To reduce the number of accidents and traffic injuries or deaths, the driver of a modern car is assisted by various Advanced Driving Assistance Systems (ADAS). They can interact with the driver as well as independently influence the driving dynamics in case of an imminent accident. Due to its lack of a passenger cabin, a motorcycle has less potential of passive safety. This leads to a crucial need of active safety systems, but until today only reactive systems are available. They are merely able to react to rider’s actions and can for example reduce the rider’s brake pressure or throttle demand, but there are no active systems that can e.g. brake autonomously. Active and autonomously acting assistants are still not existent in the world of motorcycle safety. This paper presents an efficient model-predictive controller for a motorcycle, based upon a hierarchical model of the human steering behavior, that can be used for advanced rider assistance systems (ARAS).