Cooperative road condition estimation for an adaptive model predictive collision avoidance control strategy

This paper proposes a model predictive collision avoidance scheme for use in autonomous driving, based on cooperative on-line estimation of unknown and time varying road conditions. The autonomous vehicle is linearly modelled with constraints dependent on the road condition parameter. The proposed model predictive controller (MPC) is designed to be adaptive to this parameter. To accommodate this adaptive design, a particular method is developed for estimating the road friction coefficient cooperatively, by disseminating individual estimates in a vehicular network and using a consensus algorithm to converge these estimates to the maximum likelihood value. Presented simulation results demonstrate that the cooperative consensus scheme improves estimation significantly, and accordingly, the adaptive MPC incorporates road condition properly in collision avoidance planning.