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020			_aTHE0010179 (Local) _qHardback
040			_aUMPSA _beng _cUMPSA _erda
090			_aFTKPM .A35 2025 r Thesis
100	1		_aNurul Afiqah Binti Zainal, _eauthor.
245	1	0	_aIntegrated vehicle-human biodynamic models under various road excitation for autonomous vehicles comfort assessment / _cNurul Afiqah Binti Zainal
264		1	_aKuantan, Pahang : _bUMPSA , _c2025
264		4	_c© 2025
300			_axv, 130 pages : _billustrations ; _c30 cm. + _e1 CD-ROM
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
347			_2rda _atext file _bPDF
500			_aFaculty of Manufacturing & Mechatronics Engineering Technology
502			_aThesis (Doctor of Philosophy) -- Universiti Malaysia Pahang – 2025
504			_aIncludes bibliographical references
520	3		_aVehicle development is rapidly progressing as increasing user demand drives manufacturers to produce more technologically advanced, comfortable, fuel-efficient, and safer vehicles. With the evolution of vehicle design now moving intensely towards autonomous vehicles (AVs), development standards and expectations are rising in parallel. In AVs development, it consists of three basic modules which are perception, planning and control. Motion comfort lies in the planning stages whereby improvising the motion comfort will directly enhance the planning stage of the Avs. By enhancing the motion comfort, it will eventually improve the Avs control to behave as more human-centric behaviour. This is particularly important as there is no physical driver—the system entirely governs vehicle movement while the human remains a passenger. A significant challenge arises when the AV encounters tight manoeuvres, where the control algorithm may fail to cope with sudden curvature changes due to a lack of dynamic path curvature data. This may reduce the ride comfort and increased risk of motion sickness, due to the aggressive behaviour of AV's maneuvers that are not being controlled by human. This study addresses that gap by investigating the coupling effect between a mathematical vehicle model and a human biodynamic model to analyse their dynamic response in terms of comfort performance. Several vehicle models (quarter-car, half-car, two in-wheel electric vehicle and SCAV) and human biodynamic models (8 DOF and 12 DOF, including pregnant passenger representations) are modelled and integrated to simulate how vibrations from different road trajectories and speeds affect human body responses, particularly vertical accelerations at the head and brain. These vehicle vibrations are used as input excitations to the biodynamic model, enabling the assessment of vibration transmission and potential discomfort. The modelling approach is built on the integration of established mathematical formulations for both vehicle dynamics and human biodynamics. The resulting integrated vehicle-human model is validated based on ISO 2631-1 standards for whole-body vibration and Motion Sickness Incidence (MSI) calculations. MSI is used as a comfort index based on vertical acceleration of the head. An MSI value exceeding 20% indicates that the experience becomes "uncomfortable" due to road irregularities or inconsistent accelerations. The key finding of this research is the development of a comprehensive framework by assessing integrated vehicle-human model performance, categorized by model characteristics and responses to various road conditions. Quantitatively, results show that model configurations and road excitations significantly influence head acceleration and MSI levels. Then, the study offers comparative insights into the strengths and limitations of various integrated vehicle-human model configurations in predicting human motion sickness based on the road conditions applied, qualitatively. In conclusion, this research highlights the importance human comfort in AV development by incorporating it into AV modelling and simulation frameworks. The validated integrated vehicle-human model serves as a valuable tool for predicting motion sickness and ride comfort, hence, provide a valuable insight that can alert future AV design, enhance control algorithms, and support the development of regulatory comfort assessment standards. Ultimately, this work contributes to the advancement of more human-centric AV systems and establishes a foundation for future experimental validation and integration into real-world applications.
610	2	0	_aFaculty of Manufacturing & Mechatronics Engineering Technology _xDissertations
650		0	_aUniversities and colleges _xDissertations
650		0	_aTheses _xDissertations
942			_2lcc _cTHESIS
999			_c103798 _d103804