As part of research on advanced driving assistance systems (ADAS), the ICUB project aims at designing and developing a new vision based system able to detect road obstacles, even in critical situations like moving obstacles, presence of reflecting objects or puddles on the road, poor weather conditions or faraway obstacles. We propose in this project a consistent system that includes all necessary steps from data acquisition to the targeted detection. Regarding the imaging system, it will involve a stereo-polarimetric head. Obstacle detection will be implemented through multimodal fusion of polarimetric data and disparity map, as provided by stereovision. The main objective of multimodality is to leverage jointly fine scale discrimination of detected objects thanks to polarimetry and accurate distance evaluation of the obstacles (and hence their level of danger) via the disparity map. The use of non-conventional imaging provides an alternative to existing detection techniques by proposing the detection of surface-based properties rather than relying on gray levels or on the geometric properties of obstacles, as conventional scalar methods do. The ICUB project brings together two research laboratories (LITIS, LE2I) and two industrial partners (STEREOLABS and PSA). Each partner is eager to leverage polarimetric information to address road scene analysis.