Vehicle and road state estimation using interacting multiple model approach

Abstract

This article describes the estimation algorithm of the vehicle state and the road condition, which is formulated on the basis of the interacting multiple model algorithm. Ten system modes of tire are modeled (considered nonlinearity) according to the road friction. Ten system modes are provided for switching from one mode to another in a probabilistic manner. The mode probabilities and states of vehicle are estimated based on extended Kalman filter (EKF). This algorithm is evaluated in the simulation study. Simulation results show that the algorithm is effective in the state estimation of vehicle and road surface.

Keywords:

• State estimation
• Multiple model
• Interacting multiple model
• Road friction
• Side-slip angle

Acknowledgements

A part of this study was supported by the Program for Promoting Fundamental Transport Technology Research from the Japan Railway Construction, Transport and Technology Agency (JRTT).