Now showing 1 - 6 of 6
  • Publication
    Development of Driving Simulation Experiment Protocol for the Study of Drivers’ Emotions by using EEG Signal
    The Brain-Computer Interface (BCI) is a field of research that studies the EEG signal in order to elevate our understanding of the human brain. The applications of BCI are not limited to the study of the brain wave but also include its applications. The studies of human emotions specific to the vehicle driver are limited and not vastly explored. The EEG signal is used in this study to classify the emotions of drivers. This research aims to study the emotion classifications (surprise, relax/neutral, focus, fear, and nervousness) while driving the simulated vehicle by analyse the EEG signals. The experiments were conducted in 2 conditions, autonomous and manual drive in the simulated environment. In autonomous driving, vehicle control is disabled. While in manual drive, the subjects are able to control the steering angle, acceleration, and brake pedal. During the experiments, the EEG data of the subjects is recorded and then analyzed.
      1  32
  • Publication
    Design of Experiment (DOE) for the Investigation of Human Emotions while Driving in a Virtual Environment through Brain Signal (EEG)
    The transition from the conventional vehicle to the autonomous vehicle is going to take place but, the acceptance of users to the autonomous vehicle still lacking. The past research more focusses on the driver attention, drowsiness, fatigue or the alertness of the driver. This research aims to study the drivers' emotions/reactions during the autonomous and manual drive in the simulated environment. The environment for the manual and autonomous drive is developed by using simulator software, Unity. This paper focus only on the experimental setup for the human emotions' detection using EEG signal during the manual and autonomous drive. The Emotiv Epoc+ use for the EEG signal acquisition. The simulated environments are displayed through a Head Mount Display (HMD). The analysis of the EEG signal which includes the pre-processing, feature extraction, and classification will be discussed in future works.
      1  25
  • Publication
    Suppresion of sommerfeld effect in power transmission system employing cardan shaft through phase angle arragement
    ( 2024-07-01)
    Omar M.H.
    ;
    ; ;
    Rani M.N.A.
    In a power transmission system with a cardan shaft, the Sommerfeld effect occurs, which is characterized by speed capture and release at the resonance range. Suppression of the Sommerfeld effect is critical for smooth and reliable operation. This study aims to suppress the Sommerfeld effect in a transmission system by compensating the phase angle between the two universal joints installed in the cardan shaft. The differential equations of motion representing the dynamics of the system are derived using the Lagrange equation. The responses are simulated numerically using the Runge–Kutta algorithm for scenarios with constant and gradually varying input torque. To suppress the Sommerfeld effect, the phase angle is set to 25%, 50%, 75% and 100% of the maximum twist angle observed in the subcritical speed range of the in-phase configuration. With the phase angle of 25%, the Sommerfeld effect is damped, where the output speed only deviates by 5% from the estimated value for both input torque scenarios. It is shown how the change of the phase angle attenuates the Sommerfeld effect and the system vibrations, which should be considered in the development and practical implementation.
      22  2
  • Publication
    Classification of human emotions using EEG Signals in a simulated environment
    The Brain-Computer Interface (BCI) is a computer-based system that acquires and analyses brain signals. The analysis of brain signals shows the physiological change that happens to the drivers. The physiological changes detected by the BCI system may not be visible to the naked eye. By using the BCI, it increases the diagnostic capability to detect the drivers' emotions. The negative drivers' emotions may cause bad decision making during driving the vehicle. The proposed method was developed to study the related emotions that occur during driving in the simulation environment. The experiments were designed in two situations, which are manual and autonomous drive. In the manual mode, the subjects will control the steering wheel and acceleration of the simulated vehicle. While in autonomous mode, all controls are disable and the subjects will experience the automatic simulation drive. The EEG data was recorded during the simulated drive (manual and autonomous). The EEG data from the subjects were then categorised into five emotions classifications.
      4  3
  • Publication
    Classification of Human Emotions Using EEG Signals in a Simulated Environment
    The Brain-Computer Interface (BCI) is a computer-based system that acquires and analyses brain signals. The analysis of brain signals shows the physiological change that happens to the drivers. The physiological changes detected by the BCI system may not be visible to the naked eye. By using the BCI, it increases the diagnostic capability to detect the drivers' emotions. The negative drivers' emotions may cause bad decision making during driving the vehicle. The proposed method was developed to study the related emotions that occur during driving in the simulation environment. The experiments were designed in two situations, which are manual and autonomous drive. In the manual mode, the subjects will control the steering wheel and acceleration of the simulated vehicle. While in autonomous mode, all controls are disable and the subjects will experience the automatic simulation drive. The EEG data was recorded during the simulated drive (manual and autonomous). The EEG data from the subjects were then categorised into five emotions classifications.
      2  26
  • Publication
    NUMERICAL STUDY ON EFFECT OF PHASE ANGLE ON TORSIONAL AND LATERAL VIBRATIONS IN POWER TRANSMISSION SYSTEM EMPLOYING CARDAN SHAFT
    A power transmission system driven by a Cardan shaft may experience severe vibration due to fluctuating rotational speed and moments transferred to the final drives, determined by the level of angular misalignment and phasing of the joint yokes. This study investigates the potential of an out-of-phase position displaced by a phase angle in attenuating vibrations. The governing equations representing the dynamics of the system are derived. The torsional and lateral vibration responses are numerically calculated over a range of input rotational speeds. When attenuating the vibration, the phase angle is set equal to the maximum twist that occurs during the in-phase position. Relative attenuation is used to investigate the phase angle effects. The effectiveness is studied for different levels of static angular misalignment. For the considered system, the results showed that for static angular misalignment greater than 20 degrees, the proposed phase angle arrangement could attenuate torsional vibration by more than 10 percent and significantly attenuate the lateral vibration.
      1  24