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.

Highlights

  • Patrolling is defined as “the act of walking or travelling around an area, at regular intervals, in order to protect or supervise it” (Abate, 1997, p 578)

  • We propose a set of guidelines for an effective police patrol routing strategy and the relevant evaluation measures, which are based on the characteristics and challenges of practical police patrol

  • WBAPS and based Patrolling Strategy (BAPS) have lower global average idleness (GAI) and weighted global average idleness (WGAI) compared with Cyclic Patrolling Strategy (CCPS)

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Summary

Introduction

Patrolling is defined as “the act of walking or travelling around an area, at regular intervals, in order to protect or supervise it” (Abate, 1997, p 578). Tsai et al (2010) derived a strategy for police resource allocation based on modelling the interactions between police and terrorists as an attacker-defender Stackelberg game, where a player always predicts his opponent's behaviour and chooses the best response These strategies can effectively prevent crime in crime hotspots, but only on the basis of a substantial knowledge of crime mechanisms in the area, and it is difficult to generalise these strategies to guiding police patrol in large areas and preventing multiple types of crimes. We propose a set of guidelines for an effective police patrol routing strategy and the relevant evaluation measures, which are based on the characteristics and challenges of practical police patrol.

Guidelines and evaluation measures
Efficiency
Flexibility
Scalability
Unpredictability
An online Bayesian ant-based patrolling strategy
Robustness
Transferring guidelines to strategy
Agent-based modelling of cooperative police patrols
Findings
Conclusions and future work

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