Previous work proposed an optimal control framework for modeling driver behavior. Drivers were assumed to minimize the predicted subjective effort of their control actions, taking into account the anticipated actions of other drivers. The framework was generic. Several assumptions and simplifications had to be made; this factor hampered the applicability of the framework. One of these assumptions was that the behavior of other vehicles in the flow was stationary during the prediction horizon. Furthermore, the resulting model was computationally complex. A new approach based on the generic optimal control framework is proposed for modeling and computing driving behavior. The model can deal with the dynamics of the vehicles to which a driver reacts. At the same time, the computational complexity is small and does not increase exponentially with the complexity of the prediction model or with the size of the control vector. The mathematical solution approach is presented and illustrated with several examples. Face validity of the model is shown, and an application of the theory in the field of automated vehicle guidance is discussed. In particular for these applications, the proposed optimization approach allows for the computation of cooperative driving strategies that minimize a generic range of objective functions. The improvements in performance made by cooperation are substantial, as illustrated by several examples.