Predicting Work Zone Collision Probabilities via Clustering: Application in Optimal Deployment of Highway Response Teams

Figure 9

Graphical description of the methodology via a trivial example including 2 dimensions, 3 clusters, and 41 data points (i.e., WZs). After clustering historical WZs, for each cluster, we compute the number of WZs with at least one collision over the total number of WZs within the cluster. A newly scheduled WZ is attributed to the cluster with the most similar features. The predicted probability of a collision occurring at this WZ corresponds to the ratio computed for the cluster it was attributed to.

(a) Historical (unclustered) work zones

(b) Clustered WZs and corresponding collision probabilities

(c) Newly scheduled WZ is attributed to the closest cluster