A cutting-edge web application that combines traditional ISO 26262 ASIL determination methods with AI-powered validation to ensure accurate automotive safety assessments.
- Dual Validation System: Compare database results with AI analysis from OpenAI GPT-4 or Anthropic Claude
- Intelligent Discrepancy Detection: Automatically identifies and highlights differences between database and AI assessments
- Real-time Reasoning: Get detailed explanations for Severity, Exposure, and Controllability ratings
- Auto-Learning: Optionally update the database with AI-validated results
- ISO 26262 Compliant: Follows official automotive safety standards
- Interactive Parameter Adjustment: Modify S, E, C parameters with instant ASIL recalculation
- Visual Matrix Display: Interactive ASIL determination matrix with color coding
- Component Database: Pre-loaded with common automotive components
- Futuristic UI: Glassmorphism design with neon accents and animations
- Responsive Design: Works seamlessly on desktop, tablet, and mobile
- Dark/Light Mode: Automatic theme detection with manual override
- Accessibility First: WCAG compliant with keyboard navigation support
- Modern web browser (Chrome, Firefox, Safari, Edge)
- AI API key (OpenAI or Anthropic) for enhanced features
git clone https://github.com/suduli/AI-ASIL-Analyser.git
cd AI-ASIL-Analyser
git checkout Version_V1# Simply open index.html in your browser
open index.html
# Or serve with a local server (recommended)
python -m http.server 8000
# Visit http://localhost:8000- Click the ⚙️ settings button
- Enter your OpenAI or Anthropic API key
- Select your preferred AI provider
- Save settings
- Select a component from the dropdown (e.g., "brake system", "body control module")
- View instant results from the pre-built database
- Enter any automotive component name
- Click "Analyze with AI Validation"
- Compare database vs AI results
- Modify Severity (S0-S3), Exposure (E1-E4), or Controllability (C1-C3)
- See real-time ASIL level updates
- View detailed ISO 26262 matrix position
User Input → Database Lookup → AI Analysis → Comparison → Results Display
↓ ↓ ↓
Instant Real-time Discrepancy
Results Reasoning Detection
- Review detailed reasoning from both sources
- Analyze the differences highlighted in the banner
- Choose to adopt AI values if they're more accurate
- Optionally save improved results to database
AI-ASIL-Analyser/
├── index.html # Main application HTML
├── style.css # Enhanced futuristic styling
├── app.js # Core application logic
├── components_db.js # Automotive components database
├── README.md # This documentation
└── assets/ # Additional resources
├── icons/
└── images/
- Frontend: Vanilla HTML5, CSS3, JavaScript (ES6+)
- Styling: Custom CSS with CSS Variables, Glassmorphism
- AI Integration: OpenAI GPT-4, Anthropic Claude APIs
- Standards: ISO 26262-3 ASIL Determination
- Primary: Neon Cyan (
#00f5ff) - Main interactive elements - Secondary: Neon Purple (
#bd00ff) - AI-related features - Success: Neon Green (
#00ff88) - Database results - Warning: Neon Orange (
#ff6b35) - Discrepancies - Error: Neon Red (
#ff2965) - Critical issues
- Headings: FKGroteskNeue (futuristic, clean)
- Body: Inter/Geist (readable, modern)
- Code: Berkeley Mono (technical elements)
- Glassmorphism: Translucent panels with backdrop blur
- Neon Glows: CSS box-shadow animations
- Gradient Borders: Dynamic color transitions
- Particle Effects: Animated background grid
- Model:
gpt-4-turbo-preview - Strengths: Comprehensive reasoning, automotive domain knowledge
- API Key Format:
sk-...
- Model:
claude-3-opus-20240229 - Strengths: Detailed safety analysis, ISO standard compliance
- API Key Format:
sk-ant-...
- Model:
openai/gpt-oss-20b:free - Strengths: Detailed safety analysis, ISO standard compliance
- API Key Format:
sk-or-v1-...
- Component Analysis: AI receives component description and safety context
- Structured Response: Returns S, E, C values with detailed reasoning
- Validation & Comparison: Compare with database and highlight discrepancies
- Braking Systems: brake system, ABS, brake pedal, brake fluid reservoir
- Steering Systems: power steering, steering wheel, steering column
- Powertrain: engine control unit, transmission, throttle control
- Body Electronics: body control module, lighting systems, HVAC
- Safety Systems: airbags, seatbelt systems, emergency braking
- Chassis Systems: suspension control, electronic stability control
- Communication: CAN bus, gateway modules, diagnostic systems
- ADAS Components: cameras, radar, lidar, sensor fusion
- Electric Vehicle: battery management, charging systems, inverters
- Autonomous Driving: path planning, decision making, fail-safe systems
const componentsDB = {
"component_name": {
S: 3, // Severity (0-3)
E: 4, // Exposure (1-4)
C: 3, // Controllability (1-3)
asil: "D", // Determined ASIL level
reasons: {
S: "Detailed severity reasoning",
E: "Detailed exposure reasoning",
C: "Detailed controllability reasoning"
}
}
}const aiConfig = {
provider: 'openai' | 'anthropic',
apiKey: 'your-api-key',
model: 'gpt-4' | 'claude-3-opus'
};const autoLearn = {
enabled: true,
requireConfirmation: true,
backupOriginal: true
};- Database Components: Verify all pre-loaded components return expected ASIL levels
- AI Integration: Test API connectivity and response parsing
- Parameter Modification: Ensure real-time ASIL recalculation
- Discrepancy Detection: Validate comparison logic accuracy
- Responsive Design: Test across different screen sizes
- Accessibility: Verify keyboard navigation and screen reader support
- ISO 26262 Compliance: All calculations follow official standard
- AI Response Validation: Structured prompts ensure consistent output
- Error Handling: Graceful degradation when AI services unavailable
- Performance: Optimized for fast loading and smooth animations
We welcome contributions! Please follow these guidelines:
- Fork the repository
- Create a feature branch:
git checkout -b feature/amazing-feature - Make your changes and test thoroughly
- Commit with descriptive messages:
git commit -m 'Add amazing feature' - Push to your branch:
git push origin feature/amazing-feature - Open a Pull Request
- Component Database: Add more automotive components with accurate ASIL data
- AI Prompts: Improve prompt engineering for better AI responses
- UI/UX: Enhance the user interface and experience
- Documentation: Improve guides, examples, and API docs
- Testing: Add automated tests and validation scripts
- Performance: Optimize loading times and animations
When adding new components, ensure:
{
S: 0-3, // Based on ISO 26262-3 Table 1
E: 1-4, // Based on ISO 26262-3 Table 2
C: 1-3, // Based on ISO 26262-3 Table 3
asil: "QM"|"A"|"B"|"C"|"D", // From ISO 26262-3 Table 4
reasons: {
S: "Clear severity justification with ISO reference",
E: "Exposure probability explanation with scenarios",
C: "Controllability assessment with driver capability analysis"
}
}This project is licensed under the MIT License - see the LICENSE file for details.
- ISO 26262: International standard for automotive functional safety
- OpenAI: GPT-4 API for intelligent component analysis
- Anthropic: Claude API for safety-focused reasoning
- Automotive Industry: Domain experts who contributed to component database
- Open Source Community: Libraries and tools that made this possible
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Email: [email protected]
- Documentation: Wiki
- Enhanced AI prompt templates
- Export functionality (PDF, JSON, CSV)
- Component search and filtering
- History tracking and comparison
- Multi-language support
- Advanced analytics dashboard
- Batch component analysis
- Integration with CAD tools
- Machine learning model training
- Real-time collaborative editing
- Enterprise SSO integration
- Advanced reporting and compliance
Built with ❤️ for the automotive safety community Ensuring safer vehicles through intelligent ASIL determination