Control Reconfiguration of Lateral ADAS Steering Control in the Presence of Driver Errors Using Combined Parity Space / LPV Approaches

Abstract

This paper proposes a lateral Advance Driver Assistance System (ADAS) steering controller that uses the detection of driver errors to reconfigure a Linear Parameter Varying (LPV) controller acting on the combined drivervehicle lateral steering system. The detection of driver errors is proposed to be formulated as a Fault Detection problem using the Parity Space approach, and the computed residual signal then schedules the LP V /H∞ controller. The overall goal is to compute an ADAS controller that helps in stabilizing the vehicle when driver errors are detected while otherwise minimizing the level of intrusiveness. With this goal in mind, the proposed method was tested in simulation using a full dynamical model of a Renault Megane car and driver models, for simulation of the human steering action, during a critical scenario.

MPC-based optimal parameter scheduling of LPV controllers: Application to Lateral ADAS Control

“…The simulation environment is the same as in [12]: a realistic, nonlinear full-model of a Renault Megane car [5], [14] is used to mimic the vehicles dynamics. The driver, simulated using a driver model, must perform an emergency double-lane change (DLC) maneuver at high speeds v x = 40 m/s.…”

“…The goal here is not control design itself, but rather to focus on the problem of correctly scheduling this adaptive LPV control scheme online. Full details on the ADAS controller synthesis are given in [12], and a summary is presented in section III.…”

“…In this Section, we summarise the main contribution from the preliminary work [12]. The main goal of such a strategy is to determine an auxiliary steering command that will not be felt invasive by the driver, and thus shall only act when needed to maintain vehicle and passenger safety.…”

“…In this work, the proposed MPC-based approach is used to extend the preliminary result obtained by the Authors in [12], regarding an Advanced Driver Assistance System (ADAS) for the lateral control of vehicles. Specifically, we consider an LPV ADAS (H ∞ ) controller, for which a hyperbolic function was previously used to map the design-related scheduling parameter w.r.t.…”

“…Sec. III briefly explains how the LPV state feedback H ∞ ADAS control K(ρ) was designed as in [12]. In Sec.…”