In this study, a control algorithm of an autonomous vehicle is proposed on the basis of risk level to simulate control motion of a real driver. The normal traffic situation can be expressed by risk level. The risk level is affected by several risk elements: roadside edges, curves, the other vehicles, obstacles, and so on. Each risk element is represented by an exponential function. The risk elements make risk potential field on the road. It is assumed that the desirable course to follow is determined as the point of minimum risk potential in the cross section of the road. Tree prediction models are examined to predict the future position of vehicle. The change of preview time is considered on the curved road. A lateral and longitudinal control algorithm with the prediction model proposed in this study shows similar control motion to that of a real driver.