@article {pub3534,
	title = {A survey of personalized driver assistance systems},
	author = {Martina Hasenj{\"a}ger AND Martin Ernst Heckmann AND Heiko Wersing},
	year = {2020},
	month = {June},
	abstract = {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. In this paper we develop a general conceptual framework to personalization in ADAS. Against this background we review current approaches in the literature that target an adaptation to the drivers{\textquoteright} 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.
},
	publisher = {IEEE},
	journal = {IEEE Transactions on Intelligent Vehicles},
	volume = {5},
	number = {2},
	pages = {335 -- 344}
}