ACTIVE
Research
DriveMind-Prototype
Intelligent driving decision framework combining LLM reasoning with physics models for 4500x faster decisions
// DESCRIPTION
DriveMind bridges the gap between high-level LLM reasoning and real-time driving decisions through a novel hybrid architecture.
Architecture
┌─────────────────────────────────────────────────────────────┐ │ Scene Understanding │ │ (Camera, LiDAR, HD Map, Traffic) │ ├─────────────────────────────────────────────────────────────┤ │ ┌─────────────────┐ ┌─────────────────┐ │ │ │ LLM Reasoning │ ←──→ │ Physics Model │ │ │ │ (Strategy) │ │ (Risk Field) │ │ │ └─────────────────┘ └─────────────────┘ │ │ ↓ ↓ │ │ ┌─────────────────────────────────────────────┐ │ │ │ Decision Fusion Layer │ │ │ │ (LLM intent + Physics constraints) │ │ │ └─────────────────────────────────────────────┘ │ │ ↓ │ │ Motion Planning & Control │ └─────────────────────────────────────────────────────────────┘
Key Innovation
- LLM for Strategy: High-level decision making (lane change, overtake)
- Physics for Safety: Risk field ensures collision avoidance
- Hybrid Fusion: LLM intent constrained by physical feasibility
- 4500x Speedup: Pre-computed LLM decisions + real-time physics
Dataset Support
- highD: German highway recordings
- inD: Intersection scenarios
- rounD: Roundabout maneuvers
- CARLA: Simulation integration
Performance
| Metric | Value |
|---|---|
| Decision Latency | <1ms |
| Safety Violation Rate | 0.02% |
| Scenario Coverage | 95%+ |
// HIGHLIGHTS
- Nature Communications Risk Field integration
- Multi-dataset evaluation framework
- Academic paper in preparation
- CC BY-NC-SA 4.0 License