Browsing by Author "Htike, Zaw"
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Item Open Access Control for Motion Sickness Minimisation in Autonomous Vehicles(Cranfield University, 2018-10-22 10:13) Htike, ZawPoster presented at the Cranfield Doctoral Network Annual Event 2018. Autonomous vehicles or self-driving vehicles are expected to become a wide scale deployment for public use in the very near future. Recent study shown that there will be increase in frequency and severity of motion sickness due to engaging in non-driving tasks. This establishes motion sickness as being the elephant in the room and the increase in occurrence of motion sickness is predicting to be a limitation to the successful introduction of full vehicle automation. Motion sickness is a condition marked by symptoms of nausea dizziness, and other physical discomfort. The accepted cause of motion sickness is being the sensory conflict between inputs from the visual, vestibular and somatosensory systems of human body. Factors that might increase or decrease the severity of sickness symptoms includes ages, genders, alcohols, drugs, motion environments, other environmental and psychological aspect. Nevertheless, motion sickness in road vehicles is most closely related to low-frequency fore-and-aft, lateral, yaw acceleration. The range of these frequencies stated in the Standards guideline (International Standard, British Standards and Military Standards) for human exposed to whole-body mechanical vibration and shock, are in the range between 0.1 to 0.5 Hz. Previous experiments studies also shown that passenger motion sickness increases with increased exposure to lateral motion at low frequencies less than 0.5 Hz. This project aims to develop a control strategy that could minimise motion sickness in autonomous vehicles. The first part of the project explores the empirical formulations outlined in the Standards to evaluate motion sickness as a form of predicted illness rating or motion sickness incidence. A simple optimisation algorithm is developed to investigate the effectiveness of reducing motion sickness based from such formulations. The second part of the project looks at the sensory conflict theory for estimating motion sickness by adopting the existing 6-DOF subjective vertical conflict model. This model would later incorporate with vehicle model, and an optimal control strategy would be implemented to minimise motion sickness.Item Open Access Fundamentals of motion planning for mitigating motion sickness in automated vehicles(IEEE, 2021-12-28) Htike, Zaw; Papaioannou, Georgios; Siampis, Efstathios; Velenis, Efstathios; Longo, StefanoThis paper investigates the fundamentals of motion planning for minimizing motion sickness in transportation systems of higher automation levels. The optimum velocity profile is sought for a predefined road path from a specific starting point to a final one within specific and given boundaries and constraints in order to minimize the motion sickness and the journey time. An empirical approach based on British standard is used to evaluatemotion sickness. The tradeo between minimizing motion sickness and journey time is investigated through multi-objective optimization by altering the weighting factors. The correlation between sickness and journey time is represented as a Pareto front because of their conflicting relation. The compromise between the two components is quantified along the curve, while the severity of the sickness is determined using frequency analysis. In addition, three case studies are developed to investigate the eect of driving style, vehicle speed, and road width, which can be considered among the main factors aecting motion sickness. According to the results, the driving style has higher impact on both motion sickness and journey time compared to the vehicle speed and the road width. The benefit of higher vehicle speed gives shorter journey time while maintaining relatively lower illness rating compared with lower vehicle speed. The eect of the road width is negligible on both sickness and journey time when travelling on a longer road.The results pave the path for the development of vehicular technologies to implement for real-world driving from the outcomes of this paper.Item Open Access Multi-criteria evaluation for sorting motion planner alternatives(MDPI, 2022-07-11) Papaioannou, Georgios; Htike, Zaw; Lin, Chenhui; Siampis, Efstathios; Longo, Stefano; Velenis, EfstathiosAutomated vehicles are expected to push towards the evolution of the mobility environment in the near future by increasing vehicle stability and decreasing commute time and vehicle fuel consumption. One of the main limitations they face is motion sickness (MS), which can put their wide impact at risk, as well as their acceptance by the public. In this direction, this paper presents the application of motion planning in order to minimise motion sickness in automated vehicles. Thus, an optimal control problem is formulated through which we seek the optimum velocity profile for a predefined road path for multiple fixed journey time (JT) solutions. In this way, a Pareto Front will be generated for the conflicting objectives of MS and JT. Despite the importance of optimising both of these, the optimum velocity profile should be selected after taking into consideration additional objectives. Therefore, as the optimal control is focused on the MS minimisation, a sorting algorithm is applied to seek the optimum solution among the pareto alternatives of the fixed time solutions. The aim is that this solution will correspond to the best velocity profile that also ensures the optimum compromise between motion comfort, safety and driving behaviour, energy efficiency, journey time and riding confidence.