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\subsection{Disaggregated Speed Regression}  To better manage results due to the number of variables, kmeans clustering is employed. Several clusters were performed using between 3 three  and 6 six  centroids to find a suitable model that i) produces the most meaningful and interpretable clusters, ii) produces a random effects regression model with explanatory power, and iii) where p-values still remain relatively significant. However, because we know the different indicators are statistically independant for the most part, we may find that different clusters offer different explanatory power. Table~\ref{tab:cluster_speed_profile} lists the distribution of observations (at the site level and at the disaggregated level) for the clusters used to model speed and offers a short profile for each. Variable statstics are presented in TABLE. \begin{table}  \caption{K-means cluster profile for speed regression}