The development of an automatic driving system is accompanied by the increasing importance of driver monitoring. It is necessary to estimate the state of the driver including actions with less load on the driver. In this study, we used the seat pressure as an indicator to assess the status of a driver. In the experiment, we measured the seat pressure during automatic operation under the designated state (forward gaze, cell phone use and sleeping) of the driver. Characteristic changes in the center of gravity position of the driver were confirmed during cell phone use and sleeping. Subsequently, we evaluated seating surface pressure data by calculating the accuracy of state estimation using machine learning. The results show that the accuracy of estimation corresponded to 76.8% in the overall evaluation. This suggests that it is possible to estimate the state of the driver during automatic driving using seat pressure.