Traffic Status Evaluations on an Urban Street Section

The paper shows a method of estimating as accurately as possible the state of traffic on an urban street section delimited by applying a multicriterial calculation model for improving the estimation of the level of air quality pollution. The algorithm can be applied to a linear road section for which the travel time is minimal, data recorded for a number of cars stationed at the traffic light during the traffic light cycle of approximately 1 minute (constant value), over a period of 30 days, on sets of values at 30 min ranges for 24/24 h. The method develops a linear algorithm that can be adjusted depending on traffic flow status (crowded or fluidized)using the Kernel normalization function, which can combine both crowded and fluidized traffic (free car flow). The algorithm facilitates the tracking and recording of data from multiple sources to simulate a more accurate local traffic situation, which in turn allows for better estimates of travel time and vehicle emissions on the linear section delimitate of urban street. For optimization of the estimation results, the calculation includes the parameters of the momentary traffic status. Thus, the determination of traffic flow status leads to the setting of speed regime, accuracy of emissions estimation and fuel consumption. These aspects are support in taking operational management decisions to reduce traffic congestion and the negative impact on the environment.