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Model-based tracking of complex innercity road intersections

: Heimes, F.; Nagel, H.-H.; Frank, T.


Mathematical and computer modelling 27 (1998), No.9-11, pp.189-203
ISSN: 0895-7177
Journal Article
Fraunhofer IITB ( IOSB) ()
autonomous road vehicle; image sequence analysis; intersection model; kalman-filtering

Vision-based automatic driving along innercity roads and across complex innercity intersections requires to detect and track road markings and lane boundaries in order to determine the position and orientation of the vehicle relative to the ground. The complexity of intersection scenes and the disturbances in the detected contours enforce the use of model-based state estimation techniques. We recorded monocular image sequences of complex innercity road intersections from a moving small experimental truck in order to track intersection models using a Kalman filter. A scalar distance measure for the distance between image contour points and model edge segments turned out to be advantageous for the estimation process. This scalar measure is based on the simultaneous exploitation of edge location and directions, thus using more information about the image gray value variation than previously when only the perpendicular distance between the edge element and the model segment was taken into account. We report about the theoretical foundation of this approach, its implementation and experimental results from several intersection sequences, as well as detailed comparisons with a previous, less sophisticated approach. These examples demonstrate the kind of problems which are likely to occur more frequently at intersection scenes than at those road scenes encountered while following a more or less straight, uninterrupted highway lane with clearly marked boundaries.