His doctoral thesis at hand comprises the state-of-the-art in microscopic traffic modeling and simulation methodology. The first part deals with a microscopic traffic flow theory. Models describing the individual acceleration, deceleration and lane-changing behavior are formulated and the emerging collective traffic dynamics are investigated by means of simulations. The models and simulation tools presented provide the methodical prerequisites for the second part in which a novel concept of a traffic-adaptive control strategy for Adaptive Cruise Control (ACC) systems is presented. The impact of such systems on the traffic dynamics can solely be investigated and assessed by traffic simulations. In order to ensure that ACC systems are implemented in ways that improve rather than degrade traffic conditions, the thesis proposes an extension of ACC systems towards traffic-adaptive cruise control by means of implementing an actively jam-avoiding driving strategy. The presented concept is aiming at moving forward adaptive and cooperative technologies for vehicle-based intelligent transportation systems (ITS).

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