Modeling driver behavior at roundabouts: Results from a field study

Abstract

Advanced Driving Assistance Systems could improve driving safety and comfort by supporting drivers in their driving task. To realize intelligent assistance, driver behavior prediction and recognition is an important challenge. Therefore, the aim of this study is to develop a method to predict whether a vehicle, having entered a roundabout, will choose an upcoming exit or stay within the roundabout. A field study has been conducted to collect driving behavior data for analyzing and modeling human driver behavior in interaction with roundabouts. Support vector machines proved to be a robust and efficient classification method for the roundabout leaving/ staying pattern recognition problem. From the experimental results the vehicles position can be estimated, for which the prediction becomes reliable. The steering wheel angle and angle velocity also proved to be able to provide sufficient information to predict the driver behavior at the investigated roundabouts.