Oxbotica, a UK-based autonomous vehicle software group, is using advanced Artificial Intelligence (AI) in the metaverse to accelerate the safe and efficient deployment of AV technology, reducing carbon emissions generated by vehicles driving actual miles. Oxbotica MetaDriver is a suite of tools that includes virtual world simulation, automated discovery of challenging scenarios, and real-time data expansion.
Oxbotica MetaDriver generates a vast bank of scenarios which are used to test and refine AV operations and behaviours without ever needing to physically drive in them.
It offers edge-case discovery rates at an average of 1,000 times faster than traditional testing methods, and up to 35,000 times faster in some situations.
It also provides the ability to build a digital twin representation from real-world gathered data.
MetaDriver is designed to give AV operators confidence that their vehicles are equipped to operate safely, accurately and effectively in their specialised environments, whether that is a city, mine, wind farm, solar park, or airport.
Paul Newman, founder and CTO at Oxbotica, says: “Oxbotica MetaDriver is a suite of tools that offers so much more than straight forward simulation. Using the metaverse in this way provides us and our customers with practically unlimited test challenges, revolutionising how we are accelerating AV commercial deployment to make the Earth move.”
He adds: “Oxbotica MetaDriver allows us to do the hard miles without the conventional need to physically drive the miles. The autonomous vehicle industry has become over indexed on the number of miles travelled as a synonym for safety, but what we actually care about is coverage of hard cases, not the endless miles endured. Oxbotica MetaDriver addresses this in a new and exciting way.”
Headquartered in Oxford, UK, and Toronto, Canada, Oxbotica provides customers with complete flexibility on how to deploy the technology to suit their individual needs.
Its partners include ZF, Ocado, bp, and Wenco.
Keyword: Oxbotica Uses ‘Metaverse’ to Accelerate Safe and Efficient Deployment of AVs