A Model Officer: An Agent-based Model of Policing

Crime is a complex phenomenon, emerging from the interactions of offenders, victims, and their environment, and in particular from the presence or absence of capable guardians. Researchers have historically struggled to understand how police officers create guardianship. This presents a challenge because, in order to understand how to advise the police, researchers must have an understanding of how the current system works. The work presents an agent-based model that simulates the movement of police vehicles, using a record of real calls for service and real levels of police staffing in spatially explicit environments to emulate the demands on the police force. The GPS traces of the simulated officers are compared with real officer movement GPS data in order to assess the quality of the generated movement patterns. The model represents an improvement on existing standards of police simulation, and points the way toward more nuanced understandings of how police officers influence the criminological environment

Filaments of crime: Informing policing via thresholded ridge estimation

Objectives: We introduce a new method for reducing crime in hot spots and across cities through ridge estimation. In doing so, our goal is to explore the application of density ridges to hot spots and patrol optimization, and to contribute to the policing literature in police patrolling and crime reduction strategies. Methods: We make use of the subspace-constrained mean shift algorithm, a recently introduced approach for ridge estimation further developed in cosmology, which we modify and extend for geospatial datasets and hot spot analysis. Our experiments extract density ridges of Part I crime incidents from the City of Chicago during the year 2018 and early 2019 to demonstrate the application to current data. Results: Our results demonstrate nonlinear mode-following ridges in agreement with broader kernel density estimates. Using early 2019 incidents with predictive ridges extracted from 2018 data, we create multi-run confidence intervals and show that our patrol templates cover around 94% of incidents for 0.1-mile envelopes around ridges, quickly rising to near-complete coverage. We also develop and provide researchers, as well as practitioners, with a user-friendly and open-source software for fast geospatial density ridge estimation. Conclusions: We show that ridges following crime report densities can be used to enhance patrolling capabilities. Our empirical tests show the stability of ridges based on past data, offering an accessible way of identifying routes within hot spots instead of patrolling epicenters. We suggest further research into the application and efficacy of density ridges for patrolling.Comment: 17 pages, 3 figure

Modelling Police Community Support Officer Management by Agent-Based Simulation

Complexity theory within public management is becoming a recognised field, but currently without consensus about the contribution it could make to theory and practice. This paper suggests a promising route to engage with management practitioners, in this case within policing by the use of agent-based simulation of a policing team subject to policy changes. Policing has fractal self-similar management structures at all levels. A general methodology is presented to explore the motivational consequences of policies at all levels in these complex multilevel systems as an alternative to 'point-in-time' staff surveys. It is illustrated by the motivation of Police Community Support Officers (PCSOs) at the front line of the police management hierarchy. The computational model is based on qualitative team dynamics data collected using Grounded Theory. This produced ‘behavioural codes’ for aspects of PCSO work, the most prevalent six being taken forward for simulation design: Purpose (feedback on role); Availability of supervision and support; Threat and risk of harm; Relevance to role; Orientation in relation to geographic responsibility; and Lone working (patrolling). The first letter of each phenomena (a vertex) gives the acronym PATROL (a simplex). This greatly facilitated the design and implementation of the simulation and subsequent communication with practitioners. These simplices are highly non-linear in their impact on motivation. We created an interactive computer simulation of the PCSO task execution system, where each task is a combination of simplices called a hypersimplex (a ‘system of systems’). To model motivation and demotivation PATROL simplices are mapped to an ordinal emoticon scale. Combinations of emoticons are mapped into a sequence of pair-wise connected local attractors in order of increasing motivation. PCSO motivation tends to stay in these ‘basins of attraction’ by forces driving it away from adjacent attractors. The boundaries between attractors are characterised by tipping points. Generally, the PCSOs’ motivation stays in the central attractor or above for normal empirically validated settings, based on published job satisfaction survey results. However abnormal situations, such as the sustained absence of sergeant supervision can drive motivation over the tipping points into lower states. Such low motivation has implications for performance, sick leave and retention, and may infect other PCSOs. Modelling PCSO motivation dynamics and computer simulation provide a step towards improved management procedures that avoid unnecessary demotivation. The simulation allows the possible outcome of policies to be explored before they are implemented

State of the Art in Agent-Based Modeling of Urban Crime: An Overview

OBJECTIVES: Agent-based modeling (ABM) is a type of computer simulation that creates a virtual society and allows controlled experimentation. ABM has the potential to be a powerful tool for exploring criminological theory and testing the plausibility of crime prevention interventions when data are unavailable, when they would be unethical to collect, or when policy-makers need an answer quickly. This paper takes stock of the current literature to discuss the potential contributions of ABM, assess current practice, identify shortcomings that threaten the validity of findings using ABM, and to make suggestions regarding the construction and communication of future work using ABM. METHODS: We systematically searched major databases to find all publications using ABM to simulate urban crime patterns and coded publications to quantify the following information: (1) characteristics of the publication, the model and the agents, (2) model purpose, (3) crime type investigated, and (4) interrogation of the model via sensitivity testing and validation. RESULTS: After sifting papers according to our inclusion criteria, we identified and reviewed 45 publications. Models informed by the opportunity theory framework dominated. Most publications lacked detail sufficient to enable replication. Many did not include clear a rationale for modeling choices, parameter selection or calibration. Rarely were parameters calibrated using empirical data. Model validation was limited and inconsistent across papers. CONCLUSIONS: ABM offers significant potential for criminological enquiry. However, at present, the lack of model detail reported in publications makes it difficult to assess where sufficient evidence exists to support—and where gaps limit—the development of models that reflect extant conditions and offender decision-making. For the field to progress, as a minimum, standardized reporting that encourages transparency will be necessary

Transportation in Agent-Based Urban Modelling

As the urban population rapidly increases to the point where most of us will be living in cities by the end of this century, the need to better understand urban areas grows ever more urgent. Urban simulation modelling as a field has developed in response to this need, utilising developing technologies to explore the complex interdependencies, feedbacks, and heterogeneities which characterise and drive processes that link the functions of urban areas to their form. As these models grow more nuanced and powerful, it is important to consider the role of transportation within them. Transportation joins, divides, and structures urban areas, providing a functional definition of the geometry and the economic costs that determine urban processes accordingly. However, it has proved challenging to factor transportation into agent-based models (ABM); past approaches to such modelling have struggled to incorporate information about accessibility, demographics, or time costs in a significant way. ABM have not yet embraced alternative traditions such as that in land use transportation modelling that build on spatial interaction in terms of transport directly, nor have these alternate approaches been disaggregated to the level at which populations are represented as relatively autonomous agents. Where disaggregation of aggregate transport has taken place, it has led to econometric models of individual choice or microsimulaton models of household activity patterns which only superficially embody the key principles of ABM. But the explosion in the availability of movement data in recent years, combined with improvements in modelling technology, is easing this process dramatically. In particular, agent-based modelling as a methodology has grown ever more promising and is now capable of emulating the interplay of urban systems and transportation. Here, we explore the importance of this approach, review how transportation has been factored into or omitted from agent-based models of urban areas, and suggest how it might be handled in future applications. Our approach is to take snapshots of different applications and use these to illustrate how transportation is handled in such models

Optimal patrol routing and scheduling for parking enforcement considering drivers' parking behavior

Logistics costs constitute a considerable proportion of overall daily expenses for many public sectors, among which parking enforcement agencies are some of the most prominent examples. While currently there is little research about the planning of efficient parking enforcement patrol operations, this work presents several models to generate patrol schemes that help parking departments achieve low operational costs and effective enforcement. This thesis considers two levels of problems: i) parking behavior of drivers based on given patrol frequency (but not schedule), and ii) parking enforcement patrol routing and scheduling based on the parking behavior of drivers. Driver determines optimal payment based on the distribution of parking duration, parking prices, citation fines, and patrol frequencies via a newsvendor model. As the intensity of parking enforcement increases, illegal parking is expected to occur less frequently. However, improving parking enforcement sometimes requires more frequent patrols that lead to higher agency costs. In order to find the optimal trade-off point, the problem is further formulated into a Vehicle Routing Problem (VRP). Solving this bi-level optimization problem means that the cost is reduced while anticipated parking offenses are limited to a certain level. We present a traditional discrete mixed-integer programming model, and a continuous approximation model based on the method of continuum approximation. Numerical tests are performed in order to examine the performance of these two models using randomly-generated datasets. Sensitivity analyses show that as parking price or demand increases, or citation fine decreases, more frequent patrols are required to maintain the healthy operation of the parking lots. The results also validate that the method of continuum approximation can offer good estimation of the agency cost for the parking patrol problem with comparatively minimal runtime

INTEROPERABILITY FOR MODELING AND SIMULATION IN MARITIME EXTENDED FRAMEWORK

This thesis reports on the most relevant researches performed during the years of the Ph.D. at the Genova University and within the Simulation Team. The researches have been performed according to M&S well known recognized standards. The studies performed on interoperable simulation cover all the environments of the Extended Maritime Framework, namely Sea Surface, Underwater, Air, Coast & Land, Space and Cyber Space. The applications cover both the civil and defence domain. The aim is to demonstrate the potential of M&S applications for the Extended Maritime Framework, applied to innovative unmanned vehicles as well as to traditional assets, human personnel included. A variety of techniques and methodology have been fruitfully applied in the researches, ranging from interoperable simulation, discrete event simulation, stochastic simulation, artificial intelligence, decision support system and even human behaviour modelling

Modelo matemático para seleção de rotas de patrulhamento escolar: o caso da patrulha escolar de Ponta Grossa

Studies have shown that school violence produces harmful effects on victims and society alike. Police patrols have proved to me the most effective among the main forms of preventing school violence. School police patrols take place using squad cars that serve a network of schools and consist of placing vehicles at network schools for a given period of time (routine patrol). Nevertheless, during routine patrol police vehicles must immediately answer emergency calls at network schools that are not being patrolled at that moment (emergency patrolling). This work proposes a method based on mathematical models to assist the school patrol program in defining the routes for routine patrol and emergency routes. The approach used to solve the problem consisted of graph algorithms. Routine patrol was treated as a model of the Traveling Salesman Problem, and was solved using the Nearest Neighbor Heuristic and Tabu Search metaheuristic. The emergency situation was modeled using the Shortest Path Problem, and emergency routes were determined through the Floyd-Warshall algorithm. A case study was used to demonstrate the application of the method. Results show that the proposed method is effective to treat the problem of route selection for school patrols in cities with shortcomings in technological resources.CAPESEstudos mostram que a violência nas escolas resulta em consequências prejudiciais para as vítimas e para a sociedade. Entre os principais meios de prevenção da violência escolar tem-se o patrulhamento policial como o mais efetivo. O patrulhamento policial escolar é realizado por viaturas policiais que atendem a uma rede de escolas e consiste na manutenção das viaturas em cada escola da rede por um determinado período de tempo (patrulhamento de rotina). Contudo, durante o patrulhamento de rotina, as viaturas devem prestar atendimento imediato a chamadas de emergência em escolas da rede que não estejam sendo patrulhadas naquele momento (patrulhamento emergencial). O presente trabalho propõe um método baseado em modelos matemáticos para auxiliar o programa de patrulha escolar na definição das rotas de patrulhamento de rotina e rotas emergenciais. A abordagem aplicada para resolver o problema foi a de algoritmos de grafos. O patrulhamento de rotina foi por meio do Problema do caixeiro viajante e solucionado por meio da heurística do vizinho mais próximo e da meta-heurística de Busca tabu. A situação de emergência foi modelada utilizando o Caminho mais curto e as rotas emergenciais foram determinadas por meio do algoritmo de Floyd-Warshall. Um estudo de caso em uma rede de escolas foi utilizado para demonstrar a utilização do método. Os resultados mostram que o método proposto é efetivo para tratar o problema de seleção de rotas de patrulhamento escolar em cidades com restrições de recursos tecnológicos