Unravelling Spatiotemporal Patterns of Everyday Police Patrol in Antwerp

Police patrol distinguishes itself from other routing problems due to the interaction between reactive and proactive patrol. Therefore, it is important to understand the spatiotemporal patterns of police patrol and criminal activity to logistically optimize resource allocation. Moreover, crime deterrent effects of preventative or proactive motor patrol have to be quantified and, to increase its effectiveness, it is of great value to determine the optimal dosage on the street segment level. Police presence and its deterrent effect on crime in time and space influences the optimal spatial deployment of patrol cars. In this research on police patrol, we analyse crime incidents, 911 calls, and GPS data of the Antwerp Local Police Department (ALPD) in Belgium. In 2018, the ALPD registered more than 43,000 crimes and tracked the routes of more than one hundred police vehicles. Successive data cleaning, map matching, and geocoding of the data make it possible to visualize spatiotemporal patterns of crimes, 911 calls, and police patrol. Combining these patterns is a first important step in developing an algorithm for police patrol as well as determining the relationship between police presence and crime prevention.