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Paul St-Aubin edited Methodology Indicator Time Space.tex
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\subsection{Indicator comparison over time and space}
Indicator distributions are generally gamma-like-shaped across the literature \cite{Ismail_2010} \cite{Autey_2012} \cite{St_Aubin_2013}. Quantifying collision risk based on TTC is the remaining puzzle piece. TTC thresholds have been popular, though are subject to arbitrary selection. One recent approach proposed a shifted gamma-generalised Pareto distribution model \cite{Zheng_2014}. In the meantime, some qualitative analysis is possible in some circumstances, for example with a continuous mass shift of a probability distribution function as demonstrated in Figure~\ref{fig:distro-comparison}. This approach has been tried in some early applications of the methodology, e.g. in \cite{Ismail_2010}, \cite{Autey_2012}, and in \cite{St_Aubin_2013}.
Figure~\ref{fig:distro-comparison} also demonstrates three different TTC distribution aggregation methods as used to represent nearly 3 million TTC observations over the course of one day at a single site: i) all interaction instances (subject to over-smaling by slower road users and longer corridors), ii) minimum value of time series per user pair, or iii) 15th percentile value of time series per user pair. The 15th percentile is a practical solution to ignoring outliers that may be introduced by maxima.