To provide a traffic lane followup control device of an anticipational control system capable of being achieved using only the information measurable relatively easily and accurately.

A vehicle model and target course model are prepared using DARMA(Deterministic Auto Regressive Moving Average) model which acquires anticipational information of the target course by processing the image data, for example given by a CCD camera 2, assumes it as a definitive turbulence, enters a front wheel steering angle command value δc, and emits the lateral displacement amount ye of the vehicle off from the target course. The generalized predictional control(GPC control) theory is expanded and applied to the vehicle model and target course model so as to compensate the car lane followup error for a future definitive turbulence. This allows eliminating any vehicle state quantity presumer, and it is possible to establish the same performance as a state quantity feedback anticipational control system.