Exploring Officer Patrol Behaviors Using Automated Vehicle Locator and Body-Worn Camera Data

Funder: National Institute of Justice ($862,804)

Principal Investigator: Eric L. Piza

Co-Principal Investigators: Nathan T. Connealy & Victoria A. Sytsma

Project Overview

This project is a mixed-methods research project that leverages automated vehicle locator (AVL) data and body-worn camera (BWC) video to analyze police patrol activity and police-citizen interactions. We will first operationalize daily patrol officer travel patterns from AVL data, specifically focusing on committed vs. uncommitted time, proactive vs. reactive deployment, driving speed, single vs. multiple-vehicle responses, and stationary vs. in-motion presence. We will then select a stratified random sample of incidents for further analysis through systematic social observation (SSO) of associated BWC video. The SSO will measure the degree to which police officers adhere to principles of procedural justice, deploy de-escalation tactics in contentious citizen encounters, and use their discretion to minimize punitive responses. Data from the AVL and BWC video will further be triangulated with a wide range of KCPD and public data sources to identify contextual factors that are significantly related to a range of police patrol behaviors and response outcomes. This study’s novel methodology provides a blueprint for leveraging AVL and BWC data in support of evidence-based policing and police reform.

Project Publications

• Using Automated Vehicle Locator Data to Classify Discretionary Police Patrol Across Space
• AI vs. Human Transcription: Evaluating Accuracy and Meaning in Police Body-Worn Camera Footage