Developing India-Specific Virtual Scenarios from Real-World Data – ADAS Use Cases

ADAS enhances road safety by assisting drivers with real-time alerts and automated responses to potential hazards. With increasing traffic density and accident rates, these systems are essential for reducing human error and improving driving efficiency. However, ADAS validation is inherently complex due to the need for consistent performance across diverse driving scenarios and environmental conditions. In India, this complexity is heightened by unique challenges such as heterogeneous traffic, inconsistent road infrastructure, and unpredictable road user behavior. To effectively address these challenges, it is crucial to incorporate both India-specific driving scenarios and high-fidelity 3D assets into simulation environments. These localized elements enable more accurate and realistic testing, ensuring that ADAS technologies are robust, reliable, and well-suited to the Indian driving context.

Explore an end-to-end pipeline for creating simulation-ready real-world scenarios from recorded vehicle data using Scenario Builder from Automated Driving Toolbox™ and RoadRunner. 

Highlights:

• Data collection setup – sensor configuration, mounting, and calibration
• Automation of annotation task for India-specific asset 
• Sensor fusion logic for track generation and robust traffic simulation
• Generative AI for simulation-ready 3D asset creation from high-res images

The resulting synthetic scenarios are validated for realism and functionality, supporting applications in autonomous vehicle testing and traffic simulation. This framework provides a scalable, automated solution for generating high-fidelity, India-centric synthetic scenarios, enhancing the development of robust autonomous systems.