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Simulative Workload Analysis of Police Forces
Cors, Tobias; Hoth, Kai; Tschöke, Martin; u. a. (2020): Simulative Workload Analysis of Police Forces, in: Jan Werner, Niels Biethahn, Reinhard Kolke, u. a. (Hrsg.), Mobility in a Globalised World 2019, Bamberg: University of Bamberg Press, S. 7–15, doi: 10.20378/irb-58522.
Author:
Title of the compilation:
Mobility in a Globalised World 2019
Conference:
9. Mobility in a Globalised World-Konferenz, September 2019 ; Hamburg
Publisher Information:
Year of publication:
2020
Pages:
ISBN:
978-3-86309-731-8
Language:
English
DOI:
Abstract:
This chapter discusses a simulation model for conducting workload analyses of police forces. Due to the high operational heterogeneity and variability, determining reliable profiles for resource utilization and establishing their relationship to response times is a challenging task in and of itself that requires an adequate consideration of several sources of stochastic influence. Prior approaches from police practice mainly consider static ratios (e.g. resources per number of inhabitants or calls for service) in order to estimate capacity demand. Based on an extensive dataset comprising more than two million data points, we derive stochastic process models for all relevant police operations in a major metropolitan area and use a discreteevent simulation to analyse the effects on workloads and capacity utilization of a given fleet of police cars. The simulation model predicts the spatial and temporal occurrence of police operations and dispatches available vehicles from different districts, in order to model resource sharing in emergency response. This provides key insights into the required capacity over time and constitutes a crucial first step for an adequate capacity planning.
GND Keywords: ; ; ; ;
Polizei
Arbeitsbelastung
Kapazitätsplanung
Simulation
Stochastik
Keywords: ; ; ;
Police force planning
stochastic processes
simulation
capacity planning
DDC Classification:
RVK Classification:
Type:
Conferenceobject
Activation date:
May 10, 2023
Permalink
https://fis.uni-bamberg.de/handle/uniba/58522