Abstract

In this paper, we realize parallel parking task based on two-stage modeling method, where parking task model and vehicle dynamical model are developed respectively and incorporated into a entire model in a seamless manner. The vehicle dynamics is highly constrained by non-holonomic constraint with nonlinear tire characteristics. In order to describe vehicle dynamics, we use a new data mining based affine system modeling method. The entire parking task model is combined with several sub-parking task models, which consist of some conditions in state-input space of the system and their transitions to another. The incorporation of the both parking task model and vehicle dynamical model is realized using finite state machine. The proposed model is very general that regardless of the initial position of the vehicle, it is successfully controlled to move into the parking space. In the later part of this paper, we present a mathematical programming based optimal control scheme where the optimal inputs are selected among the permissible set of the input variable, considering all the limitations specified by linear inequalities. In order to confirm the usefulness of the proposed method, some simulation results are shown.