Speaker Details

Speaker Company

Nelson Quintana

Over 25 years of experience in the semiconductor industry, focusing on real-time embedded systems. At Infineon, Nelson drives initiatives to accelerate innovation to address major challenges and opportunities in the next generation mobility space by collaborating with technology disruptors and leveraging Infineon’s leadership in automotive. Multi-disciplinary skillset including systems engineering, application engineering, product management, strategic marketing, and business development. B.S. in Electrical Engineering with a concentration in Digital Electronics from San Francisco State University, California


Trajectory tracking and Lane change for adaptive cruise control using neural network in autonomous driving systems

Some desired features for autonomous vehicles are ensuring that the car follows an expected route, steers to the adjacent lane when cars in front are slower and adjusts the velocity of the car to keep a safe distance. Model predictive control (MPC) methods are often used as they consider the non-linear dynamics of the car that degrade the overall performance. Neural networks (NN) are included to enhance the MPC and reduce the effects of the disturbances. The traditional and NN enhanced MPC can be implemented in the new AURIXTM TC4x microcontroller. A comparative study between the proposed method with the standard one is also discussed.