Feature evaluation for lane change prediction based on driving situation and driver behavior

Advanced driver assistance systems rely on the availability of robust information on the driving situation and the driver's needs and intentions to operate reasonably and safely. For this, they have to be enabled to identify and assess both the driving situation and the driver's intentions on the basis of features that can be measured by the vehicle. In case of the prediction of lane change maneuvers intended by the driver, a set of features is available describing the driving situation before lane changes, the driver's maneuver preparation and the vehicle's status. Against this background, the work presented aims at evaluating the suitability of these features to provide evidence to the maneuver prediction and at identifying suitable predictors on arterial roads in urban areas. Data obtained by a naturalistic driving study are used to evaluate and compare the effect sizes of each of the individual features in connection with different types of lane change maneuvers and with regard to the time of prediction.