vehicle safety design, research, and development. It serves applied scientists, engineers, policy makers and safety advocates with a platform to develop, promote, and coordinate the science, technology and practice of vehicle safety. IJVS also seeks to establish channels of communication between industry and academy, industry and government in the field of vehicle safety. IJVS is published quarterly. It covers the subjects of passive and active safety in road traffic as well as traffic related public health issues, from impact biomechanics to vehicle crashworthiness, and from crash avoidance to intelligent highway systems.