Adaptive Cost Function-Based Shared Driving Control for Cooperative Lane-Keeping Systems With User-Test Experiments
Mohamed Radjeb Oudainia, Chouki Sentouh, Anh‐Tu Nguyen, Jean‐Christophe Popieul
Abstract
This article presents a new shared control method with a dynamic driver-automation conflict management for cooperative lane keeping systems (LKS) of automated vehicles. Based on a human-centered control approach, the proposed shared control design takes into account the driver's activity and availability, as well as the surrounding risk to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dynamically</i> adapt the driving assistance level via an adaptive cost function. To this end, we propose a method to characterize in real-time the driver's activity, which allows for an appropriate assistance level according to the driving conditions. Linear parameter-varying (LPV) control technique is leveraged to deal with the time-varying nature of the vehicle speed and the level of assistance. The uncertainties of the lateral tires forces are taken into account in the control design via a norm-bounded representation. Using Lyapunov stability theory, the control design conditions are derived in terms of linear matrix inequality (LMI) constraints, which can be effectively solved by semidefinite programming techniques. User-test experiments are performed with the SHERPA dynamic car simulator to demonstrate the effectiveness of the proposed shared control method from both objective and subjective viewpoints.