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Our autonomous and ADAS simulation platform accelerates testing and validation time to market of automated driving systems (AV) by supporting the entire development process: training, testing, validation and certification - all the way to commercial deployment


Key features
Realistic Digital Twin 3D Environments
  • Rich drivable 3D environments for AV simulation
  • Digital twins or entirely synthetic worlds for AV testing and validation
  • Photorealism synthetic data enabled by deep neural networks (DNN)
Synthetic Datasets
  • Large Scale datasets for training and testing AI machine learning (ML)
  • Exportable and reusable
  • Pixel perfect, Accurate and consistent annotation in every frame
Real-life Traffic Agents
  • Realistic drivers, cyclists, and pedestrians
  • AI with geo-specific interactive behavior profiles
  • Configurable & deployable at scale


Key features
Ready-to-Use AV Scenarios
  • Library of pre-built AV and ADAS scenarios for common automated driving functions
  • Support for standard ADAS and AV assessment programs
  • Fuzzing to quickly create new variations of scenarios for regulations and certification
Scenario Authoring & Management
  • Authoring, configuration, and management of scenarios
  • Simple web-based graphical interface
  • Powerful Python scripting capability
Simple Integration with Existing Components
  • Closed-loop simulation over standard interfaces
  • Automated testing with Jenkins and Bamboo
  • Coverage-based validation for PLM and requirement management


Key features
Extracting Insights
  • Ready-to-use pass/fail criteria for validation and certification of AV and ADAS
  • Powerful custom rule authoring
  • Trend mining for large scale simulation
  • Goal-oriented data representation
  • Multi-layer adaptive dashboards
  • Design decision augmentation
  • Measured progress toward road readiness
  • AV and ADAS virtual certification of regulatory requirements
  • Continuous support toward geo-expansion
AV Simulation: How it works
Static Layer - Digital Twin
Automatic Virtual Worlds for AV Testing

Procedurally-built 3D environments of roads, buildings, and infrastructure accurate down to the last lane marking, surface material, and traffic light.

Dynamic Layer - Vehicles and Pedestrians
Intelligent Traffic Agents for Path Planning and Policy Training

AI drivers, pedestrians, and cyclists that accurately replicate behavior customary to the region being simulated.

Sensing Layer
Accurate Simulation of Sensors

Popular camera, LiDAR, and radar photorealistic sensor models, built with deep neural networks (DNN), and a toolchain for quickly on-boarding new sensors.

Cloud Layer
Elastic Scale in the Cloud

Cost-effective infinite scale to cover thousands of scenarios and deliver results faster.

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