  It is common to utilise dynamic models to measure the tyre-road friction in
real-time. Alternatively, predictive approaches estimate the tyre-road friction
by identifying the environmental factors affecting it. This work aims to
formulate the problem of friction estimation as a visual perceptual learning
task. The problem is broken down into detecting surface characteristics by
applying semantic segmentation and using the extracted features to predict the
frictional force. This work for the first time formulates the friction
estimation problem as a regression from the latent space of a semantic
segmentation model. The preliminary results indicate that this approach can
estimate frictional force.
