Multiple object recognition and scene interpretation for autonomous road vehicle guidance

The seeing car VaMoRs-P is the next step of development in computer vision for autonomous road vehicle guidance at the ´Universitat der Bundeswehr Munich´ (UBM). As one of the key functions, the module ´obstacle detection and tracking (ODT)´ has been developed since 1991; with several thousand kilometers of autonomous test driving a state of high reliability has been reached. For vehicles in the vehicle´s own lane the well known extraction of the left and right object boundaries using fast contour analysis is performed. Additionally, a new approach for recognition of vehicles in the neighboring lanes and those approaching from the rear is being developed. The lower object boundary detection using a knowledge based edge chaining algorithm and a special edge detector is presented. VaMoRs-P is equipped with four miniature CCD-cameras with different focal lengths mounted on two platforms viewing to the front and rear of the own car. For obstacle detection a range of 6 up to 120 meters distance in the own and the neighboring left and right lane is achieved. For collision avoidance and autonomous overtaking of slower driving road users a minimum number of 4 or 5 objects must be tracked in parallel. For this task ODT comprises about 15 transputers for image processing and state estimation.