Slippery Road Detection by Using Different Methods of Polarised Light

Abstract

Road friction measurement is an important issue for active safety systems on vehicles; hence knowledge of this key parameter can significantly improve the interventions on vehicle dynamics. This study compares two different on-board sensors for the classification of road conditions with polarised infrared light. Several tests are performed on a dedicated track, with focus on detection of dry or wet surfaces, and the presence of ice or snow. The work shows the capability of both sensors to provide a correct classification. In particular, results indicate how the monitored area, the presence of active illumination and the mounting position influence measurements and response times. It is concluded that both systems classify different road conditions in all cases. Performance of the Road eye system varied from 80 to 90% whereas the camera based IcOR achieved 70-80% accuracy level. Since these are being prototype sensors more development is needed before implemented into advanced safety applications.