Intelligent vehicle systems have introduced the need for designers to consider user preferences so as to make several kinds of driving features as driver friendly as possible. This requirement raises the problem of how to suitably analyse human performance so they can be implemented in automatic driving tasks. The framework of the present work is an adaptive cruise control with stop and go features for use in an urban setting. In such a context, one of the main requirements is to be able to tune the control strategy to the driver's style. In order to do this, a number of different drivers were studied through the statistical analysis of their behaviour while driving. The aim of this analysis is to decide whether it is possible to determine a driver's behaviour, what signals are suitable for this task and which parameters can be used to describe a driver's style. An assignment procedure is then introduced in order to classify a driver's behaviour within the stop and go task being considered. Finally, the findings were analysed subjectively and compared with a statistically objective one. (Author/publisher)
Abstract