New collaborative project aims to solve safety issues with autonomous vehicles

Close-up of driver's hands behind the steering wheel of a car — Photo: Chalmers

New collaborative project aims to solve safety issues with autonomous vehicles

Published

5 October 2023

at

AI and machine learning have accelerated the development of autonomous vehicles. By training the car's systems on a vast amount of data, the car can now recognize a parking space, a cyclist on the road, or a small child on the sidewalk. But how much data is enough to ensure that the vehicle does not make mistakes? How accurate does the data and its labels (parking, cyclist, child) have to be? These, and other questions, are what the FAMER project is set to answer.

"We aim to develop tools which will help all stakeholders in the manufacturing process to collaborate and reach a point where everyone feels confident that both the quantity and quality of the data are sufficient to ensure the system’s safety," says Eric Knauss, professor at the Department of Computer 91̽�� and Engineering.

In September he launched the, which is set to span three years and is funded by Vinnova. The project is coordinated by the University 91̽�� and partners include Kognic, RISE, Volvo Cars and Zenseact.

Read the full article on the department's main webpage.

Area

91̽�� and Information Technology