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Automated, conductive charging systems enable both, the transmission of high charging power for long electric driving distances as well as comfortable and safe charging processes. Especially by the use of heavy and unhandy cables for fast charging, these systems offer user friendly vehicle charging - in particularly in combination with autonomously driving and parking vehicles. This paper deals with the definition of requirements for automated conductive charging stations with standard charging connectors and vehicle inlets and the development of a fully-automated charging robot for electric and plug-in hybrid vehicles. In cooperation with the project partners BMW AG, MAGNA Steyr Engineering, KEBA AG and the Institute of Automotive Engineering at Graz University of Technology, the development and implementation of the prototype took place in the course of a governmental funded research project titled “Comfortable Mobility by Technology Integration (KoMoT)”.

Car driver’s behavior and its influence on driving characteristics play an increasing role in the development of modern vehicles, e.g. in view of efficient powertrain control and implementation of driving assistance functions. In addition, knowledge about actual driving style can provide feedback to the driver and support efficient driving or even safety-related measures. Driving patterns are caused not only by the driver, but also influenced by road characteristics, environmental boundary conditions and other traffic participants. Thus, it is necessary to take the driving circumstances into account, when driving patterns are studied. This work proposes a methodology to cluster and evaluate driving patterns under consideration of vehicle-related parameters (e.g. acceleration and jerk) in combination with additional influencing factors, e.g. road style and inclination. Firstly, segmentation of the trip in distance series is performed to generate micro cycles.