Chen, Huanfa;
Gao, Xiaowei;
Li, Huanhuan;
Yang, Zaili;
(2024)
A framework for the optimal deployment of police drones based on street-level crime risk.
Applied Geography
, 162
, Article 103178. 10.1016/j.apgeog.2023.103178.
(In press).
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Abstract
Drones are increasingly adopted for policing in many countries, as they can aid police officers to detect hazards and respond to incidents with timely and low-cost services. However, the planning and deployment of police drones are subject to several challenges, including the proper distance metric for drone flying and the risk-based location optimisation of drone base stations. This study proposes a new framework that enables the optimal deployment of police drones to address crime risk issues on urban street networks. This risk-based decision framework takes into account three potential distance metrics that regulate and shape the flying routes of drones, which in turn affects the optimal location of drone base stations. In addition, this framework takes into account the major risk constraints of flying drones in urban areas, including domestic privacy and elevation. The proposed risk-based decision framework is validated using the real case study of Liverpool with historical crime data and street network layouts. The findings contribute to the operations and management of police drones in urban areas and shift the paradigm of policing drones towards a risk-based regime.
Type: | Article |
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Title: | A framework for the optimal deployment of police drones based on street-level crime risk |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1016/j.apgeog.2023.103178 |
Publisher version: | http://dx.doi.org/10.1016/j.apgeog.2023.103178 |
Language: | English |
Additional information: | © 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Police drones, Location selection, Risk-based decision framework, Risk-based optimisation, Crime risk |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng |
URI: | https://discovery.ucl.ac.uk/id/eprint/10184652 |
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