Abstract
In this paper a real time and automatic system for data analysis (ADAS: Automatic Data Analysis System) will be developed for the different kinds of traffic data. ADAS combines different procedural models from traffic engineering with approaches of artificial intelligence into a hybrid overall system for data analysis. The architecture of ADAS (in three steps) and the combination of the different components will be described in detail. The first aspect to be dealt with will be the plausibility check and the aggregation of the very often inconsistent and faulty input data, followed by the deep data analysis with different models. In its third step ADAS interprets the results of the data analysis up to the derivation of output information with knowledge based approaches.A final example with a real test environment from the SOCRATES field trial will indicate the feasibility of the approach. Incident detection tests at places in the SOCRATES area which are known for recurrent congestion will exemplify the interplay of the detection site data, the model, and the floating car data.
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