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Advanced driver assistance systems already help drivers reach their destinations safely and more comfortably. Future systems will evolve from driver assistance over highly automated vehicles to fully automated driving. With an increasing level of automation, automated functions will reduce the driver's burden more and more, thereby creating space for productivity, communication or entertainment while driving. In this article we outline our roadmap for future automated vehicles, assess the key challenges for introduction and give an overview of the major algorithmic components.

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In recent years various collision warning systems for rear-end crash situations have been introduced into the market. Their goal is to reduce the number of fatalities and to mitigate collision consequences. The challenge in the design for such functions is to achieve a high effectiveness for both attentive and inattentive drivers. A possible approach could be an adaptation of the human-machine interface (HMI) to driver attentiveness levels.This paper presents a preliminary study of different visualacoustical HMI concepts performed in a driving simulator. The participants completed two drives with each warning signal. In the first drive they were distracted by a secondary task and in the second one they were in an attentive state. The statistical analysis of the inattentive drivers' data showed a significant reaction time reduction by employing an acoustical speech warning. A visual alert for inattentive subjects did not result in an additional reduction. Only a simple and intuitive visual display showed a significant reduction of response time for attentive participants. The results of this study show that for varying driver attentiveness levels a warning intensity adaptation is needed in order to increase the benefit and acceptance of the collision warning.

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