Course Details

Course Overview

Learning Outcomes

• Explain the fundamental components of Smart Driving Systems, including sensors, communication protocols, and decision-making units.
• Describe how GPS, LiDAR, radar, and computer vision contribute to environment perception in autonomous vehicles.
• Analyze real-time data from vehicle sensors and understand how it influences driving behavior.
• Compare different levels of driving automation as defined by the SAE (Levels 0–5).
• Evaluate safety protocols, cybersecurity risks, and legal challenges in autonomous driving systems.
• Design a basic system architecture for a smart driving prototype or simulation.

Course Requirements

• A basic understanding of programming concepts (preferably Python or C++)
• Familiarity with electronics and sensor systems (e.g., Arduino, Raspberry Pi)
• Introductory knowledge of physics and mathematics, especially linear algebra and kinematics
• Comfort with using computing platforms (PC/Mac/Linux) for simulations
• Basic experience or interest in automotive systems, robotics, or IoT (preferred but not mandatory)
• A stable internet connection to access video lectures, simulation tools, and interactive content

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