Reference Design

Automotive Control System

A complete example of how we build production-ready automotive systems—from concept to deployment. This reference design demonstrates our proven approach to functional safety, vehicle networking, and ADAS integration.

Overall Project Overview

What We Built

Advanced Driver Assistance System (ADAS) controller with real-time sensor fusion, object detection, and autonomous driving capabilities for Level 2+ automation.

• Multi-camera vision processing (up to 8 cameras)
• Radar and LiDAR sensor integration
• Vehicle CAN/CAN-FD bus interface
• Real-time path planning and control
• V2X communication support

Requirements & Design Philosophy

Safety First: ISO 26262 ASIL-D compliance with redundant processing and fail-safe mechanisms

Real-Time Performance: Deterministic processing with <10ms latency for critical safety functions

Scalability: Modular architecture supporting various vehicle platforms and sensor configurations

Reliability: Automotive-grade components rated for -40°C to +125°C operation

Maintainability: OTA update capability with secure boot and rollback protection

System Architecture

Distributed processing architecture with separation of safety-critical and non-critical functions:

• Primary ECU: High-performance SoC for AI/ML processing
• Safety MCU: Lockstep ARM Cortex-R5F for safety monitoring
• Sensor Hub: Dedicated processing for camera/radar fusion
• Gateway Module: Secure vehicle network communication
• Power Management: Intelligent power distribution with redundancy
• Diagnostic Interface: OBD-II and UDS diagnostic protocols

Hardware

Platform Choice

Arches Platform (NVIDIA Jetson Xavier NX) - Selected for its powerful AI/ML capabilities and automotive-grade reliability.

Why chosen: Superior neural network inference performance for real-time object detection and path planning

Hardware parameters: 384-core Volta GPU, 6-core Carmel CPU, 8GB LPDDR4x memory

Design Considerations

Form Factor: Compact 70mm x 45mm module with automotive connector interfaces

Power Requirements: 10-20W typical operation with automotive voltage range (7-36V DC)

Environmental Constraints: -40°C to +125°C operating temperature, vibration resistance per ISO 16750-3, IP67 ingress protection

Requirements & Design Philosophy: Redundant power supplies with fail-safe switching, thermal management for continuous high-load operation

OS/Firmware

OS Chosen & Configuration

Yocto Linux with PREEMPT_RT patches - Selected for real-time determinism and automotive-grade stability.

Why chosen: Deterministic scheduling for safety-critical functions, extensive automotive ecosystem support

Kernel configuration: Real-time priority scheduling, high-resolution timers, CPU isolation for critical threads

OS configuration: Minimal footprint with only essential services, secure boot with TPM integration

Drivers & Requirements

Drivers developed: Custom CAN/CAN-FD drivers with error handling, camera ISP drivers for automotive sensors, LiDAR interface drivers

Requirements & Design Philosophy: Zero-copy data pipelines for sensor fusion, watchdog timers for driver health monitoring, fail-safe driver recovery mechanisms

Middleware

Middleware Chosen

Autonomous Driving Data and Control (ADDC) Framework - Custom middleware stack optimized for automotive sensor fusion and control.

Why chosen: Purpose-built for automotive applications with proven safety and performance characteristics

Requirements & Design Philosophy: Modular architecture for easy customization, deterministic data flow with quality-of-service guarantees

Interfaces

Sensor Interfaces: Standardized APIs for camera, radar, LiDAR, and IMU data streams

Vehicle Interfaces: CAN/CAN-FD, LIN, and Ethernet for vehicle network communication

Application Interfaces: DDS (Data Distribution Service) for real-time data sharing between modules

Application

Applications Developed

ADAS Control Application - Real-time processing pipeline for autonomous driving functions.

• Object detection and classification using deep neural networks

• Sensor fusion algorithms for robust environmental perception

• Path planning and trajectory optimization

• Vehicle control algorithms with safety constraints

Interfaces & Requirements

Interfaces: RESTful APIs for configuration, WebSocket interfaces for real-time telemetry, CAN bus interfaces for vehicle control

Requirements & Design Philosophy: Modular design for easy feature addition, comprehensive error handling with graceful degradation, extensive logging for post-mortem analysis

Support Apps

Desktop

Configuration and calibration tools for ADAS parameter tuning, sensor alignment utilities, and diagnostic dashboards with real-time visualization.

Cloud

Fleet management platform for over-the-air updates, data analytics for performance monitoring, and remote diagnostics with predictive maintenance.

Mobile

Technician apps for on-site diagnostics, configuration tools for field service, and monitoring apps for test drives and validation.

Other Support

Cloud Interface & Diagnostics

Comprehensive cloud connectivity for data collection, remote monitoring, and advanced diagnostics.

• Secure MQTT-based cloud connectivity with end-to-end encryption

• Real-time telemetry streaming for performance monitoring

• Automated diagnostic algorithms with predictive maintenance alerts

• Historical data storage and analytics for continuous improvement

Profiling & Requirements

Performance Profiling: Real-time CPU/GPU utilization monitoring, memory leak detection, and bottleneck analysis tools

Requirements & Design Philosophy: Non-intrusive profiling with minimal performance impact, comprehensive coverage of all system components, automated report generation for optimization insights

Final Overview

What Will Be Delivered

Complete production-ready ADAS system with all hardware, software, documentation, and support tools.

• Fully assembled and tested hardware modules
• Complete software stack with source code
• Comprehensive documentation and design guides
• Support tools for configuration and diagnostics
• Integration guides and API documentation
• 12-month technical support and maintenance

Requirements & Design Philosophy

Production Ready: All components meet automotive industry standards and are ready for mass production

Customizable: Modular design allows easy adaptation to specific vehicle platforms and requirements

Supportable: Comprehensive documentation and tools ensure long-term maintainability and evolution

Scalable: Architecture supports future enhancements and additional ADAS features

Complete Documentation Available

Request the complete reference design package including hardware schematics, BSP/firmware, middleware, application code, support tools, and comprehensive documentation.