Adaptive user interfaces for automotive environments

Abstract

We investigate the use of adaptive user interfaces for in-car information access. These interfaces attempt to efficiently provide content the driver needs and wants, and gather feedback on these preferences through the driver's interaction with the system. In this way, the performance of the system improves as it unobtrusively builds a more accurate model of the user. The three systems presented here are: the Adaptive Route Advisor for navigation; the Adaptive News Reader for news stories; and the Adaptive Place Advisor for restaurant selection. All of these systems provide useful information to a driver, and we argue that they do not negatively impact safety because they are replacing other less effective, information sources. We intend to test this hypothesis in future studies.