Wayve’s Lingo-1 brings human-like reasoning to self-driving cars


Wayve, a British startup specializing in AI-based autonomous driving, unveils its new model: Lingo-1, which combines machine vision with text-based logic.

Humans have to make decisions on the road all the time: When do we step on the gas, when do we take our foot off the gas, when do we pass or when do we hold back?

Self-driving cars have to make the same decisions. But unlike humans, they can’t justify their decisions – not yet. Lingo-1 aims to change that.

Image: Wayve

Lingo-1 combines language models with visual models

Typical autonomous driving systems rely on visual perception to make decisions. Wayve’s new Lingo-1 visual language model inserts textual logic between visual perception and action, allowing the car to explain its actions.



For a driving decision and for the general traffic situation, the car continuously provides textual statements describing the current situation and justifying decisions, similar to a driver thinking aloud or a driving instructor wanting to support the learner’s attention.

Video: Wayve

This textual logic could increase the sense of safety in cars by making their decisions seem less like a “black box”. It could also contribute to the safety of autonomous vehicles by allowing the system to reason textually through traffic scenarios that are not included in the training data.

In addition, Lingo-1’s behavior can be flexibly adjusted through simple text prompts, and it can be trained with additional examples written by humans without the need for extensive and costly visual data collection.

“Causal reasoning is vital in autonomous driving, enabling the system to understand the relationships between elements and actions within a scene,” Wayve writes.


Leave a Comment

Your email address will not be published. Required fields are marked *

Scroll to Top