So as to create innovative car silhouettes, we propose in this paper a model based on an Interactive Genetic Algorithm using an encoding of a design solution by a Fourier analysis approach. This model permits the designer to browse through generations of car profiles from an initial population of existing silhouettes. By qualitatively assessing each individual, the designer converge towards solutions complying with his/her requirements and preferences, possibly creating novelty and generating surprise. We describe here tests for assessing the efficiency of this innovative design platform. These tests are mainly based on a similarity index, a similarity measure being the perceived distance between two cars silhouettes. The results highlight a good convergence toward a satisfactory solution. In addition, this design process turns out to be very flexible because of the local and intuitive modifications allowed on a given individual solution at any moment of the design process.