Real-Time Look-Ahead Distance Optimization for Smooth and Robust Steering Control of Autonomous Vehicles

This paper presents an optimization problem for the look-ahead distance used in lateral automated vehicle control. A relation is formulated to describe the sensitivity of the control input steering speed $\dot \delta $ with respect to the variation of the look-ahead distance L. The nonlinear relation is written as an LPV model using the grid-based approach. The aim is to design a controller which minimizes the steering speed $\dot \delta $ by optimizing an additional look-ahead distance Ld that is added to the nominal look-ahead distance. Such action generates a smooth/stable vehicle motion when subjected to high oscillations due to noises, large lateral errors, etc. The proposed solution is based on the Linear Parameter Varying (LPV) control approach, where an output-feedback dynamic controller is designed based on Linear Matrix Inequalities (LMIs). The control synthesis is carried out using the grid-based approach combined with the ${\mathcal{H}_\infty }$ control problem. Simulation results show the tracking performance and the smoothness of the steering input, when the vehicle is subjected to successive large lateral errors, which provides a comfortable riding.