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 number of possible users due to wider market penetration. To deal with such a large variety of use conditions and usage patterns, personalization methods have been developed to ensure optimal user experience and supplied system function. In this paper we review personalization approaches for ADAS systems that target 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, and their practical realization and point out open issues in the design and implementation of a personalized driving experience.
Personalization in advanced driver assistance systems and autonomous vehicles: A review
2017-10-01
84273 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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