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

Abstract

This paper proposes a clustering approach to predict the probability of a collision occurring in the proximity of planned road maintenance operations (i.e., work zones). The proposed method is applied to over 54,000 short-term work zones in the state of Maryland and demonstrates an ability to predict work zone collision probabilities. One of the key applications of this work is using the predicted probabilities at the operational level to help allocate highway response teams. To this end, a two-stage stochastic program is used to locate response vehicles on the Maryland highway network in order to minimize expected response times.