Swarms are a known and studied phenomenon in biology. In different scientific fields transferring of the swarm ideas is done to solve specific problems. In computer science swarm approaches are applied from computer graphics till mobile robotics. The main contribution of this master thesis is to transfer swarm behaviour to the autonomous car context of the AutoNOMOS Project of the Freie Universität Berlin - A Swarm Behaviour for Path Planning.  Therefore a processing pipeline is developed, which generates a driving plan for the autonomous car from swarm based data. A detailed description of the different processing steps is given. The steps include the topics: 1) Swarm member selection, 2) velocity matching, 3) swarm member trajectory based path planning, 4) abstracting data from swarm member trajectories to generate clustered data, 5) cluster based path planning, and 6) plan smoothing with linear regression. Furthermore, the developed approach is evaluated and experimental results in simulation and live tests on the autonomous car MadeInGermany are provided.