Parallel Domain launches virtual-world training platform for driverless vehicles


A new company led by former Apple and Pixar Animation employees, Parallel Domain, has used its experience in video gaming graphics and engineering simulation to launch its new virtual-world generation technology that will enable the large-scale training and testing of driverless cars before they hit public roads.

Autonomous vehicles (AVs) and automated ground transportation are projected to grow to multi-trillion-dollar markets at scale. However, for vehicles to demonstrate an acceptable level of safety, they will need to drive an estimated 11 billion miles to surpass current human standards and be prepared for critical corner cases, such as a pedestrian suddenly darting in front of a moving car.

AV development companies often build training worlds for their simulators by hand, which is prohibitively slow, often taking weeks to craft a few city blocks. Parallel Domain’s new platform can generate multiple realistic, highly detailed city blocks in less than a minute, unlocking the necessary simulated training and testing environments for automated vehicles.

The introduction of Parallel Domain’s new platform comes as the company makes its public debut armed with its Seed funding round of US$2.5m led by Costanoa Ventures and Ubiquity Ventures, with participation from RRE Ventures and Bessemer Venture Partners.

The Parallel Domain platform encompasses multiple ways to generate new worlds quickly. Real-world map data can be used to automatically reconstruct a photorealistic, living world complete with traffic, pedestrians, time of day, and more.

Any element is adjustable and programmable, from the number of lanes to the condition of the asphalt. Road curvatures, locations of mountains, and hundreds of new cities can be generated with a few simple clicks. Further, procedural growth algorithms and generative models can create a massive variety of fictional worlds, whether they are completely new or similar to real locations.

Parallel Domain says its approach works for any company currently developing driverless car technology. The platform ensures that car sensors and machine-learning algorithms all work for the full spectrum of simulated driving scenarios before a car ever hits the road. The company is launching with Shanghai-based NIO as a customer. NIO is a global startup that designs, develops and produces smart, high performance, premium electric vehicles for the Chinese market.

“We are at a turning point in the industry. Driverless cars need massive quantities of challenging training miles in order to learn how to drive safely, but these real-world miles are dangerous, expensive, and inflexible. State of the art simulations alleviate these bottlenecks while providing essential interactivity, control, and reproducibility,” stated Kevin McNamara, founder and CEO of Parallel Domain.

“Our software automatically generates the environments and scenarios that feed into simulators, making it safe and fast for autonomous vehicles to learn from their mistakes, accelerating time to safety for all vehicles.”

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About Author


Tom has edited Traffic Technology International (TTi) magazine and its Traffic Technology Today website since May 2014. During his time at the title, he has interviewed some of the top transportation chiefs at public agencies around the world as well as CEOs of leading multinationals and ground-breaking start-ups. Tom's earlier career saw him working on some the UK's leading consumer magazine titles. He has a law degree from the London School of Economics (LSE).