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Incompatibility between two colliding cars is becoming an important issue in passive safety engineering. Among various phenomena, indicating signs of incompatibility, over-riding and under-riding are likely caused by geometrical incompatibility in vertical direction. The issue of over-riding and under-riding is, therefore, not only a problem for partner-protection but also a possible disadvantage in self-protection. One of the possible solutions of this dual contradictory problem is to have a good structural interaction between the front-ends of two cars. Studies have been done to develop a test protocol for assessment of this interaction and to define criteria for evaluation but mostly in terms of aggressivity, which is a term describing incompatibility of a relatively stronger car. In this study, it was hypothesized that homogeneous front-end could be a possible better solution for good structural interaction.

Most of the existing control techniques applied to automobiles are based on a linear model of the relevant dynamic system. However, in spite of the increasing demand for more sophisticated vehicles, very little research is being directed toward understanding and predicting the nonlinear response caused by non-predictable operating conditions such as the variation of suspension characteristics due to wear and tear or the frictional coefficient of the road. In this research, we used a neural network based identification technique to predict the structural response of dynamic systems and validated the technique through comparison with experimental data obtained with a cantilever beam. This identification technique is further extended to forecast the frictional coefficient μ of roads. Numerical results indicate promising future applications.