Our simulation suite offers a comprehensive solution for accelerating the development of advanced driver assistance systems (ADAS) and autonomous driving (AD) technologies. We provides a cost-effective alternative to physical prototypes, enabling virtual testing and analysis of radar, lidar, and camera sensors within realistic driving scenarios. Our Headlamp simulation facilitates the rapid development of intelligent headlamp systems by validating control behavior and testing edge cases early in the design phase. Meanwhile, We streamlines the development of ADAS/AD systems by simulating driving tests virtually, leading to significant cost and time savings.
Realistic Driving/ Flight Scenarios using the Driving/ Flight Simulators.
Our sensor simulation solution provides a cost-effective alternative to physical prototypes, accelerating the design process. It enables virtual testing and analysis of sensors, such as radar, lidar, and camera sensors, within realistic driving scenarios. This allows for comprehensive examination of sensor perception in both Mil Sil and Hil contexts.
Test Lighting Systems in a Controlled Environment.
Our Intelligent headlamps Simulation solution offers Real-time Headlight Simulation, C++ / Simulink Plugin for Control Law Development, Discomfort Glare Assessment, Multiscreen + Driving Simulator, Advanced Headlights (Matrix Beams, Pixel Beams), Night Test Driving, IIHS Virtual Regulation, Sensor Camera Model, Smart HL Simulation, Photometric Analysis Tools, Driver In the Loop Assessment.
Streamline Development & Validation of L2+, L3 & above ADAS/AD systems.
Our Autonomous vehicle Simulation solution facilitates the development of L2+, L3, and higher-level ADAS/AD systems by simulating the majority of required driving tests through virtual simulation. With our Autonomy solution, companies can achieve up to a 100,000x reduction in cost and time to compliance. This reduction is realized through at least a 100x decrease resulting from the virtualization of actual drives, supplemented by an additional 1000x reduction through adaptive optimization in the cloud.
