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Enhancing public safety through integrated UAV and police patrols

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  • Yan, Shangyao
  • Hsieh, Tsung-Hsun
  • Lai, Yu-Chien

Abstract

The police departments in Taiwan have been facing a problem in recent years due to the shortage and aging of the police force. The government and research institutes have developed unmanned aerial vehicles (UAVs) with higher endurance, combined with advanced key technologies, to support police patrols under the concept of the “Aerial Police Vehicle”. This development aims to reduce the workload of the police and make it possible to conduct police patrols in the future by using a combination of police vehicles and UAVs. Given the characteristics of police vehicles and UAVs, this study adopts the time-space network technique, incorporates relevant operational constraints, and adopts the objective of maximizing crime coverage rates to develop the routing and scheduling model for combined UAV-police vehicle patrols. Additionally, this study proposes a heuristic algorithm that utilizes a decomposition technique of patrol resources to efficiently solve this complex problem. The performance of the proposed algorithm was evaluated using a case study created from practical data from a police department in Taiwan, demonstrating that for a large-scale problem with 9 police stations and 91 patrol points, the proposed algorithm achieved a solution with an objective value of 906 for the maximized cumulative crime coverage rate in approximately 884 s, while a commercial solver (CPLEX) failed to find a feasible solution within a time limit of 28,800 s. The recommendations based on the sensitivity and scenario analysis results can be used as a reference for decision-makers to gradually replace police vehicles with UAVs in the future.

Suggested Citation

  • Yan, Shangyao & Hsieh, Tsung-Hsun & Lai, Yu-Chien, 2025. "Enhancing public safety through integrated UAV and police patrols," Socio-Economic Planning Sciences, Elsevier, vol. 102(C).
    • Handle: RePEc:eee:soceps:v:102:y:2025:i:c:s0038012125001831
    DOI: 10.1016/j.seps.2025.102334
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    References listed on IDEAS

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