Abstract
The paper presents a method of travel time estimation by neural nets based on traffic data collected by cameras of the Intelligent Transportation System in the city of Wroclaw, Poland. The methodology is explained of using traffic intensity data as neural net inputs and of using car plate number recognition system to provide target training data. The advantages of the suggested solution are pointed out. The results of preliminary research are presented for several travel routes and neural net architectures.
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