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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 50th 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.