Rush: repeated recommendations in an automotive context

With powerful entertainment systems in cars, the growing size of multimedia collections becomes a problem: The requirement of short interaction cycles in order not to distract the driver too much collides with the overhead of navigating thousands of items to create a playlist. We propose to use the rush interaction technique for such scenarios: The system repeatedly generates recommendations based on the user's previous choices from which the user is again able to choose and thus allows him to create a personalized playlist without much effort or distraction. In this paper, we present a discussion of this concept in an automotive context.