Dual-layer GRU-LQR framework for end-to-end learning of trajectory tracking control in autonomous vehicles
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
Published online on February 02, 2026
Abstract
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Ahead of Print.
End-to-end learning with stability control for autonomous vehicles in maneuvering environments remains a significant challenge. To solve this problem, a framework of dual-layer gated recurrent unit (GRU) and linear quadratic regulator (LQR) is proposed to ...
End-to-end learning with stability control for autonomous vehicles in maneuvering environments remains a significant challenge. To solve this problem, a framework of dual-layer gated recurrent unit (GRU) and linear quadratic regulator (LQR) is proposed to ...