Developing an online cooperative police patrol routing strategy

Authored by Sarah Wise, Tao Cheng, Huanfa Chen

Date Published: 2017

DOI: 10.1016/j.compenvurbsys.2016.10.013

Sponsors: United Kingdom Engineering and Physical Sciences Research Council (EPSRC)

Platforms: MASON

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

A cooperative routing strategy for daily operations is necessary to maintain the effects of hotspot policing and to reduce crime and disorder. Existing robot patrol routing strategies are not suitable, as they omit the peculiarities and challenges of daily police patrol including minimising the average time lag between two consecutive visits to hotspots, as well as coordinating multiple patrollers and imparting unpredictability to patrol routes. In this research, we propose a set of guidelines for patrol routing strategies to meet the challenges of police patrol. Following these guidelines, we develop an innovative heuristic-based and Bayesian-inspired real-time strategy for cooperative routing police patrols. Using two real-world cases and a benchmark patrol strategy, an online agent-based simulation has been implemented to testify the efficiency, flexibility, scalability, unpredictability, and robustness of the proposed strategy and the usability of the proposed guidelines. (C) 2016 The Authors. Published by Elsevier Ltd.

Tags

Agent-based modelling hotspots Police patrols Multi-agent patrol routing Bayesian-based decision making Ant colony algorithm