Modeling Pollutant Concentration And Environment Loss Analysis Of Urban Traffic

Based on the theories of traffic parameters detection and modeling pollutant concentration, the paper discusses on estimation of traffic pollutant concentration along urban roadside with the technique of artificial neural network. The purpose of this study is to not only provide a numerical reference to the construction of varies control measures, but also provide a theoretical base on environment management and transportation planning.In Traffic Parameters Detection, Firstly, the digitizing videos of the traffic flow are saved in the computer, and then color scale images are transformed into gray ones. Next, one image is selected, in which there is no moving objects, as the background with three virtual loops set on it. Thirdly, the background subtraction method is used to facilitate detection of the vehicles passing through the virtual loops and automatically calculate the vehicle speed.In Modeling pollutant concentration, this study analyzes the multiple factors that affect the pollutant concentration first, and then establishes the model structure using the ANN technique. Secondly, collect data such as: traffic flow, vehicle speed and flow composition, from Traffic Parameters Detection model to train the ANN model. At last, the pollutant concentrations are gain.In Environment Loss, based on the detected and estimated data we use the atmospheric diffusion equation to calculate the economic loss by the traffic pollutant. Finally, some suggestions is made for environment management and transportation planning.