# Novel Motion Sickness Minimization Control via Fuzzy-PID Controller for Autonomous Vehicle
## 1 Introduction  
The autonomous vehicle is one of the rapidly evolving technologies that offer enhancement in mobility and positive contributions in terms of environmental impact [1; 2]. However, the transfer of control from the driver to an autonomous system can trigger motion sickness (MS), an uncomfortable sensation that will negatively affect the user acceptance [3]. It has been reported that MS is one of the human factor issues that needs a finer understanding, so that vehicle automation can be successfully introduced [4]. Thus, this study focuses on the MS issue in an autonomous vehicle. It is well-known that drivers experience less MS than the passengers. In terms of the behavior of the occupants, the factors of MS include the sensory conflict theory and postural instability [5]. However, this current study was inspired by the findings of [PERSON] et al. whose method was straightforward and thus easy to understand. Those authors stated that the dissimilar head tilt movements by both driver and passenger towards the direction of the lateral acceleration influenced their MS susceptibility [6; 7]. The same authors also proved that in slalom driving conditions, the head roll angle and lateral acceleration are correlated to each other. As depicted in Figure 1, in cornering situations, the passengers are more likely to tilt their heads according to the direction of lateral acceleration while the drivers are more likely to tilt their heads against the direction. An understanding of the interaction of head tilt direction and lateral acceleration is important toward the study of MS minimization. The passengers can mitigate their MS level by imitating the driver's head tilt direction or by reducing their head tilt or head roll angle towards the lateral acceleration direction. For example, a postural device has been successfully invented to reduce the passenger's head roll angle during curve driving [8; 9]. However, instead of using devices, implementing a vehicle control system appears to be more practical and less pri  
In terms of vehicle dynamics, the primary factor of MS is the lateral acceleration generated by the driver's turning skill. The greater the lateral acceleration produced by the driver, the greater the possibility that the passengers experience MS [10]. Thus, [PERSON] et al. proposed that a smooth vehicle lateral control system can solve the MS issue [11]. Improvement in the lateral control system for an autonomous vehicle can be achieved by integrating a path tracking controller with a path planner [12], dynamic speed adaptation (DSA) [13] and torque vectoring control [14]. Besides combining the path tracking controller with a high-computation control system, the lateral system can also be improved by simply adding a corrective wheel angle to the vehicle. The wheel corrector scheme is known as active steering system, where an additional angle is generated based on the controlled variables which are normally selected from the vehicle states like yaw rate and side slip [15]. [PERSON] et al. succeeded in proposing the development of a MS minimization control strategy, by introducing an estimated head roll angle to represent the controlled variable to produce a corrective wheel angle [16]. The proposed control strategy is based on the MS occurrence factors from occupant behavior and vehicle dynamic perspectives. The goal of the control strategy is to diminish the lateral acceleration to minimize the passenger's head roll angle, which will subsequently mitigate their level of MS. However, the study only applied a conventional fuzzy logic controller (FLC) as the corrective wheel angle generator. The other drawback of the study is that it only tested the MS mitigation control system in simulation. Therefore, to extend the previous study, the main contribution of this study is to propose the utilization of a fuzzy-proportional integral derivative (PID) controller to compute the corrective wheel angle and also to evaluate the proposed system in the hardware platform by using driving simulator.