Model analysis of adaptive car driving behavior

This paper deals with two modeling approaches to car driving. The first one is a system theoretic approach to describe adaptive human driving behavior. The second approach utilizes neural networks. As an illustrative example the overtaking task is considered and modeled in system theoretic terms. Model results are used to teach a neural network. The results show that a neural network is able to learn this task even when certain task variables change. The next step is to perform an experiment with real human operators in order to assess the validity of both modeling approaches and their relative merit