Motion Sickness Incidence Research Articles

Studi Motion Sickness Incidence (MSI) Pada Kapal Patroli (KAL-28) Katamaran

Motion sickness or seasickness is a condition caused by the movement of a ship that results in dizziness, nausea, and vomiting. The Motion Sickness Incidence (MSI) Study on the Patrol Catamaran (KAL-28) aims to evaluate the comfort level of passengers and the safety of the ship's crew during operations, following the ISO 2631/1997 standards. The evaluation is conducted on the vertical acceleration response of the ship under various wave conditions, speeds, and wave directions. Mapping is performed in various areas of the ship, including the deck, navigation room, and engine room, considering wave heights of 0.875 meters and 2 meters at speeds of 15 knots, 22.5 knots, and 30 knots. The research results indicate that at a speed of 15 knots, the deck area, navigation room, and engine room meet the criteria from comfortable to somewhat uncomfortable. However, at speeds of 22.5 knots and 30 knots, these areas are rated as somewhat uncomfortable to very uncomfortable. This study emphasizes the need for ship design that considers both passenger comfort and safety, especially for patrol catamarans

Numerical Analysis of Ship Motion of Crew Boat with Variations of Wave Period on Ship Operational Speed

Seakeeping is influenced by several factors such as speed, ship hull shape, and the direction of the waves (heading angle). In this research, the crew boat is analyzed using the 3D Diffraction method to obtain the response of the ship's motion at regular waves. The study focused on analyzing the sea motion of the crew boat at different wave periods (2.58 s, 4.12 s, 5.67 s, and 7.22 s) and variation of ship speeds (0 Knot, 3 knots, 6 knots, 9 knots, 12 knots, 15 knots, and 18 knots). It used input data including the heading angle of the wave (μ) which is 180° and at a wave height of 0.5 m. The numerical analysis was carried out to determine the ship's seakeeping and compare it with NORDFORSK 1987 criteria, and also to identify the Motion Sickness Incidence (MSI) of the crews on board. Based on the results obtained, the seakeeping value of the ship accepted the criteria of NORDFORSK 1987 up to a speed of 9 knots, starting at a speed of 12 knots it does not accept the criteria. As for the operability, the comfort level of the crew while on board has an MSI index of 0% for 0 Knot, and an MSI index for 18 knots is 4.46% of the total crew of the ship namely only 1 person from 25 persons will likely feel sea sickness.

Evaluation of Ride Comfort under Vortex-Induced Vibration of Long-Span Bridge

The increasing number of suspension bridges has led to designs favoring greater length and flexibility, resulting in a common problem of vortex-induced vibration. While vortex-induced vibration typically does not cause structural damage, it diminishes the bridge’s fatigue resistance and has a detrimental impact on ride comfort. Additionally, this study introduces a road–bridge–vehicle vibration model, proposing an evaluation method for assessing ride comfort during vortex-induced vibrations in long-span bridges. This method features simplified modeling and swift calculations, circumventing the need for intricate finite element modeling and iterative solving. Furthermore, it evaluates ride comfort for vehicles crossing a prototype long-span suspension bridge using the Overall Vibration Total Value (OVTV) and Motion Sickness Incidence (MSI) criteria. This study also analyzes the influence of various parameters on OVTV and MSI, including vehicle speed, road grade, vortex-induced vibration frequency, and amplitude. It establishes a reference limit for vortex-induced vibration amplitude based on OVTV and MSI values. Moreover, the study substantiates that, within the context of vortex-induced vibration, the MSI value is more suitable for evaluating driving comfort compared to the OVTV.

MOTION SICKNESS INCIDENCE (MSI) PREDICTION ON 80 M LNG SHIP CARRIER

The motion of ships is move up and down or shocking on the high seas caused by large and continuous waves can cause symptoms of illness in the form of dizziness, nausea and even vomiting which is often termed as seasickness (sea sickness or motion sickness). In this research, a study was conducted on the results of calculations and simulations of the vertical acceleration of the LNG ship's movement so that it could be seen the performance of the ship on crew comfort. Overall Motion Sickness Incidence (OMSI), is also presented as one of the outputs for this crew comfort level prediction, where in this OMSI calculation uses 3 different sea-states and also in each sea-state it is simulated with 3 types of periods (Tz) at service speed (Vs) 20 knots. ISO 2631 standard states seasickness is not experienced at speed 20 at 45, 135 or 180 degrees. After 8 hours, seasickness occurs when hit by 90 degrees. Moderate water conditions and rough water do not cause motion sickness at 0 and 45 degrees.

INTELLIGENT MONITORING OF A LARGE CATAMARAN FERRY

Wave load cycles, wet-deck slamming events, accelerations and motion comfort are important considerations for high-speed catamarans operating in moderate to large waves. Although developing a hull monitoring system according to classification guidelines for such vessels is broadly acceptable, the data processing requirements for outputs such as rainflow counting, filtering, probability distribution, fatigue damage estimation and warning due to slamming can be as sophisticated to implement as the system components themselves. Advanced analytics such as machine learning and deep learning data pipelines will also create more complexities for such systems, if included. This paper provides an overview of data analytics methods and cloud computing resources for remotely monitoring motions and structural responses of a 111 m high-speed catamaran. To satisfy the data processing requirements, MATLAB Reference Architectures on Amazon Web Services (AWS) were used. Such combination enabled fast parallel computing and advanced feature engineering in a time-efficient manner. A MATLAB Production Server on AWS has been set up for near real-time analytics and execution of functions developed according to the class guidelines. A case study using Long Short‑Term Memory (LSTM) networks for ship speed and Motion Sickness Incidence (MSI) is provided and discussed. Such data architecture provides a flexible and scalable solution, leading to deeper insights through big data processing and machine learning, which supports hull monitoring functions as a service.

Assessing the Welfare of Technicians during Transits to Offshore Wind Farms

Available decision-support tools rarely account for the welfare of technicians in maintenance scheduling for offshore wind farms. This creates uncertainties, especially since current operational limits might make a wind farm accessible but the vibrations from transits might be unacceptable to technicians. We explore technician exposure to vibration in transit based on the levels of discomfort and the likelihood of seasickness occurring on crew transfer vessels (CTVs). Vessel motion monitoring systems deployed on CTVs operating in the North Sea and sea-state data are used in a machine learning (ML) process to model the welfare of technicians based on operational limits applied to modelled proxy variables including composite weighted RMS acceleration (aWRMS) and motion sickness incidence (MSI). The model results revealed poor to moderate performance in predicting the proxies based on selected model evaluation criteria, raising the possibility of more data and relevant variables being needed to improve model performance. Therefore, this research presents a framework for an ML approach towards accounting for the wellbeing of technicians in sailing decisions once the highlighted limitations can be addressed.

Comparison of Transfer Function Models to Represent the Correlation Between Vehicle Lateral Acceleration and Head Tilting Angle in Motion Sickness

Motion Sickness (MS) is described as an unpleasant feeling caused by a forceful movement; hence vehicle movement impacts the severity of MS. While negotiating a curve, drivers and passenger tilt their heads differently, affecting their motion sickness incidence (MSI), which is the severity of MS. MS is a negative feeling, that affects occupant’s comfort, and to further understand the correlation between occupants' behavior and vehicle movement in MS and then represent it using mathematical models, it was proven that MSI could be predicted through mathematical models. However, there is an indefinite value between values between occupant’s behavior and vehicle movement. Based on that it is vital to express it the correlation mathematically. An experiment adopted from a prior study was utilized to get the data and develope the mathematical models with different proportions to represent the correlation between vehicle movement and occupant behavior in motion sickness in transfer function equations using system identification (SI), by utilising black-box feature to use the experimental data as input and output to allow SI to predict the transfer function models. The aim of this study is to investigate MS factors in relation to the vehicle movement and occupant’s behavior, to develop multiple transfer function models, to analyze and compare them. The results were obtained in the three different transfer function orders, second, third and fourth order functions for each proportion used for both the driver and passenger, the driver models’ results were in between 64.68%-67.87%, and the passenger results were in between 63.75%-67.93%, after the comparison the highest fits for each order were obtained. The highest fits amongst driver models were 67.87% (4th Order), 66.78% (3rd Order) and 65.17% (2nd Order) and 67.93% (4th Order), 66.3% (3rd Order) and 64.82% (2nd Order) amongst the passenger models. Those fits were then validated via Simulink with unseen data that was not used in identification process, and lastly the models Root Mean Square Error (RMSE) was obtained for all of them to determine their efficiency.

Dynamic Hull Vane—A Solution for Active Pitch Motion Reduction and Resistance Reduction of Ships

_ The Dynamic Hull Vane® is an actively controlled version of the Hull Vane®, a patented energy-saving and seakeeping device which consists of a submerged wing mounted on the aft ship. The Hull Vane is positioned in the upward flow aft of the ship, to develop forward thrust and reduce the stern wave. Naiad Dynamics US Inc, is a supplier of ride control systems and has worked with Hull Vane BV to develop the Dynamic Hull Vane®. By enabling the Hull Vane® to rotate, it can produce variable lift forces which when suitably controlled can reduce the pitching motions of a vessel in a seaway. This paper describes some of the research carried out on the AMECRC series 13, a generic fast displacement hull. Introduction Among other characteristics, two main performance parameters of a ship are fuel consumption and ship motions. Besides a well-designed hull, several appendages can be used to increase the performance. One of this is the Hull Vane. The Hull Vane is a fixed hydrofoil behind the transom of the ship. The Hull Vane has the potential to create large lift forces on the aft ship, thereby changing the resistance and the dynamic position of the vessel (Uithof et al. 2014). Ship motion reduction has long been a topic of research, and this has led to a number of solutions, which are widely applied. Most of the study work and products have been related to the rolling motions of ships, and there are indeed various effective solutions available, such as fin stabilizers, gyrostabilizers, interceptors, trim tabs, and antiroll tanks. The pitching motion of ships has been studied less, and while there are systems on the market to actively dampen the pitching motions of fast (planing) vessels, it has always been a challenge to dampen the pitch and heave motions of displacement ships, due to their inertia and limited speed. The pitch and heave motions are the prime source of vertical accelerations on board and these in turn are one of the main contributors in the Motion Sickness Incidence (MSI). Passive systems to reduce pitch motions exist, such as bow foils, which are preferably retractable to avoid their resistance penalty in calm water. There are two passive systems which dampen pitching motions while not adding calm-water resistance on specific ship types, because they reduce the wavemaking resistance of the ship: the bulbous bow and Hull Vane®. The pitch dampening effect of the passive Hull Vane has been demonstrated on naval vessels in computational fluid dynamics (CFD) (Bouckaert 2016) and in model tests (Ferré 2019).

Motion Sickness Prediction in Self-Driving Cars Using the 6DOF-SVC Model

Drivers who assign the driving task to a self-driving car switch to a passive role to work or enjoy leisure time like a traditional passenger. Consequently, the risk of developing motion sickness (MS) symptoms increases significantly. Adapting one’s own driving behavior, e.g. by choosing an alternative route or decreasing the velocity, offers future intelligent vehicles a way to independently prevent MS. Accurate predictions help to improve journey’s planning of the vehicle and make correct decisions so as to minimize disruption to the traffic flow. In the present study our contribution is as follow: We conduct two studies by focusing on real-world driving under self-driving conditions and induced MS symptoms in passengers. We simulated driving parameters of the conducted studies to extract simulated driving dynamics and contrasted them with recorded driving dynamics. A well-known model of MS, namely the six-degrees-of-freedom subjective vertical conflict model (6DOF-SVC model) was utilized to predict motion sickness incidence (MSI) for both studies. In order to do so, we implemented a customized Human-Vehicle-Model to map the car’s dynamics to the head, which is crucial to apply the 6DOF-SVC model. We evaluated different Human-Vehicle-Model conditions and optimized the parameters of the 6DOF-SVC model to increase prediction accuracy in the case of our experiments. Note that our modeling approach enabled capture effects of missing visual anticipation and cognitive distraction that we present in our experiment. It is concluded that the 6DOF-SVC model is applicable in realistic driving scenarios as the ones used in our study.

Influence of an active T-foil on motions and passenger comfort of a wave-piercing catamaran based on sea trials in oblique seas

In this paper the influence of a Ride-Control System (RCS) on the Response Amplitude Operator (RAO) of a full-scale high-speed catamaran was investigated using sea trials data. A T-foil and stern tabs were installed on a Wave-Piercing Catamaran (Incat Tasmania Hull 061) to improve ship motions and passenger comfort. More than 40 total effective hours of sea trials were conducted by the US Navy in 2004, encountering sea states 4–5 in the Atlantic Ocean near the United Kingdom. The reduction in Motion Sickness Incidence (MSI) was estimated in order to examine the effectiveness of the RCS in improving passenger comfort. By comparing the case of active RCS (T-foil plus stern tabs) with the case of active stern tabs only, it was found that the T-foil plays a vital role in the passenger comfort enhancement. Based on ISO recommended MSI calculation of a 2-h seaway, the percentage reduction in MSI was estimated, and hence the effectiveness of the T-foil deployment, along with the influence of speeds, headings, location on board and encountered wave height were analysed. A notable improvement in passenger comfort was observed in the real world bow quartering sea by deploying the RCS. An MSI reduction of 21% in high speeds (30–35 knots, [Formula: see text] 0.6) was observed, which was almost twice the MSI reduction (11%) in low speeds (15–20 knots, [Formula: see text] 0.3). However, in terms of MSI percentage reduction, the ability of T-foil in vessel motion control in oblique seas was found to be limited compared to the results in head seas.

Analysis of Seakeeping And Motion Sickness Incidence (MSI) Prediction Of The Ship's Bow When Sailing In Cilacap Sea

The waves are quite large, and the ship's movement continues to be a barrier tossed about or up and down on the high seas. It can result in symptoms of illness or an uncomfortable atmosphere for passengers on board. This symptom is often referred to as seasickness or motion sickness. The main cause of seasickness is the absence of similarity of excitability or conformity between the stimulus, eye and ear labyrinth the human brain receives. Usually, people who get seasick are on closed decks because their eyes cannot see any movement. At the same time, the ear labyrinth responds to the ship's movement so that there is a conflict between the stimuli received by the eyes and the ear labyrinth, which is responsible for body balance, causing nausea. In severe cases, passengers or crew must be taken to the hospital. Modelling MSI on Finite Element Method Software, it can be seen that passengers experience ship sickness or, in this case, experience MSI at what time on a cruise on the Cilacap sea lane processed to determine the condition of the ship's MSI to passengers by the acquisition of 6 degrees of freedom where various components that affect such as wind, the main current is a wave it occurs 6 degrees of freedom, i.e. Surging is a translational movement along the X axis, Rolling is the movement of the ship around the X axis, Swaying is the translational movement of the ship that occurs when the ship moves along the Y axis, Pitching is the movement of the ship around the Y axis, Heaving is the movement of the ship along the Z axis. A ship with a speed of 12.5 knots sailing in the Cilacap sea with a wave height reaching an average wave of 2.5 meters, the MSI of the ship occurs, namely the effect of sea conditions on the movement of the ship indicating that the ship's response to the sea is at 90 degrees. In the opposite direction of the wave, MSI occurs in 20% of passengers after 2 hours on the vehicle deck at the bow point. At that time, the magnitude of the encounter frequency was 2.137 Hz.

Analysis of Seakeeping And Motion Sickness Incidence (MSI) Prediction Of The Ship's Bow When Sailing In Cilacap Sea

The waves are quite large, and the ship's movement continues to be a barrier tossed about or up and down on the high seas. It can result in symptoms of illness or an uncomfortable atmosphere for passengers on board. This symptom is often referred to as seasickness or motion sickness. The main cause of seasickness is the absence of similarity of excitability or conformity between the stimulus, eye and ear labyrinth the human brain receives. Usually, people who get seasick are on closed decks because their eyes cannot see any movement. At the same time, the ear labyrinth responds to the ship's movement so that there is a conflict between the stimuli received by the eyes and the ear labyrinth, which is responsible for body balance, causing nausea. In severe cases, passengers or crew must be taken to the hospital. Modelling MSI on Finite Element Method Software, it can be seen that passengers experience ship sickness or, in this case, experience MSI at what time on a cruise on the Cilacap sea lane processed to determine the condition of the ship's MSI to passengers by the acquisition of 6 degrees of freedom where various components that affect such as wind, the main current is a wave it occurs 6 degrees of freedom, i.e. Surging is a translational movement along the X axis, Rolling is the movement of the ship around the X axis, Swaying is the translational movement of the ship that occurs when the ship moves along the Y axis, Pitching is the movement of the ship around the Y axis, Heaving is the movement of the ship along the Z axis. A ship with a speed of 12.5 knots sailing in the Cilacap sea with a wave height reaching an average wave of 2.5 meters, the MSI of the ship occurs, namely the effect of sea conditions on the movement of the ship indicating that the ship's response to the sea is at 90 degrees. In the opposite direction of the wave, MSI occurs in 20% of passengers after 2 hours on the vehicle deck at the bow point. At that time, the magnitude of the encounter frequency was 2.137 Hz.

NUMERICAL ANALYSIS SEAKEEPING AND MOTION SICKNESS INCIDENCE (MSI) ON HOSPITAL SHIPS BY ADDING FINS STABILIZER

The development in maritime technology to improve ship performance and operations are growing and diverse. One of the developments carried out is the addition of fin stabilizers to improve ship safety as support for comfort and ships. This research analyzes the effect of variations in the shape of the fin stabilizer on the seakeeping and Comfort Index for Hospital Ships using Maxsurf Modeler software. The parameters used in this research are fins stabilizer Gemini 30, Gemini 50, and modular NR 30. While the variation of ship speed 0, 14, and 18 knots. The direction of the arrival of waves 0, 45, 90, 135, and 180 degrees. Based on data analysis carried out on ship motion, the NR 30 type fin stabilizer is far superior to the others with a maximum value of 4.04- degree roll movement, 0.543- degree pitch movement, and 0.4116 heave acceleration movement. Type NR 30 also has the best comfort on the moderate Motion Sickness Incidence (MSI) Criteria.

Operation of T-Foils and Stern Tabs to Improve Passenger Comfort on High-Speed Ferries

_ High-speed ferries of around 100mlength cruising at around 40 knots can cause significant passenger discomfort in head waves. This is due to the frequencies of encountering waves, of maximum hull response to encountered waves and of maximum passenger discomfort all falling within a similar range. In this paper, the benefit obtained by fitting active T-foils and stern tabs to control heave and pitch in head waves is considered. Ship motion responses are computed by numerical integration in the time domain including unsteady control actions using a time domain, high-speed strip theory. This obviates the need to identify transfer functions, the computed time responses including nonlinear hull immersion terms. The largest passenger vertical accelerations occur at forward locations and are best controlled by a forward located T-foil acting in combination with active stern tabs. Various feedback control algorithms have been considered and it is found that pitch damping control gives the greatest improvement in passenger comfort at forward positions. Operation in adaptive and nonlinear modes so that the control deflections are maximized under all conditions give the greatest benefit and can reduce passenger motion sickness incidence (MSI) by up to 25% in a 3-mhead sea on the basis of International Organization for Standardization (ISO) recommendations for calculation of MSI for a 90-minute seaway passage. Introduction When the first high-speed, lightweight catamaran car ferries were developed, it quickly became apparent that motion control systems were desirable to improve passenger comfort. This was a direct consequence of the high operating Froude numbers (based on waterline length) of up to 0.75, which gave rise to heave and pitch motions in excess of the wave height and wave slope. It was also a consequence of the period of encountered waves at high speed that becomes close to the period at which passengers would experience significant motion discomfort, approximately 5-6 seconds. As a consequence, active motion controls were introduced and have been fitted to most vessels operating on routes where significant wave heights might reach or exceed approximately 3m.

A method for the probabilistic assessment of the on-board comfort on a passenger vessel route

The intense maritime traffic of modern days requires that a considerable attention be paid toward the comfort of ships not only as design criteria, but also as a means of assessing the quality of navigation in service conditions. Certain passenger routes and ship dimensions are more vulnerable than others to rough weather and the current climate changes require adaptation of design and navigation warning strategies.The main aim of the paper is to describe a method to derive a probabilistic representation of the comfort of passengers and crew on a selected route. AIS data is used to identify and characterise the chosen route. The seakeeping properties of the principal ships are evaluated employing a strip theory code. Detailed wave hindcast data is then employed to build state-of-the-art wave scatter diagrams along the route which allow the calculation of the ship responses for each sea state and the associated probability. The Motion Sickness Incidence is finally used as a comparative measure of the overall on-board comfort experienced on a variety of passenger vessels.

Computational Model of Motion Sickness Describing the Effects of Learning Exogenous Motion Dynamics.

The existing computational models used to estimate motion sickness are incapable of describing the fact that the predictability of motion patterns affects motion sickness. Therefore, the present study proposes a computational model to describe the effect of the predictability of dynamics or the pattern of motion stimuli on motion sickness. In the proposed model, a submodel – in which a recursive Gaussian process regression is used to represent human features of online learning and future prediction of motion dynamics – is combined with a conventional model of motion sickness based on an observer theory. A simulation experiment was conducted in which the proposed model predicted motion sickness caused by a 900 s horizontal movement. The movement was composed of a 9 m repetitive back-and-forth movement pattern with a pause. Regarding the motion condition, the direction and timing of the motion were varied as follows: (a) Predictable motion (M_P): the direction of the motion and duration of the pause were set to 8 s; (b) Motion with unpredicted direction (M_dU): the pause duration was fixed as in (M_P), but the motion direction was randomly determined; (c) Motion with unpredicted timing (M_tU): the motion direction was fixed as in (M_P), but the pause duration was randomly selected from 4 to 12 s. The results obtained using the proposed model demonstrated that the predicted motion sickness incidence for (M_P) was smaller than those for (M_dU) and (M_tU) and no considerable difference was found between M_dU and M_tU. This tendency agrees with the sickness patterns observed in a previous experimental study in which the human participants were subject to motion conditions similar to those used in our simulations. Moreover, no significant differences were found in the predicted motion sickness incidences at different conditions when the conventional model was used.

Machine Learning and Cloud Computing for Remote Monitoring of Wave Piercing Catamarans: A Case Study using MATLAB on Amazon Web Services

Wave load cycles, wet-deck slamming events, accelerations and motion comfort are important considerations for high- speed catamarans operating in moderate to large waves. This paper provides an overview of data analytics methods and cloud computing resources for remotely monitoring motions and structural responses of a 111 m high-speed catamaran. To satisfy the data processing requirements, MATLAB Reference Architectures on Amazon Web Services (AWS) were used. Such combination enabled fast parallel computing and advanced feature engineering in a time-efficient manner. A MATLAB Production Server on AWS has been set up for near real-time analytics and execution of functions developed according to the class guidelines. A case study using Long Short-Term Memory (LSTM) networks for ship speed and Motion Sickness Incidence (MSI) is provided and discussed. Such data architecture provides a flexible and scalable solution, leading to deeper insights through big data processing and machine learning, which supports hull monitoring functions as a service.

Novel Motion Sickness Minimization Control via Fuzzy-PID Controller for Autonomous Vehicle

In terms of vehicle dynamics, motion sickness (MS) occurs because of the large lateral acceleration produced by inappropriate wheel turning. In terms of passenger behavior, subjects experience MS because they normally tilt their heads towards the direction of lateral acceleration. Relating these viewpoints, the increment of MS originates from the large lateral acceleration produced by the inappropriate wheel’s turn, which then causes greater head movement with respect to the lateral acceleration direction. Therefore, this study proposes the utilization of fuzzy-proportional integral derivative (PID) controller for an MS minimization control structure, where the interaction of the lateral acceleration and head tilt concept is adopted to diminish the lateral acceleration. Here, the head movement is used as the controlled variable to compute the corrective wheel angle. The estimation of the head movement is carried out by an estimation model developed by the radial basis function neural network (RBFNN) method. An experiment involving a driving simulator was conducted, to verify the proposed control system’s performance in regard to the autonomous vehicle’s passengers. The results show that the averages of motion sickness incidence (MSI) index can be lowered by 3.95% for single lap and 11.49% for ten laps.

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

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.

세관 감시선의 선내 위치변화에 따른 멀미도 지수에 대한 연구

세관 감시선의 선내 위치변화에 따른 멀미도 지수에 대한 연구