Abstract
Keywords - environment perception, driver assistance, intersection assistance, stereo vision, space-time stereo.
More than one third of all traffic accidents with injuries occur in urban areas, especially at intersections. Therefore, a driver assistance system supporting the driver in cities is highly desirable and has a tremendous potential of reducing the number of collisions at intersections.
A suitable system for such complex situations requires a comprehensive understanding of the scene. This implies a precise estimation of the free space and the reliable detection and tracking of other moving traffic participants. Since the goal of accident free traffic requires a sensor with high spatial and temporal resolution, stereo vision will play an important role in future driver assistance systems.
Most known stereo systems concentrate on single image pairs. However, in intelligent vehicle applications image sequences have to be analyzed. The contribution shows that a smart fusion of stereo vision and motion analysis (optical flow) gives much better results than classical frame-by-frame reconstructions. The basic idea is to track points with depth known from stereo vision over two and more consecutive frames and to fuse the spatial and temporal information using Kalman filters. The result is an improved accuracy of the 3D-position and an estimation of the 3D-motion of the considered point at the same time. This approach, called 6D Vision, enables a detection of moving objects even if they are partially hidden.
From static points very accurate occupancy grids are built. A global optimization technique delivers a robust estimation of the free space. Pixels moving in the world are clustered to objects which are then tracked over time in order to estimate their motion state and to predict their paths. This allows for powerful collision avoidance systems: pedestrians crossing the street are detected before they enter the lane; the same holds for vehicles from the sides which are not detectable by common radar systems. Since we are able to estimate the yaw rate of oncoming traffic, the prediction is not restricted to straight motion but can detect potential collisions with turning traffic, especially at intersections.
Urban vision asks for a large field of view. Within the German project AKTIV a fisheye stereo camera system is under development with a field of view of up to 150 degrees. If the 6D-Vision principle is applied to these images, laterally entering vehicles are also detectable.