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In fact, the researchers say, in modeling the traffic flow mathematically, the pushing -- what the researchers call "inhibitory interactions" -- is critical to maintaining optimum flow.
We consider both the Poisson and Pareto distributions for modeling the traffic.
This estimated vehicle density can be related to the vehicle density, acquired by modeling the traffic flow for a road segment.
In the remaining part of this section, we study the benefit of using aggregated versus more detailed input data when modeling the traffic conditions in different time slices.
One example of such an application was proposed by Nanni et al., who create the OD-matrix of Ivory Coast and then assign this matrix to the road network [122] to produce a map (see Figure 22) modeling the traffic of the main roads of the country, showing estimated traffic flows.
The first block in Figure 1 implements a multiresolution analysis (MRA), using the stationary wavelet transform (SWT), providing two types of wavelet coefficients: approximation coefficients used for modeling the traffic overall tendency and detail coefficients used for modeling the variability around the overall tendency of traffic.
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Sulfur hexafluoride was used as tracer gas to model the traffic emissions.
We refer stochastic models and related parameters in[19, 20] to model the traffic types as shown in Table1.
In [2] the authors proposed to model the traffic evolution in an IP backbone network at large time scales.
The developed simulator is intended to model the traffic capacity of the system, and thus to model the system at the so-called call (flow or connection) level [38].
Forecasting and modeling the network traffic can help optimize it further.
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