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This high-resolution data permits the measurement of precisely defined instantaneous surrogate safety measures identifying collision risk. One such measure is time-to-collision (TTC) which measures the time remaining at any given instant to some collision point in the future defined by a collision course with another road user. This measure is useful as it provides the remaining time road users have to react to and avoid potential collisions. Higher TTCs are generally considered safer, though the precise link has yet to be defined. However, this measure relies on motion prediction hypotheses to identify collision courses. The traditional approach is to use constant velocity projection (situations in which road users fail to correct their course), which is the motion prediction method most frequently used, without a justification. This approach does not natively provide a collision course probability, and it will not be suitable in situations where observed trajectories do no include constant velocity displacements: for example, turning lanes in an intersection and movements in a roundabout.  More advanced collision course modelling efforts are underway, including motion patterns which represent naturalistic (expected) driving behaviour learnt from the same data set. This procedure provides several potential collision points and their probability as a function of both the characteristics of the specific site and the behaviour of the road users. The motion patterns, or the distribution of trajectories at a site and their probabilities, may be described discretely over time and space \cite{St-Aubin_2014}  or with prototype trajectories. The motion and collision predictions are intensive as they explore, for each pair of road users, at each point in time, all future positions in time and space (typically subject to a time horizon). Furthermore, interaction complexity and exposure increases exponentially with increases in traffic flow, as the number of potential interactions is proportionnal to the square of the number of road users simultaneously going through the intersection. Over the course of one day, a typical intersection can experience between 100 thousands and 100 millions of these instantaneous interactions, depending on the intersection complexity.