Most research in vision-based driver assistance has utilized graylevel or color image sequences. Since the spatial arrangement of scene objects is often more relevant than the reflected brightness information, there has been an increasing interest in range sensors for collision avoidance systems recently. In our approach for obstacle detection and tracking, obstacles are defined as non-traversable objects. Thus obstacle detection is done by checking the traversability of the environment in the sensor's field of view. Once an obstacle is detected, it is tracked along the time axis. Robust long-term tracking is performed by the analysis of the spatial arrangement of obstacles. Our tracking scheme handles problems as occlusion, new appearance or disappearance of scene objects. To be robust against segmentation errors and poor reflection properties of scene objects, splitting of obstacles is taken into account. Our approach was tested on 11 range image sequences consisting of 447 frames. Different scenarios such as driving along a curve, oncoming traffic, high relative velocity between vehicles, and heavy traffic were investigated.