This paper presents the analysis of the stopping maneuver of the human driver by using a new three-dimensional driving simulator that uses CAVE, which provides stereoscopic immersive vision. First of all, the difference in the driving behavior between 3D and 2D virtual environments is investigated. Secondly, a GMDH is applied to the measured data in order to build a mathematical model of driving behavior. From the obtained model, it is found that the acceleration information has less importance in stopping maneuver under the 2D and 3D environments.

This paper describes a design scheme of generalized minimum variance controllers (GMVC) using a group method of data handling (GMDH) network for nonlinear systems. Concretely, the predictive value of the output required in the GMVC is obtained by using the GMDH which is a kind of multilayered networks. Since the predictive value of the output in GMVC is calculated by a nonlinear model which is generated by the GMDH network, one can expect to obtain the better control performance than that by the conventional scheme. The behavior of the newly proposed control scheme is evaluated on numerical examples.