deletions | additions       diff --git a/Results TTC.tex b/Results TTC.tex  index 0884fa1..a9369f0 100644  --- a/Results TTC.tex  +++ b/Results TTC.tex 
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\subsection{Disaggregated Speed Regression}  To better manage results due to the number of variables, k-means clustering is employed on all of the variables. Several clusters were performed using between three and 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 independent for the most part, wemay  find that different clusters offer different explanatory power for each dependant variable. 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. A selection ofVariable of variable  statistics are presented in Table~\ref{tab:cluster_speed_stats}. \begin{table}  \caption{K-means cluster profile for speed regression} 
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\end{tabular}  \end{table}  \begin{table}[h]  \caption{K-means cluster select statistics for speed regression}  \label{tab:cluster_speed_stats} 
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& 1 & 1 & 1 & 92.5 & 24.4 & 233 & 0.45 & Industrial & Regional Highway \\  & 1 & 1 & 1 & 105.0 & 26.0 & 443 & 0.75 & & \\ \hline  c3\_s & 1 & 0 & 1 & 45.0 & 17.5 & 67 & 0.12 & & \\  & 1.15 & 1.15 & 1 & 91.9 & 22.9 & 330 & 0.69 & Residential &Regional  Highway Ramps & Arterials  \\ & 2 & 2 & 1 & 145.0 & 27.5 & 583 & 0.98 & & \\ \hline  c4\_s & 1 & 1 & 1 & 90.0 & 13.5 & 45 & 0.00 & & \\  & 1 & 1 & 1.17 & 96.7 & 16.8 & 218 & 0.51 & Residential & Collector \\ 
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\end{tabular}  \end{table}  This regression  model offers relatively good explanatory power. The coefficients and statistical test results are provided in Table~\ref{tab:re_speed_regression}  All but cluster c6\_s (2 lane arterials)  provides adequate moderate  to very strong statistical significance. The coefficients Cluster c1\_s (single-lane residential arterial) is associated with the lowest speeds. From the cluster characteristics, we gather that high  and statistical test results are provided moderate flow ratios have an important effect of increasing speed. Unsurprisingly, the highest speeds attributed to regional highway roundabouts. Large-diameter, 2-lane, roundabout-converted traffic circles had the poorest speed results, probably because the approach angle remained tangential to the circle instead of the usual mostly orthogonal approach of smaller roundabouts. Interestingly, roundabouts situated  in Table~\ref{tab:re_speed_regression}. residential neighbourhoods on collector streets (cluster c4\_s) were associated with higher speeds than highway ramps (cluster c3\_s), despite the smaller size. This may be attributed to significantly lower flows and thus fewer conflicts.  \begin{table}  \caption{Random effects speed regression} 
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\begin{tabular}{llll}  \textbf{Cluster} & \textbf{Description} & \textbf{Group size} & \textbf{Observations} \\ \hline  c1\_t & Small single and double lane residential collectors & 11 & 4,200 \\  c2\_t & Single lane Single-lane  regional highways and arterials with70-90  speed limits of 70-90 km/h  and mostly polarised flow ratios & 16 & 26,243 \\ c3\_t & 2 lane 2-lane  arterials with very high flow ratios & 5 & 13,307 \\ c4\_t & Hybrid lane 1->2 2->1 arterials with very low flow ratios & 3 & 4,809 \\  c5\_t & Traffic circle converted to roundabout (2 lanes, extremely large diameters, tangential approach angle) & 4 & 10,295 \\  c6\_t & Single-lane regional highway with large-angle quadrants 140 degrees (140 degrees)  and mixed flow ratios & 2 & 2,235 \\ ~ & ~ & ~ & ~ \\  ~ & ~ & ~ & ~ \\  \end{tabular} 
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\end{table}  This regression model offers moderately good explanatory power.  The coefficients and statistical test results are provided in Table~\ref{tab:re_TTC_regression} Table~\ref{tab:re_TTC_regression}. Clusters c5\_s and c6\_s are not statistically significant. Small, residential, local roundabouts are associated with the second-worst (lowest) TTC performance, after traffic circle conversions which were noted for their issues with higher speed. The best performing group, in terms of safety appears to be 2-lane arterials with excessively high flow ratios (c3\_s). This is probably explained due to the extremely low amount of interactions generated at the weaving zone---instead these results are probably governed by TTC measures generated from lane changing manoeuvres. Clusters c4\_t (Hybrid lane arrangement arterials with very low flow ratios) and cluster c2\_t (single-lane regional highways and arterials with speed limits and polarised flow ratios) offer the next best TTC performance. The most striking aspect in this model is that higher TTC appears to be associated with flow ratio extremes where as lower TTCs (more dangerous) appear to be associated with highly mixed flow ratios. This might be explained by the increase in the generation of complex merging manoeuvres when flows are equivalent on both the roundabout and it's approach.  \begin{table}  \caption{Random effects TTC regression} regression (higher is better)}  \label{tab:re_TTC_regression}  \begin{tabular}{lll}  Cluster & Coefficient & p-value \\ \hline 
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\subsection{TTC Distributions by Cluster}