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In this paper, after analyzing different road features and road models, the road extraction methods were classified into the classification-based methods, knowledge-based methods, mathematical morphology, active contour model, and dynamic programming.
As mentioned earlier, in CA models, the road is represented by a lattice of uniformly sized cells and the size of cells affects the computational time and accuracy of the model.
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Well, I'm going to model the road system using a directed graph, a digraph.
Two different power spectral densities are considered for modelling the road irregularity.
We explicitly model the road congestion by formulating each route as a queue where the travel time is an increasing function of the state.
In the public regulatory model, the road toll location and charge level are simultaneously optimized together with the bus service fare and frequency.
Thus, in order to control noise sound level in urban areas, it is very important to develop methods for modelling the road traffic noise.
We model the road network as an undirected graph, where each node locating in a two-dimensional space represents a road intersection or a Points of Interest (POI), and each edge with weight represents a road segment.
With this model, the road pricing mechanism makes each driver internalize the costs it imposes to others and to the road network when acting greedily.
However, since we exploit simple methods for the sake of real time application, we modelled the road lines with simple lines.
Furthermore, in this model, the road transportation technologies are defined referring to both different fuel consumption and the national emission standards.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com