@article {pub3870,
	title = {DEVELOPMENT OF A COOPERATIVE ON-DEMAND INTERSECTION ASSISTANT-CONCEPT EVALUATION, PERSONALIZATION AND PROTOTYPE IMPLEMENTATION- 
},
	author = {Martin Ernst Heckmann AND Heiko Wersing AND Dennis Orth AND Dorothea Kolossa AND Nadja Sch{\"o}mig AND Mark Dunn},
	year = {2019},
	month = {July},
	abstract = {In this paper we present our recently introduced {\textquotedblleft}assistance on demand (AOD){\textquotedblright} concept, which allows the driver to request assistance via speech whenever he or she deems it appropriate. The target scenario we currently investigate is turning left from a subordinate road in dense urban traffic. We first compare our system in a driving simulator study to driving without assistance or with visual assistance. The results show that drivers clearly prefer our speech-based AOD approach. Next, we investigate differences between drivers{\textquoteright} left-turn behaviour. The results of this driving simulator study show that there are large inter-individual differences. Based on these results we performed another driving simulator study, where participants compared manual driving to driving with a default and a personalized AOD system. The results of this study show that the personalization very notably improves the acceptance of the system. Given the choice between driving with any of the AOD variants and manual driving, 87.5\% of the participants preferred driving with the AOD. Finally, we present an evaluation of the AOD system in a prototype vehicle in real urban traffic. },
	publisher = {Society of Automotive Engineers of Japan},
	journal = {International Journal of Automotive Engineering},
	volume = {10},
	number = {2},
	pages = {175-183}
}