Autonomous vehicles (AVs) bring advantages such as comfort, safety, and eco-friendliness compared to conventional ones. The focus on comfort has become increasingly important as it plays a key role in the widespread acceptance of AVs. Passenger demand for alleviating motion sickness (MS) during travel has also driven extensive research in this area. This manuscript conducts a comprehensive and comparative review of published articles to provide up-to-date research outcomes on MS mitigation. It also examines the optimization methods employed over the past two decades to enhance motion comfort in AVs. The methods for detecting and resolving MS are elaborated upon, and the research gap and challenges are addressed. Furthermore, the manuscript presents the current efficacy of the research and proposes an anti-motion sickness control framework that utilizes a cloud control platform, which might offer potential future research directions in the field of autonomous driving. This study serves as a valuable reference for future efforts and opportunities to improve the motion comfort of AVs.

A novel adaptive iterative learning control (NAILC) strategy is proposed to enhance static and dynamic control performances for the autonomous farming vehicle tracking repetitive trajectories of alternating parallel straight and large curvature. The method integrates an exponential decay function, an internal model principle (IMP), and an input constraint auxiliary variable design system in an adaptive iterative learning control framework. The introduction of exponential decay improves the convergence rate of the iterative process and ensures the control system’s dynamic performance. The IMP enhances the static performance of the trajectory tracking control system and guarantees the alignment condition setting. The auxiliary variable design system reduces the adverse effects of input constraints on the control system performance during the iterative process. Moreover, the adaptive iterative learning updating law estimates the total time-varying disturbance to improve the robustness of the tracking process against the actual disturbance. Simulation comparisons with existing results verify the effectiveness and advantages of the designed NAILC strategy under the MATLAB/Simulink environment.

Recently, a renewal interesting is focused on time-delay systems, particularly nonlinear time-delay systems. Krasovskii functional or Razumikhin function based methods have been investigated widely, since the time-delay system is described by the functional differential equation, and the stability analyzing tools are provided early with the functional or function as a parallel way with the Lyapunov stability theory. In the spirit of Lyapunov function based design method, some interesting results on backstepping design for the time-delay systems have been given, however, this is an issue that easily leads a misunderstanding. This paper would show that the problem to construct a Krasovskii functional or Razumikhin function is not a trivial problem.