A team of the University of Cambridge machine learning researchers created the British startup business Wayve in 2018. The goal of Wayve is to navigate the complex environment without relying on pre-programmed maps or human intervention.
Compared to other companies, Wayve is using artificial intelligence and machine learning for training their vehicles. To make the vehicle understand the rules of the road and the safety operation, Wayve is using neural network training.
Wayve senses its surroundings and makes judgments using a combination of radar, lidar, and camera sensors. Extensive testing of self-driving car technology is carried out on public roads in the UK, including navigating through traffic, pedestrians, and other obstacles.
One of the advantages of Wayve’s technology is its ability to adapt to different driving conditions and environments. It includes operating in a variety of settings, such as rural and suburban areas.
Wayve received various funding from a variety of sources, such as Microsoft, billionaire Virgin Group co-founder Richard Branson, and Meta chief AI scientist Yann LeCun. Even from venture capital firms and angel investors.
“Other self-driving technologies work only on specific mapped streets.” Wayve’s technology operates more like a human driver learning to drive in one city and then applying that knowledge to drive in new places.
According to consulting firm McKinsey’s prediction, by 2035, around 37% of new passenger cars sold will have “advanced” features in autonomous driving technology, where cars can handle most driving situations on their own without drivers taking control.
It is predicted that the self-driving car industry will bring in up to $400 billion in revenue annually.