Using Automated Vehicle Locator Data to Classify Committed and Uncommitted Patrol Assignments across Space and Time

• In Event: Improving the Tracking of Police Officer Activity Through Novel Technology Applications (Sponsored by Division of Policing)

Abstract

In the current socio-political climate, policing has come to face a resource challenge characterized by budget constraints, personnel turnover, and staffing shortages. Despite these operational deficits, police are still expected to remain proactive in their efforts to prevent crime and promote public safety. Many well-known and empirical policing strategies, including hot spots policing, situational crime prevention, and community policing hinge on the assumption that patrol officers have enough uncommitted time on a shift to have an impact on crime or engage citizens pro-socially. Using automated vehicle locator (AVL) data in Manchester, NH, the present study considers the temporal and spatial distribution of committed and uncommitted time across daily patrol officer shifts. The results will examine potential differences in patrol assignment across space, indicate the proportion of shift time that is uncommitted, and quantify the expected shift ratio of uncommitted time. The present study is positioned to make a meaningful contribution to the literature by extending the scope of how AVL data is used to understand policing and by informing upon the practicality of a litany of routine policing strategies.

Authors

• Nathan Connealy, University of Tampa

• Eric Piza, Northeastern University

• Victoria A. Sytsma, Queen's University

• Savannah Reid, Northeastern University

• Christianna Palermo, Northeastern University