Virtual ADAS Development Environment
SIMSTAR™️ powered by unique Eatron IP of “AI Controlled Agents”, enables every ADAS engineer to test, validate and calibrate algorithms and software at their desktop, enabling considerable savings in development cost
Photorealistic Rendering
Development and Validation of Computer Vision / DL Algorithms
Vehicle Models
Accurate vehicle models. Easy Integration of 3rd party models.
Sensor Models
Lidar, Radar, Camera, GPS, IMU, Ultrasonic, Raw and Labelled Values
AI Controlled Agents
Artificial Intelligence Controlled Agents with Calibratable Parameters
Scenario Generation
Define Agents and Trajectories Weather Conditions Automate Testing
Environment Generation
Import HD Map Easily Recreate Infrastructure and Landmarks
Photorealistic Rendering
Based on the industry leading Unreal Engine development platform, SIMSTAR simulation environments are perfectly suited to the development of Computer Vision algorithms including;
- Training
- Validation
- Integration
Vehicle & Sensor Models
Built in vehicle model is based on Nvidia PhysX 3.X Engine, which allows realistic modelling of; “engine, transmission, differential, suspension and tire model.” Sensor suite includes:
- RADAR (Raw / Smart)
- Multiple Cameras (Raw / Smart)
- LIDAR
- IMU
- Ultrasonic
3rd Party models can be integrated as a Simulink or compiled model.
Vehicle & Sensor Models
Built in vehicle model is based on Nvidia PhysX 3.X Engine, which allows realistic modelling of; “engine, transmission, differential, suspension and tire model.” Sensor suite includes:
- RADAR (Raw / Smart)
- Multiple Cameras (Raw / Smart)
- LIDAR
- IMU
- Ultrasonic
3rd Party models can be integrated as a Simulink or compiled model.
Custom Environment and Scenario Definition
Through the Environment Editor user can easily modify the built-in environments or create new ones from scratch, including importing map information from OpenStreetMap. The Scenario Definition API gives user the possibility to;
- Set-up automated testing in “infinite” environment
- Define number of agents and their default behaviour (aggressive / assertive / defensive)
- Define special agent trajectories / behaviours
- Change weather conditions
