deletions | additions       diff --git a/Methodology Complimentary Data.tex b/Methodology Complimentary Data.tex  index 85f2c28..fcc7b4a 100644  --- a/Methodology Complimentary Data.tex  +++ b/Methodology Complimentary Data.tex 
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\subsubsection{Network Topology}  Once trajectories are clustered, a network topology is constructed in order to be able to inteligently propogate future possible positions of moving objects through the network. In simple networks (i.e. 2 two  alignments), these movements are implicitly defined simply by observing lane change ratios, but in more complex networks, such as the network shown in \ref{fig:complex-network}, movements may involve multiple lane changes and therefore may require a more general approach. A recursive tree model is employed. Alignment extremities are linked to other nearby alignments, creating diverging or converging branches, as are momentarily adjacent alignments. Alignments which run in parralel over a distance of more than 15 metres are instead grouped into corridors over which lane changes may occur. This creates a series of links and nodes with implicit direction which can be searched to determine all possible future positions of a moving object inside of this network. This serves to reduce calculation times of spatial relationships between objects (triage) and provides more inteligent interpretation of the spatial relationships.