Multistage High Gain Observer for Simultaneous Ego-Vehicle State Estimation and Vehicle Trajectory Tracking*

Accurate vehicle tracking is an important requirement on autonomous and semi-autonomous vehicles for safe operation. This paper presents a multi-stage high-gain observer formulation for vehicle tracking using various motion models. Vehicle tracking has previously relied on inaccurate relative motion models due to which tracking errors are obtained, especially during turning maneuvers of the ego vehicle. In this paper, the limitations of the previous motion models are delineated along with the development of new motion models. An important aspect of the new models is that they inherently need ego state estimates to track the other vehicles on the road. The previously developed relative models neglect the motion of the ego vehicle. In the first newly developed model the ego state estimates are accounted for in the measurement equation while in a second model, they are accounted for in the process dynamics. Furthermore, in this paper the new motion models are transformed into companion form, and a high-gain observer formulation is then provided for each model along with ego state estimation. Such a multi-stage high gain observer performs simultaneous ego state estimation and vehicle tracking for both inertial and relative motion models. The performance of this multi-stage high-gain observer is validated using experimental data from an autonomous vehicle at the University of Minnesota.