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For many decades congestion on highways and arterial roads has been a major problem of vehicular traffic worldwide. It is impossible to build and extend roads to keep up with the increase of traffic. Traffic congestion has a major impact on the environment, the economy and last but not least on the individual driving comfort. Congestion is caused by large-enough perturbations in dense traffic. We developed a driving strategy using Car-to-Car (C2C) communication to prevent congestion, which we call Jam-ADS (ADS = Advanced Distributed Strategy). C2C communication provides information about current positions and velocities of the vehicles ahead to a Jam-ADS processor in each vehicle. Jam-ADS aggregates this information and computes a velocity recommendation, which is presented to the driver. If sufficiently many drivers follow the recommendations congestion does not occur. In this work, we tested and evaluated several variants of Jam-ADS by simulating different scenarios. To do this, we developed our own traffic simulator CircSim to be able to influence the simulation and freely evaluate the results. CircSim simulates a closed road system consisting of a circular road of arbitrary length with arbitrary many lanes. To validate the results, we performed the same simulations with the established open-source traffic simulator SUMO and the communication network simulator Shawn. To make the simulations more realistic, we also performed our simulations in an open system consisting of a section of a highway with an on-ramp, because on-ramps are a major source of congestion-causing perturbations. Such a scenario is often used for the simulation of traffic congestion. In both scenarios we performed simulations, which showed that Jam-ADS improves the flow of traffic. To support the effectiveness of Jam-ADS beyond numerical simulations, we analyzed it mathematically as well by applying methods of control engineering. They confirmed that Jam-ADS damps all perturbations. ; Schon seit einigen Jahrzehnten sind Staus auf Autobahnen ...