Lateral control strategy based on head movement responses for motion sickness mitigation in autonomous vehicle

Abstract

Passengers are more susceptible to motion sickness (MS) than the drivers because during cornering, they tilt their heads according to lateral acceleration direction, while the drivers tilt their heads against it. During slalom driving, high lateral acceleration that resulted from inappropriate wheel's turning will increase the severity level of MS as it contributes to a larger passenger's head roll angle towards the lateral acceleration direction. Thus, for an autonomous vehicle, it is necessary to design a smooth lateral control to obtain appropriate wheel angle to prevent high lateral acceleration. This study proposes an inner-loop lateral control strategy which utilized head roll angle as the controlled variable to generate corrective wheel angle to reduce the lateral acceleration. Firstly, an estimation model of driver's and passenger's head roll angle is developed by radial basis function network method based on the correlation between lateral acceleration and occupant's head roll angle. The driver's and passenger's models are considered as the reference and the controlled subject, respectively. Secondly, a fuzzy logic controller is adopted to generate corrective wheel angle based on the head roll angle responses. The reduction of the lateral acceleration caused by the corrective wheel angle minimized the passenger's head roll angle and hence mitigated their MS level. Simulation results show 3.25% and 10.86% reduction of motion sickness incidence in a single lap and ten laps after the proposed control strategy is applied. It is expected that the proposed control strategy will contribute to the MS mitigation study in autonomous vehicle field.

Can Variations of Vehicle Driving Status Provide Accurate Predictors of Discomfort? A Study on the Actual Driving Test

“…In data analysis using ANOVA, it is found that when the vehicle is in a turning or lane changing state, the lateral acceleration and yaw angular velocity of the vehicle has a significant impact on the passenger's comfort, i.e., compared with other driving status, passengers in turning or lane changing state are more likely to experience discomfort， which is consistent with the conclusion of Saruchi et al [12,13].…”

“…Rinaldi et al [11] evaluated the results by using the Lilliefors test and discussed the influence of lateral acceleration and angular acceleration on the symptoms and level of motion sickness of people. Saruchi et al [12,13] proposed an inner-loop lateral control strategy which utilized head roll angle to generate corrective wheel angle to reduce the lateral acceleration, and a time delay neural network (TDNN) was utilized to model the correlation of the occupant's head movement and lateral acceleration. However, they don't pay attention to the motion of buses except for lateral vection (Vection refers to various cognitive factors that can influence self-motion perception in virtual reality), such as vertical and longitudinal vection, which could cause discomfort to passengers.…”

Design and Implementation of a Position, Speed and Orientation Fuzzy Controller Using a Motion Capture System to Operate a Wheelchair Prototype

“…The controller validation was carried out with a person with null mobility in lower limbs as shown in Figure 17. Saruchi et al [50] developed a fuzzy orientation controller to drive their prototype, which has linguistic variables related to the input error and output error. In contrast, this research has Euler angles as inputs of the system and direction as output.…”

Electrogastrography in Autonomous Vehicles—An Objective Method for Assessment of Motion Sickness in Simulated Driving Environments

“…Reduced comfort offered by the AVs due to MS can overshadow their other benefits which are more important for the society (reduced fuel consumption, security, car sharing possibilities, etc.). One of the suggested approaches to MS symptoms mitigation in AVs is a smoother lateral acceleration than a human driver may perform [ 9 , 10 ], possibly leading to different (milder) sickness in comparison to passenger sickness in human-driven vehicles. Finding a real-time method for assessment of MS or its symptoms in autonomous vehicles could be therefore useful for early detection and development of in-vehicle infotainment concepts and driving algorithms that could further reduce or minimize MS symptoms.…”