Emission load estimation and modeling in relation to the real input traffic data
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The paper presents a model of the emission load in the vicinity of a monitored road in relation to the real traffic input data. It describes a simple method of the emission load estimating. In Addition to the modeling method itself, the paper describes particular methodologies of the real data conversion and processing. Discussed are traffic intensities of the heavy trucks over 12 tons of weight. The model uses as its input real traffic data files from intelligent traffic systems (ITS) localized by the monitored roads. More specifically, data from selected highway toll gates were used in this work. At the end, particular and final, results are presented in graphs as examples.
[1] Haibo Chen,et al. Predicting Real-Time Roadside CO and $\hbox{NO}_{2}$ Concentrations Using Neural Networks , 2008, IEEE Transactions on Intelligent Transportation Systems.