The novel reactive method of avoiding dynamic obstacles by real-time optimization introduced before at the measuring campaign at DEKRA Lausitzring, was tested on the airfields of DLR Oberpfaffenhofen with different scenarios of obstacles. As before mentioned, this method uses a monocular camera to identify dynamic obstacles in the image sequence by clustering the optical flow. The respective epipoles of the clusters are determined and afterwards the relative epipole positions are evaluated to identify colliding and dangerous objects. The correlation between the vehicle’s velocities and the cluster epipoles is derived and utilized in a cost function for shifting the epipoles. By optimizing this cost function, the vehicle is able to avoid collisions, which means that the 3D motion is deduced from purely 2D image data. The method was tested and evaluated for single and multiple stationary objects and for a combination of static and moving objects.