Adaptive vehicle motion estimation and prediction

Accurate motion estimation and reliable maneuver prediction enable an automated car to react quickly and correctly to the rapid maneuvers of the other vehicles, and so allow safe and efficient navigation. In this paper, we present a car tracking system which provides motion estimation, maneuver prediction and detection of the tracked car. The three strategies employed-adaptive motion modeling, adaptive data sampling, and adaptive model switching probabilities-result in an Adaptive Interacting Multiple Model algorithm (AIMM). The experimental results on simulated and real data demonstrate that our tracking system is reliable, flexible, and robust. The adaptive tracking makes the system intelligent and useful in various autonomous driving tasks.