Analyzing an offender's journey to crime: A criminal movement model (CriMM)

Originally appeared in the 2011 European Intelligence and Security Informatics Conference (12-14 September 2011, Athens, Greece). In the current study we develop a Criminal Movement Model (CriMM) to investigate the relationship between simulated travel routes of offenders along the physical road network and the actual locations of their crimes in the same geographic space. With knowledge of offenders' home locations and the locations of major attractors, we are able to model the routes that offenders are likely to take when travelling from their home to an attractor by employing variations of Dijkstra's shortest path algorithm. With these routes plotted, we then compare them to the locations of crimes committed by the same offenders. This model was applied to five attractor locations within the Greater Vancouver Regional District (GVRD) in the province of British Columbia, Canada. Information about offenders in these cities was obtained from five years worth of real police data. After performing a small-scale analysis for each offender to investigate how far off their shortest path they go to commit crimes, we found that a high percentage of crimes were located along the paths taken by offenders in the simulations. Aggregate analysis was also performed to observe travel patterns in different areas of the cities and how they relate to the amount of crime in each neighbourhood. The results are discussed in relation to both theory and potential policy implications.Peer reviewedFnal article publishedCrime attractorshortest pathstreet segmentroad networkjourney to crim