Papers
4
Total Citations
22
H-Index
3
About
Duc An Pham is a researcher whose work bridges the critical gap between virtual simulation and real-world motion, with a primary focus on motion cueing algorithms (MCAs) for driving simulators. His most impactful contribution, the 2015 paper "Optimal Motion Cueing Algorithm Selection and Parameter Tuning for Sickness-Free Robocoaster Ride Simulations" (11 citations), tackles the fundamental challenge of mapping vehicle motion into a simulator’s limited workspace while preventing motion sickness. This work is complemented by a 2017 study (6 citations) that provides a comprehensive comparison and auto-tuning of state-of-the-art MCAs, validated through subjective evaluation on a KUKA robocoaster—a platform used for both training and entertainment. Beyond simulation, Pham has advanced sensor calibration, notably developing an elliptical fitting algorithm for magnetometer validation (2023, 2 citations) and a tilt angle determination method using the MPU6050 inertial measurement unit (2022, 3 citations). His research directly improves the fidelity and comfort of driver training systems and autonomous vehicle testing, making him a key contributor to the practical implementation of realistic, sickness-free motion simulation.
Research Focus
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Top Papers
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