Papers
1
Total Citations
3
H-Index
1
About
Dr. Zengxi Wang is a researcher advancing the field of autonomous vehicle control, with a particular focus on the development of intelligent driving robots. His key research areas encompass model predictive control (MPC) algorithms, automated driving systems, and the integration of robotics for Advanced Driver-Assistance Systems (ADAS) testing. Dr. Wang’s major contribution lies in his work on improving the robustness and precision of automatic driving robots, specifically through an enhanced MPC approach that addresses the complex constraints and uncertainties inherent in high-speed horizontal and vertical vehicle control. His most-cited paper, "Research on control algorithm of a automatic driving robot based on improved model predictive control" (2021), has garnered 3 citations, establishing a foundational reference for researchers tackling real-world control challenges. This work is notable for its practical application in replacing human drivers during rigorous vehicle testing, thereby increasing safety and repeatability. Dr. Wang’s efforts are instrumental in bridging the gap between theoretical control strategies and their deployment in demanding, real-world autonomous driving scenarios.
Research Focus
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Top Papers
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