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Automated Scenario Curation for Safer ADS

This is the second blog in a series. In the first blog (Accelerating Automated Driving System Deployment with Scalable, Data-Driven Evaluation), Mike Stellfox pointed out that the real challenge in AV development has shifted from simply building systems to ensuring we can truly trust them.

Blog Post

Interview with Glen De Vos - Foretellix’s Newest Board Member

You’re joining our board as Temasek’s representative, what about our technology, team, and vision excites you? What excites me about working with the Foretellix team is that they are offering a comprehensive solution to a critical issue that OEM’s and Tier 1’s are facing during the development of Level 2++, 3 and 4 advanced mobility systems. ...

Why High-Fidelity Sensor Simulation Is Critical for AV Development and Testing

Autonomous vehicles (AVs) must safely navigate complex and unpredictable environments. Yet even the most advanced perception systems face limitations when an object or road user is temporarily hidden from view. These occlusion scenarios, blind spots caused by obstructing vehicles, are among the most critical and difficult to test....

Automated Map Construction from Vehicle Perception Data

The autonomous vehicle industry is undergoing a transition from high-definition maps toward real-time perception-based navigation. This shift raises a critical challenge for development teams: their simulation and validation tools still require detailed maps that are becoming increasingly costly and impractical to maintain....

Beyond NCAP: Achieving ADAS Safety in the Real World

Many of today’s most advanced vehicles proudly display their 5-star NCAP safety ratings, and for good reason. These standardized tests have driven major safety improvements across the industry, offering a reliable benchmark for features like Advanced Emergency Braking (AEB) and Crash Avoidance....

Shifting Left: A Case Study on Cutting Costs and Accelerating AV Development

Facing escalating development costs and lengthy validation cycles, a leading Level 4 autonomous vehicle company turned to simulation to complement its real-world driving and modernize its testing strategy. ...

Accelerating Automated Driving System Deployment with Scalable, Data-Driven Evaluation

As advanced ADAS systems are doing more of the driving for us and fully autonomous vehicles hit the streets without safety drivers, e.g Waymo Robotaxis, Aurora Self-driving Trucks, the question isn’t just ‘can we build them?’—it’s ‘can we trust them?'...

Unlocking Scalable Neural Reconstruction for AV Development

Neural reconstruction has emerged as a promising technology, enabling the creation of realistic 3D simulation from real-world drive data, to validate increasingly complex systems across a vast range of scenarios, including rare edge cases, without compromising safety while keeping to development schedules....

Ten Essential Categories for Scenario Variation

Developing autonomous vehicle (AV) stacks capable of safely navigating real-world environments involves rigorous training, testing, and validation against countless realistic scenarios. Each scenario must be represented in numerous variations to comprehensively assess and ensure AV stack safety and performance. This complexity underscores the critical importance of systematic scenario variation and management within the AV development process....

Foretellix's MCP Bridge Brings AV Testing to Your AI Agent

Discover how Foretellix’s MCP Bridge brings AV testing into your AI assistant, with scenario launches, test runs and result analysis without leaving your development environment. ...

AI, Autonomy, V&V and Abstractions - Automating at Hyper Speed

In this blog, I will look at the near-term future of AI-based autonomy and will discuss: trends in AI-based autonomy - E.g. the move to “end-to-end”, the growing role of V&V in autonomy and the need for a common tool for both V&V and implementation of AI-based systems ...

Creating “Right-of-Way Violator” Scenarios for Synthetic Sensor Data Generation

The need for realistic and reliable driving data is imperative for training AI-powered AV stacks with end-to-end planning models, and yet, real-world data is limited in diversity and scale. The solution is to generate synthetic data that is both scalable and controllable....

Foretellix Expands Data Automation Toolchain with NVIDIA Omniverse and Cosmos Transfer

Foretellix Expands Data Automation Toolchain for AI-Powered AV Development with Breakthrough Simulation Capabilities Using NVIDIA Omniverse and Cosmos Transfer...

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