Intelligent Machines and Connected Vehicles

Undergraduate

This course focuses on the intelligent vehicles where both AI algorithms and their system aspects are studied. The topics covered include key concepts of the perception-planning-control pipeline for autonomous driving; key concepts of machine learning (ML), especially reinforcement learning (RL), and deep reinforcement learning (DRL); hands-on exercises with one of the popular open-source ML frameworks such as Tensorflow or PyTorch. Training, deployment, and validation of ML-based autonomous driving algorithms in a simulation environment. This course is one of the four specialization courses introduced in the fourth year and is specific to the area of specialization of Autonomous Vehicles. (Prerequisite: ELEC-3040 and GENG 4500) (This is an experiential learning course.)