Syllabus
Fundamentals of Classic AUTOSAR and Automotive Software Design
Basics of Automotive Electronics and ECUs: Introduction to Embedded Systems in Automobiles, Overview of the AUTOSAR Consortium and Standardization, AUTOSAR Classic Platform: Architecture Layers (MCAL, BSW, RTE, SWC), Communication Protocols: CAN, LIN, Ethernet – Fundamentals and Uses, AUTOSAR Development Workflow and System Configuration (ARXML), Introduction to AUTOSAR Tools: Vector and EB tresos, Model-Based Design with Simulink and Code Generation Basics, Software Component Design and Port Mapping in Simulink, Case Study:
Fundamentals of Adaptive AUTOSAR and High-Performance Vehicle Computing
Differences between Classic and Adaptive AUTOSAR, Need for Adaptive AUTOSAR in Autonomous and Connected Vehicles, Introduction to POSIX-based Operating Systems (Linux, QNX), Overview of Adaptive AUTOSAR Execution Environment, Service-Oriented Architecture Basics: SOME/IP and DDS Fundamentals, Application Manifest, Service Discovery, Execution Management, Introduction to Cybersecurity and Functional Safety in Adaptive Platforms, Tools for Adaptive AUTOSAR: AUTOSAR Builder, Eclipse IDE, Over-the-Air (OTA) Update Concepts and Diagnostics, Case Study:
Fundamentals of ADAS and AI Applications in Vehicle Systems
Overview of ADAS: Objectives, Passive and Active Safety Systems, Basic ADAS Features: Cruise Control, Lane Departure, Blind Spot Detection, Sensors in ADAS: Working Principles of Radar, Camera, LiDAR, Ultrasonic, Introduction to AI in ADAS: Object Detection using CNNs, Lane Detection using Image Processing, Pedestrian Detection using Pre-trained Models, Reinforcement Learning Basics for Path Planning, Driver Monitoring Systems: Camera-based Eye Tracking and Drowsiness Detection, Simulation Tools: MATLAB ADAS Toolbox, Python OpenCV, Case Study.