Nguyen Duc Thang

ADAS functions improvement and development

- Autonomous public/share transport systems perception and modelling - Autonomous vehicle level 4: system analysis, development and simulation in Matlab/Simulink and SCANeR - Focus on Driving strategy with the integration of risk assesment and situation anticipation which mimics the human reasoning. The driving algorithm has the capacity of: + Taking several simultanneous decisions for the longitudinal and the lateral control + Taking into account the passengers' comfort + Taking into account the limites of the vehicle such as brake capacity and lateral stability + Cancelling external disturbances such road slope and wind + Cancelling the parameters imperfections of the vehicle such as tire pressure or vehicle load + Respecting road signalisation such as traffic light, speed limits ... + Providing natural, seamless and precise longitudinal control so that the vehicle can perform with ease tasks such as precise stop at traffic light or at stop line, obtacle avoidence and lane change + Driving without a high precise GPS signal + Working together to form a transport system thank to the three-level trajectory management - Method of management of a fleet of autonomous vehicles via the three-level trajectory design - Methods of verification and validation for ADAS systems / Autonomous vehicle from its driving behavior: + Definition a set of safety index + Definition of dangerous threshold with the consideration of situation such as cut-in or highway insertion + Index calculation in real time and providing the validation report - Digital twin for industry - Matlab, Simulink, System Composer, Capella, Python, SCANeR, Autoware, Carla simulator, Linux, Windows

- ADAS: Steer-by-Wire, ACC, TJC, Platooning: vehicule modelling; system analysis and control law development - Autonomous vehicle level 4: model-based system engineering (MBSE) - Innovation: fuel cell control system for aeronautic and automobile industry - Model Based Design, ISO26262, DO178C - Matlab/Simulink, SCANeR, RTMaps, ROS, Docker, CARLA, C++, Python

- Modelling and control law design - Adaptive control, Neural networks, Fuzzy logic, PID - Matlab/Simulink, Real-time simulation, DSpase

Autonomous vehicle prototype: - Autonomous functional concept - System supervision and control - Camera, radar, electric vehicle - C++, TCP/IP, CANalyser

Modelling and control law design with fuzzy logic and neural networks

- Neural networks learning and control of nonlinear systems - System modelling, advanced control method, simulation, computing - Malab/Simulink