Scheduling resources in a mobile photo enforcement program

Abstract

This paper presents a model for scheduling resources in a mobile photo enforcement (MPE) program. An MPE program deploys operators driving vehicles equipped with radar and photo equipment to roadway locations where speeding and collision problems are significant. We developed a binary integer linear programming model to allocate MPE shifts over the course of a month to selected enforcement locations. These locations are pre-determined from a set of city neighborhoods chosen for enforcement through a prior multi-objective programming step. A major feature of the scheduling model is to observe the time halo effects of enforcement; our optimization model minimizes visits to an enforcement location over consecutive shifts. The model was applied to data obtained from the currently operating MPE program in Edmonton, Canada. Based on the resource allocation in neighborhoods determined in the previous stage, this scheduling model produces a scheduling plan that allocates resources to individual enforcement sites within each city neighborhood during a month. The purpose of this scheduling model, in combination with the first stage neighborhood allocation model, is to provide enforcement agencies with a tool to systematically and transparently assign limited resources in an efficient manner, providing greater efficacy in achieving program-level objectives such as reducing speeding, reducing collisions, and providing enforcement presence in areas with many vulnerable pedestrians (i.e. school zones).