Generating crime data using agent-based simulation

•We propose an agent-based model to simulate crime in public places.•The proposed model has been applied to Santiago (Chile) and Vancouver (Canada) and provided reliable results.•The proposed model can be used to test patrolling strategies as well as predictive crime models.

Policing plays an important role in combating street crime. Though policing actions have a dissuasive impact on criminal behavior, they can also have unpredictable and even undesirable effects such as displacement of crime hot-spots. This paper presents an agent-based simulation model that generates artificial street-crime data which can be used to test different policing strategies in a virtual environment. The model can thus evaluate the strategies’ effectiveness and collateral effects before putting them into practice and provide support for the policing decision-making process. Based on this model, a crime simulator was implemented in Repast Simphony and a series of test simulations on fictitious and real cities were carried out. The proposed formulation was successfully validated, confirming its potential as a powerful tool for the study of street crime.