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Vehicle dynamics and external disturbance estimation for vehicle path prediction

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3 Author(s)
Chiu-Feng Lin ; Vehicle Eng. Dept., Nat. Pintung. Polytech. Inst., Pintung, Taiwan ; A. G. Ulsoy ; D. J. LeBlanc

This paper addresses the onboard prediction of a motor vehicle's path to help enable a variety of emerging functions in autonomous vehicle control and active safety systems. It is shown in simulation that good accuracy of path prediction is achieved using numerical integration of a linearized two degree of freedom vehicle handling model. To improve performance, a steady-state Kalman filter is developed to estimate the vehicle's lateral velocity and the magnitudes of external disturbances acting on the vehicle, specifically the lateral force and the yaw moment disturbances. A comparison is made between three models of external disturbance time variation; a piecewise-constant-in-time model is found to be sufficient. Finally, an algorithm is proposed to characterize path prediction uncertainty using a statistical characterization of the measurement and modeling errors. Simulation suggests that these algorithms may provide a useful suite of path prediction tools for a variety of applications

Published in:

IEEE Transactions on Control Systems Technology  (Volume:8 ,  Issue: 3 )