An Assisted Driver Model. towards Developing Driver Assistance Systems by Allocating Support Dependent on Driving Situations

Partially automated driving is expected to increase traffic efficiency. However, automation causes human factors concerns. One concern is the reduced operability during transitions between automation level, e.g. when failures occur. These concerns ask for a more justifiable implementation of automation for automobile appliances. As a first step towards applicable solutions for driver support, we developed the assisted driver model. The attempt with this model was to answer: what driving situations are in need for what kind of support? The influence of different levels of automation on task performance, were used to define 7 recommended support types relevant for driver assistance. For the allocation of recommended support types to distinguished driving situations we then considered the prerequisites to provide good operability in terms of the avoidance of errors and familiarity with driving circumstances. An assessment of adaptive cruise control showed the model‟s potential to help developing advanced driver assistance systems whilst anticipating concerns associated with the appliance of partial automation.