Nguyen Nguyen Trung

About

Nguyen Nguyen Trung is a rising researcher in autonomous vehicle control and intelligent transportation systems, with a focus on integrating deep learning into real-world driving tasks. His most-cited work, "An Improved Lane-Keeping Controller for Autonomous Vehicles Leveraging an Integrated CNN-LSTM Approach" (2023), addresses the complexity of traditional lane-keeping algorithms by training artificial neural networks on front-facing camera data to generate steering commands. This CNN-LSTM framework captures both spatial features and temporal driving dynamics, offering a more adaptive and robust solution for lane-keeping under varied traffic conditions. With 3 citations since its publication, the paper signals growing interest in his approach to end-to-end learning for vehicle control. Trung’s research bridges computer vision, recurrent neural networks, and control theory, aiming to reduce reliance on handcrafted rules in autonomous navigation. His work contributes to the broader goal of safer, more efficient self-driving systems, and positions him as an emerging voice in the integration of deep learning with vehicular automation.

Research Focus

Key Achievements

Top Papers

1. 1
   An Improved Lane-Keeping Controller for Autonomous Vehicles Leveraging an Integrated CNN-LSTM Approach

   3 citations · 2023

Key Collaborators

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