Conducción Autónoma End-to-End y Simulación de Sensores
SelfDriveSim proporciona pistas de prueba virtuales de alta fidelidad donde las redes neuronales de percepción entrenan a lo largo de miles de millones de kilómetros sintéticos. Modela óptica a nivel de fotones para cerrar la brecha sim-to-real en Nivel 4.
Simulation Engine Core Zonal Architecture
Central Controller: Simulation Engine Core — GPU Ray-Tracing Pipeline
Zonal Control Units & TSN Ring
- RTX-Accelerated LiDAR Pulse Synthesizer
- CMOS Sensor Physics & Bayer Filter Engine
- Electromagnetic Wave Radar Scatterer
- ASAM OpenDRIVE Road Graph Generator
- Direct Video Injection (GMSL2/FPD-Link)
Cerrando la Brecha de Realidad entre Simuladores Virtuales y Cámaras Reales
Validar software de conducción autónoma requiere reproducir casos límite con repetibilidad bit a bit. SelfDriveSim combina dinámica vehicular ISO 8855 con carreteras OpenDRIVE, evaluando el comportamiento bajo lluvia, niebla y deslumbramientos solares.
Core Engineering Areas
- Hardware Ray-Traced LiDAR Simulation — Shooting millions of optical rays per second using GPU ray-tracing cores to calculate accurate returns from vehicle paint, retroreflective road signs, and asphalt.
- CMOS Camera Sensor Physics — Simulating the photon-to-electron conversion pipeline inside automotive image sensors, including temperature-dependent dark current noise.
- Radar Backscatter & Multipath Clutter — Computing Radar Cross Section (RCS) using physical optics approximations to capture multipath ghost reflections from guardrails and bridge decks.
Technical Articles
Related Cluster Architecture Specifications
- AutomotiveSDV — Full SDV Stack & Reference Architecture
- A2HCard — Agent-to-Human (A2H) Interface Cards & In-Cabin Autonomous Interaction Manifests
- A2HumanCard — Standardized In-Vehicle AI Agent Capability Discovery, Trust & Authorization Cards
- AIDrivenSynBio — AI-Driven Synthetic Biology for Automotive In-Cabin Air Purification, Bio-Engineered Pathogen Scavengers & Molecular Biosensors