A Comparative Study of Vehicle Front Shape Based on Multi-Objective Optimization for Minimizing Injury Risks in Pedestrian and Cyclist Impact

This study aims to explore the influence of a vehicle front-end shape on pedestrian and cyclist injuries. The injuries of head, upper leg and lower leg based on 50^th human model are considered as design response. A multi-objective optimization approach is developed to design and optimize the front shape for minimizing injury risks of pedestrian and cyclist in this study. The numerical models of pedestrian-vehicle and cyclist-vehicle impact is constructed and validated first. Then, the optimal Latin hypercube sampling (OLHS) method is adopted for design of experiment (DOE) and the surrogate model is constructed through radial basis function (RBF). The optimal problems involving a number of objectives are solved by the multi-objective particle swarm optimization (MOPSO) algorithm in this study. With the optimization design of vehicle front shape by using pedestrian-vehicle impact and cyclist-vehicle impact, the optimal front shape is obtained although some design variables strongly compete with each other.