Supporting personalisation of ADAS through driver characteristics - a design science study

University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

Abstract: The identification of driver characteristics is an importantstep to allow the adaptation of Advanced Driver Assistance Systems(ADAS) to individual driver needs, and thus increase system performanceand trust in the system function. However, most ADAS are designed forthe average driver and we investigated which driving characteristics arerelevant for personalised features, and how to derive them using Requirementelicitation. We conducted a design study in two iterative cycles andinvestigated the objectives by performing semi-structured interviews andliterature review. From the interviews and literature review a a list ofcharacteristics was created. The list was later used to propose a way toderive the characteristics from a driver using a Human-Machine Interactioninterface.

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