  This paper presents methods for vehicle state estimation and prediction for
autonomous driving. A roundabout is chosen to apply the methods and illustrate
the results as autonomous vehicles have difficulty in handling roundabouts.
State estimation based on the unscented Kalman filter (UKF) is introduced first
with application to a roundabout. The microscopic traffic simulator SUMO is
used to generate realistic traffic in the roundabout for the simulation
experiments. Change point detection based driving behavior prediction using a
multi policy approach is then introduced and evaluated for the round
intersection example. Finally, these methods are combined for vehicle
trajectory estimation based on UKF and policy prediction and demonstrated using
the roundabout example.
