A Survey of Personalization for Advanced Driver Assistance Systems

The field of advanced driver assistance systems (ADAS) has matured towards more and more complex assistance functions, applied with wider scope and a strongly increasing user base due to wider market penetration. To deal with such a large variety of usage conditions and patterns, personalization methods have been developed to ensure optimal user experience. In this article we review current approaches in the literature that demonstrate an adaptation to the drivers' preferences, driving styles, skills and driving patterns. We discuss the general assumptions on which personalization in the automotive context is based, the general design of personalized ADAS, the current approaches with their practical realization and point out open issues in the design and implementation of a personalized driving experience. Based on this analysis we propose a general conceptual framework to personalization in ADAS. It suggests a modular decomposition for the next generation of personalized ADAS and HMI which can be expected to continuously adapt in interaction with the driver.