Advanced OR and AI Methods in Transportation TRAFFIC PARAMETERS ESTIMATION TO PREDICT ROAD SIDE POLLUTANT CONCENTRATIONS USING NEURAL NETWORKS
نویسندگان
چکیده
The analysis aims to evaluate which among traffic parameters (flows, queues length, occupancy degree and travel time) are most important in order to forecast CO and C6H6 concentrations. The study area was identified by Notarbartolo Road and bounded by Libertà Street and Sciuti Street in the urban area of Palermo. In this area, various loop detectors and one pollution monitoring site were located. Traffic data were estimated by SUMO micro-simulator software. Traffic and weather data were used as input variables to predict pollutant concentrations by using neural networks.
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