Safer Automation with Friction Estimation from tiRe- and perceptIon- baseD sEnsing (SAFE-RIDE)

Research Project, 2025 – 2028

The project aims to design an embedded road friction predictor by actively combining perception-based and tire-based estimates. A handful of state-of-the-art AD/ADAS functions will be studied using the combined friction knowledge. With emerging data-driven methods and highly efficient calculation techniques, the project has the potential to revolutionize vehicle safety by providing a reliable real-time estimate of tire-road-road adhesion properties.

The project contributes to safer vehicles and a safer traffic environment, enabling the implementation of higher-level vehicle automation. Ultimately, this will help enable higher levels of vehicle automation by providing advanced driver assistance and autonomous driving functions with the ability to proactively adapt to changing road weather conditions in advance, significantly reducing the risk of traffic accidents.

Volvo Cars is the main applicant, supported by expertise in tire modeling and testing from VTI, as well as fusion technology from Chalmers. The project is scheduled to start in January 2026 and run until January 2028. An industrial doctoral student at Volvo Cars will work together with a project assistant at Chalmers. Road Condition Fusion Manager optimally combines different information sources in real time to meet the requirements for next-generation safe automation functions on board.