Dynamical road modeling and matching for direct visual navigation

This paper proposes a new concept of direct visual navigation, (DVN), which superimposes virtual direction indicators and traffic information into the real road scene to give drivers efficient and direct visual navigation guidance. To align the virtual objects properly with respect to the real world, we need to solve the so-called Registration Problem in Augmented Reality (AR) context. Traditional solutions always employ a fixed and known-structure model as well as the object depth information to obtain the 3D-2D correlations, which is not possible in the case of on-road driving navigation. With the constraints of road structure and on-road vehicle motion features, this paper presents a dynamical multi-lane road shape modeling method as well as a road model matching method to simplify the 3D-2D correlation problem to the 2D-2D road model matching on projective image. Additional road shape lookup table (RSL) concept is also presented in this paper to calculate the road model matching score. The algorithms proposed in this paper are validated with the experimental results from real road test under different conditions and types of road.