User-adaptive interface based on mental model and symbol matching

We design a user-adaptive interface that is adapted to a driver considering his/her personal differences. This paper deals with the interactive adaptation interface based on probability model of hidden Markov model and symbol matching for in-vehicle information systems. This interface builds a user´s navigation pattern model by navigation data and recommends symbols or clues which are affected by the user model. User´s intention is inferred by the interactive behavior between the driver and the interface which is symbol matching. As an application example, we present a car navigation system and experiments were performed to confirm the effectiveness on the reduction of the response time.