A new method for road profile estimation in time domain with the application of vehicle system response was presented in this paper, and the problem was transformed as a system identification issue for an inverse nonlinear quarter vehicle model. Firstly, the inverse vehicle dynamic model was trained with specifically chosen white noise signal, and then eight different types of membership functions (MF) for Adaptive Neuro Fuzzy Inference System (ANFIS) were compared. Finally, the comparison of three different methods: ANFIS, Recursive Least Square (RLS) and Group Method of Data Handling (GMDH) were researched with different vehicle speeds and different road levels in the simulation part. The results showed that ANFIS is better in comparison with RLS and GMDH and this method can be further applied for vehicle system analysis.

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