Braking Distance Minimization on Roads with Varying Friction

Licentiate thesis, 2025

Braking safely and efficiently becomes especially challenging when road friction is uneven—for example, when one side of the car is on ice while the other is on asphalt. This situation, known as split friction, can cause vehicles to veer off course unless both braking and steering are carefully controlled.

This thesis explores how optimizing both braking and steering can minimize stopping distances on split friction roads. By using mathematical optimization and vehicle simulations, the research shows that traditional braking systems, like ABS, work well when the friction difference between the left and right wheels is small. However, on more extreme split friction surfaces, a more advanced approach is needed—allowing slightly higher slip at the low-friction wheels and adjusting steering to maintain stability. A proposed control method, tested in simulations, reduces stopping distances by up to 13% compared to professional human drivers.

The research also investigates how a vehicle’s path can be optimized when friction varies across the road, such as when avoiding an icy patch. Results show that even a simplified vehicle model can accurately predict optimal paths, offering a fast and efficient way to enhance automated braking and path-planning systems.

These findings could help improve the safety and performance of future driver assistance systems, ensuring vehicles can stop faster and more predictably in challenging road conditions.