Software Defined Vehicle (SDV) Foundation

Hands-on Training Workshop

Venue : T-works
Date : To be announced
Duration : 2 Days
Registration : â‚ą10,000+ GST

Open to automotive system, software, embedded, and E/E architecture professionals from OEMs and Tier-1/Tier-2 suppliers who want to understand Software Defined Vehicle fundamentals.

Register

Core Learning Pillars

  • SDV Foundations & Architecture

    Evolution to SDVs, signal-oriented vs service-oriented architectures, SDV building blocks

  • Key SDV Technologies

    In-vehicle networks, AI/ML, cloud and edge computing in automotive systems

  • Software Architecture & Middleware

    SDV software stack, microservices, containerization, APIs, AUTOSAR (Classic & Adaptive)

  • Vehicle OS, HPC & Platforms

    POSIX, RTOS, QNX, Automotive Linux, Yocto basics, HPCs and hardware accelerators

  • Connectivity, OTA & Communication

    OTA architecture, Ethernet backbone, TSN, V2X, 5G, real-time communication

  • Security, Lifecycle & Future Trends

    SDV cybersecurity, secure boot, IDS, DevOps, CI/CD, autonomous software basics, future innovations

âś” Comprehensive introduction to Software Defined Vehicle (SDV) architecture

âś” Clear comparison between traditional vehicle and SDV paradigms

âś” Exposure to HPCs, Automotive Linux, POSIX, AUTOSAR, and middleware

âś” Coverage of OTA, TSN, V2X, cloud-edge computing, and connectivity

âś” Introduction to SDV cybersecurity and future technology trends

âś” Industry-aligned content mapped to real automotive project use cases

Key Highlights

âś” Understand core SDV concepts and architectures

âś” Differentiate traditional ECUs from SDV-based systems

âś” Interpret SDV software stacks and middleware choices

âś” Understand the role of HPCs, OS, and embedded Linux

âś” Apply SDV concepts to real automotive project scenarios

âś” Assess technical challenges and ToCs (Terms of Concern) in SDV programs

âś” Build readiness for advanced SDV, ADAS, and autonomous vehicle roles

Program Outcome

Program Details

    • Evolution of automotive electronics to SDVs

    • Differences between traditional and SDV architectures

    • Key Components of SDVs: Sensors, actuators, control units and communication

    • systems

    • Signal Oriented vs Service Oriented Architectures

    • In-vehicle networking protocols (CAN, LIN, FlexRay, Ethernet)

    • Cloud and Edge Computing for SDVs

    • Role of A1 and Machine Learning in SDVs

    • SDV software stack layers

    • Middleware and application layer software

    • Role of microservices and containerization

    • Use of service-oriented architectures (SOA) and APIs

    • Powertrain, ADAS (Advanced Driver Assistance Systems), and infotainment systems

    • Cybersecurity and over-the-air (OTA) updates

    • Data management and logging requirements

    • Analysing different HPCs in the market

    • Role of Hardware Accelerators in HPCs

    • Introduction about S32G274a HPC Gold box

    • Overview of Automotive Embedded Linux

    • Yocto build project- a basic Introduction

    • Overview of Vehicle OS - POSIX vs RTOS vs QNX

    • Middleware overview: Classic Vs Adaptive AUTOSAR

    • Importance of Hypervisors in SOA Architecture

    • Containerization in SDV

    • Edge Vs Cloud native Computing

    • Introduction to OTA

    • Ethernet as Backbone

    • V2X Communication Overview

    • TSN Overview

    • Advanced OTA Use Case: Gateway Server +4 Client architecture

    • V2X communication types: V2V (vehicle-to-vehicle), V21 (vehicle-to-infrastructure), V2P

    • (vehicle-to-pedestrian)

    • Bluetooth, Wi-Fi, 5G, and emerging standards for SDVs

    • Real-time communication and latency management

    • Agile development methodologies for SDVs

    • DevOps and CI/CD pipeline in automotive software

    • Software verification, validation, and compliance (ISO 26262, ASPICE)

    • Levels of vehicle autonomy

    • Sensor fusion and path planning algorithms

    • Role of machine learning and A1 in perception and decision-making

    • SDV data lifecycle management

    • Role of cloud in processing, storage, and remote diagnostics

    • Edge computing for real-time decision making

    • Threat landscape in automotive software

    • Security protocols and encryption methods

    • Key management and secure boot mechanisms

    • Base Platform Selection for Safety-Critical Apps

    • Cybersecurity in SDV: Secure communication, IDS, Blockchain, Quantum Resilience

    • Edge Security & Cloud Security Comparison

    • Continuous Homologation

    • Role of A1 and quantum computing

    • Digital twins and predictive maintenance

    • Emerging technologies: 6G, software-defined connectivity

Step into the future of automotive software

Upgrade your skills for next-gen automotive platforms—HPCs, Automotive Linux, AUTOSAR, OTA, V2X, and Cloud-Edge computing.

Register