Abstract
This study proposes a method of achieving an optimised vehicle front-end profile for improved protection for both adult and child pedestrian groups, which at the same time is able to avoid designs that may cause Run-over scenarios. A hybrid model of a seven-parameter vehicle front-end geometry and a pedestrian dummy is used. Latin Hypercube sampling is utilised to generate a Plan of Experiments for the adult and child pedestrian cases. Head injury criteria results from the simulations that are tabulated as the response functions. The radial basis function method is used to obtain mathematical models for the response functions. Optimised front-end geometries are obtained using the Genetic Algorithm method. The optimised vehicle front-end profile for the adult pedestrian is shown to be different from that of the optimised profile for the child pedestrian, and optimised profiles are shown to be not mutually applicable for safety. Furthermore, Run-over scenario is observed in child pedestrian optimised profiles, where its occurrence invalidates the optimisation. A simple weighting method is used to optimise the geometry for both adult and child pedestrian groups. The Run-over occurrences are mapped using Logistic Regression and is subsequently used as a constraint for optimisation. The final optimised model is shown to achieve a safe vehicle front-end profile which equally caters for both adult and child pedestrians while simultaneously avoiding Run-over scenarios.
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