Wayve's Fleet Learning Technology

Fleet Learning Technology

What makes AV2.0 unique is that our intelligent autonomy software constantly improves from every mile driven across all fleet deployments. Our Fleet Learning Technology enables this network effect.

This platform brings together all of the capabilities needed to train, evaluate, and deploy machine learning systems that can operate safely at scale in the real world. Today, we’re building technology to collect data from fleets of vehicles, train models on vast amounts of driving data, create simulated worlds where it can learn how to drive in different environments and situations, and ensure that these models are safe before they’re deployed on real roads.

Large scale driving data

Data is a key ingredient for our autonomous driving software to learn how to drive safely and reliably in different environments. It is also crucial in evaluating the performance of our AI Driver.

We’ve built a robust system for collecting and analysing data from all on-road experiences and simulated environments to enable continuous learning. We continually expand our driving datasets to cover various environments, such as urban and suburban roads, during the day and night and in many weather conditions.

Image of the driving data that Wayve processes

Groundbreaking MLOps

To ensure our models are developed responsibly, we’re developing groundbreaking MLops workflows—creating new tools, processes and pipelines that allow us to build, train and deploy billion-parameter AI models on vehicles more quickly and confidently.

We’re building new methods to manage our foundation models faster and more confidently across the entire machine learning lifecycle so that we can demonstrate that our AI Driver is safe and trustworthy.

Overhead view of a virtual intersection created by Wayve's Infinity Simulator

Computer vision perception system on Wayve self-driving system

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Infinity Simulator

We are building a world-class simulator to train and evaluate our autonomous driver to function in any environment. Our simulator enables us to test our AI Driver on an infinite number of miles and an endless array of driving scenarios in diverse generated worlds. Virtual testing allows us to test situations that would otherwise be difficult or unsafe to try on real roads using simulation testing. We can also experiment in simulation with new vehicle platforms and different geographies before we build prototypes for real-world applications.

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Fleet Learning Technology

Fleet Learning Technology

Large scale driving data

Groundbreaking MLOps

Infinity Simulator

Learn more about our technology

Evaluating driving performance in diverse simulated worlds

Wayve and DPD launch a Fleet Data Collection Pilot Program in the UK

Our journey