Investigation of vibration's effect on driver in optimal motion cueing algorithm

Area of Science:

• Human-computer interaction
• Automotive engineering
• Control systems

Background:

• Driving simulators often suffer from sensation errors, leading to unrealistic motion cues.
• Existing motion cueing research frequently overlooks the impact of vibrations on driver health, comfort, perception, and motion sickness.

Purpose of the Study:

• To develop a novel optimal motion cueing algorithm that minimizes sensation error by integrating driver body and perception models.
• To enhance the realism of motion cues in driving simulators.

Main Methods:

• Utilized a driver's body model to account for vibration effects on the driver.
• Employed H∞ control, replacing the linear quadratic regulator, for optimizing the cost function of sensation error.
• Combined driver body and perception models for a comprehensive approach to motion cueing.

Main Results:

• Achieved a significant decrease in sensation error: 70% for longitudinal acceleration, 61% for lateral acceleration, and 84% for yaw velocity.
• Demonstrated improved realism through increased coefficient of cross-correlation by 3% for longitudinal acceleration and 1% for lateral acceleration.
• Validated the effectiveness of the proposed optimal motion cueing algorithm compared to state-of-the-art methods.

Conclusions:

• The proposed optimal motion cueing algorithm effectively reduces sensation error and enhances motion cue realism in driving simulators.
• Integrating driver body and perception models is crucial for improving the fidelity of driving simulation.
• The use of H∞ control offers a robust method for optimizing motion cueing algorithms.