Unlocking IoT Potential: Strategic Approaches to Sensors and Communication
Date: Thursday, October 10 2024
Time: 10:00 PM (PST)
Location: Virtual
Register Here
SDV ADAS
Next-Generation Safety Intelligence & Rapid Prototyping Workshop
Duration
4 Hrs
Preferred Date
TBD
Preferred Location
TBD
Time
11:00 AM EST
Register Here
About the Workshop
This workshop enables automotive engineering teams to rapidly prototype, validate, and productionize AI-driven ADAS features (L2+ to L4) using industry-standard development platforms, with clear migration paths to production SoCs and compliance-ready architectures.
The workshop bridges innovation velocity and production readiness, demonstrating how advanced driver monitoring, predictive road intelligence, and generative AI accelerate ADAS roadmaps from concept to commercial deployment while meeting functional safety and cybersecurity requirements.
Agenda
Session 1: Strategic Context & Industry Trends (45 min)
- 2026 ADAS landscape: L2+ to L4 progression
- OEM case studies: Toyota Safety Sense 3.0, Honda Sensing 360, Tesla FSD
- Regulatory roadmap: Euro NCAP 2025+, UNECE, China C-NCAP
- Software-defined vehicle economics: Subscription models, feature monetization
Session 2: Pillar 1 - Intelligent Driver Assistance (75 min)
Use Case 1A: Next-Gen Driver Monitoring System (DMS) with Generative AI
- Multimodal fusion architecture: Vision, cabin sensors, vehicle dynamics, external context
- Five-stage adaptive escalation (Predictive Awareness → Contextual Intervention → Active Assistance → Urgent Safety Protocol → Minimal Risk Condition)
- Generative AI enhancements: Vision-Language Models, synthetic data, real-time personalization
- Production readiness: ISO 26262 ASIL B/D, UNECE R137, cybersecurity threat modeling
Use Case 1B: Driver Behavior Monetization Engine
- Anonymized driver scoring API for UBI, fleet certification, gamification
- Feature-on-demand unlocking and subscription tiers
- Data marketplace participation for safety research
Break (15 min)
Session 3: Pillar 2 - Predictive Road Intelligence (60 min)
Use Case 2A: Advanced Pothole & Road Hazard Intelligence System
- Multimodal detection: Vision, radar, lidar, IMU/suspension, V2X connectivity
- Three-layer intelligence: Onboard real-time, trip-based analytics, cloud predictive modeling
- Advanced features: Generative AI severity assessment, predictive maintenance, insurance claim automation
- Business impact: Fleet TCO reduction, customer satisfaction, municipal partnerships, insurance premium reduction
Use Case 2B: Weather-Adaptive Road Intelligence
- Weather API and precipitation detection
- Real-time traction optimization, black ice prediction, hydroplaning risk assessment
- Automatic driving mode switching (Sport → Comfort → Safety)
Session 4: Pillar 3 - Production-Ready Architecture & Compliance (75 min)
Module 3A: Platform Migration Strategy
- Jetson → production SoC migration (Qualcomm, NVIDIA, custom ASICs)
- HAL design, AUTOSAR integration, cross-platform optimization
- Hands-on lab: Deploy DMS model on Jetson AGX Orin and Qualcomm SA8775P, benchmark performance
Module 3B: Functional Safety & Cybersecurity Integration
- ISO 26262 ASIL decomposition: Camera failure, alert generation, driver override
- Fault Tree Analysis and FMEA hands-on exercises
- ISO 21434 threat modeling, UNECE R155/156 compliance
Module 3C: Edge-to-Cloud Architecture Design
- Onboard edge, 5G MEC edge, and cloud layers
- Hands-on lab: Federated learning pipeline, privacy preservation, 15% accuracy improvement over 30-day simulation
- ISO 21434 threat modeling, UNECE R155/156 compliance
Post-Workshop Deliverables
- Reference architecture diagrams (Visio/Lucidchart)
- Sample code repositories (GitHub CI/CD)
- Compliance checklists (ISO 26262, UNECE R155/156)
- ROI calculator spreadsheet
- 30-day email support for implementation questions
Workshop Objectives
Enable automotive engineering teams to rapidly prototype, validate, and productionize AI-driven ADAS features (L2+ to L4) using industry-standard development platforms, with clear migration paths to production SoCs and compliance-ready architectures.
This workshop bridges the gap between innovation velocity and production readiness, demonstrating how advanced driver monitoring, predictive road intelligence, and generative AI can accelerate your ADAS roadmap from concept to commercial deployment.
Who Should Attend
ADAS and AD engineering managers, software-defined vehicle platform leads, functional safety engineers, cybersecurity architects, product managers, fleet operations directors, advanced engineering and innovation labs, and teams working on L2+ to L4 ADAS systems
Why You Should Attend
- Accelerate ADAS feature time-to-market while maintaining ISO 26262 and cybersecurity compliance
- Bridge rapid prototyping with production deployment on real automotive SoCs
- Monetize safety intelligence through subscriptions, insurance, and fleet services
- Gain hands-on experience with generative AI, sensor fusion, and edge-to-cloud architectures
- Prepare for regulatory and market shifts impacting ADAS programs in 2026
- Prepare for regulatory and market shifts impacting ADAS programs in 2026
Key Takeaways
- Working DMS prototype with generative AI alerts
- Sensor fusion architecture and predictive road intelligence reference
- Platform migration checklist from prototype → production SoCs
- ISO 26262, ISO 21434, UNECE R155/156 compliance frameworks
- Feature monetization playbook and ROI models
- 90-day PoC roadmap with risk mitigation strategies
