The Multi-agent Simulation-based Framework for Optimization of Detectors Layout in Public Crowded Places

AbstractIn this work the framework for detectors layout optimization based on a multi-agent simulation is proposed. Its main intention is to provide a decision support team with a tool for automatic design of social threat detection systems for public crowded places. Containing a number of distributed detectors, this system performs detection and an identification of threat carriers. The generic model of detector used in the framework allows to consider detection of various types of threats, e.g. infections, explosives, drugs, radiation. The underlying agent-based models provide data on social mobility, which is used along with a probability based quality assessment model within the optimization process. The implemented multi-criteria optimization scheme is based on a genetic algorithm. For experimental study the framework has been applied in order to get the optimal detectors’ layout in Pulkovo airport

DEVELOPMENT OF A MIXED-FLOW OPTIMIZATION SYSTEM FOR EMERGENCY EVACUATION IN URBAN NETWORKS

In most metropolitan areas, an emergency evacuation may demand a potentially large number of evacuees to use transit systems or to walk over some distance to access their passenger cars. In the process of approaching designated pick-up points for evacuation, the massive number of pedestrians often incurs tremendous burden to vehicles in the roadway network. Hence, one critical issue in a multi-modal evacuation planning is the effective coordination of the vehicle and pedestrian flows by considering their complex interactions. The purpose of this research is to develop an integrated system that is capable of generating the optimal evacuation plan and reflecting the real-world network traffic conditions caused by the conflicts of these two types of flows. The first part of this research is an integer programming model designed to optimize the control plans for massive mixed pedestrian-vehicle flows within the evacuation zone. The proposed model, integrating the pedestrian and vehicle networks, can effectively account for their potential conflicts during the evacuation. The model can generate the optimal routing strategies to guide evacuees moving toward either their pick-up locations or parking areas and can also produce a responsive plan to accommodate the massive pedestrian movements. The second part of this research is a mixed-flow simulation tool that can capture the conflicts between pedestrians, between vehicles, and between pedestrians and vehicles in an evacuation network. The core logic of this simulation model is the Mixed-Cellular Automata (MCA) concept, which, with some embedded components, offers a realistic mechanism to reflect the competing and conflicting interactions between vehicle and pedestrian flows. This study is expected to yield the following contributions * Design of an effective framework for planning a multi-modal evacuation within metropolitan areas; * Development of an integrated mixed-flow optimization model that can overcome various modeling and computing difficulties in capturing the mixed-flow dynamics in urban network evacuation; * Construction and calibration of a new mixed-flow simulation model, based on the Cellular Automaton concept, to reflect various conflicting patterns between vehicle and pedestrian flows in an evacuation network

OPTIMIZATION OF TERMINAL LAYOUTS: AN ANALYTICAL AND SIMULATIVE APPROACH BASED ON GENETIC ALGORITHMS

2012/2013Every day millions of pedestrian move with different needs and objectives through spaces each of them with its functional specifications. An accurate design or revisiting of transport terminals, as for example railway stations, underway stations, airports, as well as complex buildings, open spaces and a deep analysis of public events with relevant pedestrian flows, would improve its usability at users benefit. To reach this goal is necessary a careful integration among architecture, engineering needs and transport disciplines, that, starting from the study of users behavior and pedestrian dynamics, provides the fundamental elements to be considered during design stage to ensure a major level of service. In literature nothing much is known about the optimal dimension of pedestrian transportation terminals. The aim of this study is to develop a methodology to size the functional terminal layouts, by the integration of analytical and simulative models submitted to generic algorithms, taking into account the dynamics and flows generated inside the terminals. In order to obviate the lack of requisite data for models calibration, validation and verification, as well as testing the process developed, an algorithm for data acquisition has been elaborated. It has a dedicated graphic interface, which allows to reveal the pedestrian dynamics and consequently to generate database; with these data is possible to obtain statistical and behavioral indicators about pedestrians detected. The use of analytical models, both to define the sizing of facilities inside the terminals and to model the user behavior during their paths, allows to define an objective function able to represent the performances of the terminal functional layout. Defined the dimensional ranges of each functional element inside the layout according a specific Level of Service, performed a design of experiments methodology and applied genetic algorithms to minimize the objective function, it is possible to obtain a set of optimal solutions for the terminal configuration sizing, in coherence with flows and dynamics generated inside the terminals itself. A further simulative approach, based on the application of the social force algorithm, allows, through quantitative and qualitative parameters, to identify the best solution(s) inside the domain previously identified with genetic algorithm application. Starting from the motivation that inspired this work, analyzed the existing literature and the main methods for data acquisition, it will be introduced the algorithm for the automatic acquisition of data and pedestrian database generation. The application of this tool will be illustrated in order to manifest the potentiality of the instrument same. Subsequently introduced the tool developed for the definition of the characteristic elements sizing and the model chosen for the correct estimation of pedestrian travel times, it will be explored the structure of the objective function aimed to identify the right trade-off between infrastructure and pedestrian costs. Finally, the application of genetic algorithms, resulting in the identification of Pareto front, generates the domain of optimal solutions to sift through the simulation approach. The developed methodology reveals a flexible and simple instruments, but, at the same time, accurate in the resolution of the problems for which has been structured. The potential of the developed methodology is highlighted in the course of the work thanks to a case of study.Ogni giorno milioni di pedoni si muovono con esigenze ed obbiettivi diversi in contesti differenti, ognuno dei quali con le sue caratteristiche tecniche funzionali. Un’attenta progettazione o rivisitazione dei terminali di trasporto, quali stazioni ferroviarie, metropolitane, aeroporti, così come degli edifici complessi, degli spazi aperti ed una corretta disamina degli eventi pubblici con flussi pedonali rilevanti, consentirebbe di migliorarne la fruibilità a beneficio dell’utenza. Per raggiungere tale obiettivo risulta necessaria un’attenta integrazione tra esigenze architettoniche, ingegneristiche e le discipline trasportistiche, le quali, partendo dallo studio comportamentale degli utenti e dalle dinamiche pedonali, forniscano gli elementi fondamentali da tenersi in considerazione nella fase di progettazione per garantire un maggiore livello di servizio. Riscontrata in letteratura una carenza di approcci finalizzata alla determinazione del miglior layout funzionale dei terminali, attraverso l’integrazione di modelli analitici e simulativi sottoposti ad algoritmi genetici, è stata sviluppata una metodologia che, coerentemente con le dinamiche e i flussi che all’interno dei terminali stessi si generano, mirasse al dimensionamento ottimo dei terminali di trasporto pedonale. Per ovviare alla mancanza di dati necessari per i processi di calibrazione, validazione e verifica dei modelli così come per testare il metodo sviluppato è stato innanzitutto elaborato un algoritmo per l’acquisizione di dati, con interfaccia grafica dedicata, che consente di rilevare le dinamiche pedonali, generare database e conseguentemente ricavare dati statistici e comportamentali dei pedoni. L’utilizzo di modelli analitici, sia per l’identificazione dei range dimensionali degli elementi caratteristici presenti all’interno dei terminali che per la modellizzazione del comportamento degli utenti, permette di definire una funzione obbiettivo che rappresenti le performances dei layout funzionali dei terminali. Attraverso design of experiments calibrati sui range dimensionali dei singoli elementi funzionali presenti all’interno dei terminali e la successiva applicazione degli algoritmi genetici finalizzati alla minimizzazione della funzione obiettivo, è possibile definire un insieme di soluzioni ottime per il dimensionamento dei terminali, in coerenza con i flussi e le dinamiche che in esso si generano. Un’ulteriore approccio simulativo, basato sull’applicazione dell’algoritmo delle forze sociali, consente, attraverso la valutazione di parametri quantitativi e qualitativi, di identificare la/e miglior soluzione/i all’interno del dominio di soluzioni precedentemente identificate con l’applicazione degli algoritmi genetici. A partire dall’esplicitazione delle motivazioni che hanno alimentato questo lavoro, analizzata la letteratura esistente e le principali metodologie per l’acquisizione dati, verrà introdotto l’algoritmo per l’acquisizione automatica dei dati pedonali e la generazione di database contenenti i profili degli utenti rilevati. A seguire troverà spazio l’applicazione di questo strumento per manifestarne le potenzialità. Successivamente, introdotto il tool sviluppato per la definizione dei range dimensionali degli elementi caratteristici e il modello scelto per la corretta stima dei tempi di percorrenza pedonali, verrà esplorata la strutturazione della funzione obiettivo finalizzata alla ricerca del giusto trade off tra costi infrastrutturali e pedonali. Infine, l’applicazione degli algoritmi genetici, risultanti nell’identificazione del fronte paretiano, genererà il dominio di soluzioni ottime da vagliare attraverso l’approccio simulativo. La metodologia sviluppata si è rivelata uno strumento flessibile ed agevole, ma, allo stesso tempo, puntuale nel risolvere i problemi per cui è stata ideata. Le potenzialità della metodologia sviluppata vengono messe in risalto nel corso dell’elaborato grazie ad un caso di studio condotto.XXVI Ciclo198

A Semi-Automated Technique for Transcribing Accurate Crowd Motions

We present a novel technique for transcribing crowds in video scenes that allows extracting the positions of moving objects in video frames. The technique can be used as a more precise alternative to image processing methods, such as background-removal or automated pedestrian detection based on feature extraction and classification. By manually projecting pedestrian actors on a two-dimensional plane and translating screen coordinates to absolute real-world positions using the cross ratio, we provide highly accurate and complete results at the cost of increased processing time. We are able to completely avoid most errors found in other automated annotation techniques, resulting from sources such as noise, occlusion, shadows, view angle or the density of pedestrians. It is further possible to process scenes that are difficult or impossible to transcribe by automated image processing methods, such as low-contrast or low-light environments. We validate our model by comparing it to the results of both background-removal and feature extraction and classification in a variety of scenes

Objective Validation of Airport Terminal Architecture using Agent-based Simulations

This thesis explores how airport terminal architecture is tested before it is built. The purpose of testing is to make sure an architectural layout aligns with the rest of the airport’s systems. The design of a terminal is a long and expensive process that must accommodate tens of thousands of passengers every hour, the movement of logistics, and control of security. Evaluating spaces for that many people can be difficult to measure, which can result in architects relying on their intuition and experience to judge the impact of a layout for daily operations without objective validation. It is not practical for designers to build a complete airport to see how it works and make renovations after finding aspects that have poor performance. As a result, testing airports requires using mathematical models and simulations to validate how well different systems work together. Designers try to validate architectural layouts in airport terminals by using crowd simulations to approximate passenger behaviour. Existing research in civil engineering and computer science has shown how mathematical models can predict patterns of human activity in the built environment on a large scale. However, these simulations have primarily focused on either modelling passengers as a process flow or people in emergency building evacuation. As a result, existing agent navigation does not consider how passengers use the surrounding architecture for decision-making during daily airport interactions. When passengers enter a terminal for the first time, they can be unaware of what they need to do or how to get there. Instead, passengers rely on using their perception of the environment (the architecture) to inform them what to do. However, there currently are no methods that incorporate architectural perception to validate a building layout in these conditions. This thesis develops an agent-based simulation to validate how well architectural layouts align with the daily operations of an airport terminal. It quantifies the value of a spatial arrangement as a function of people’s interactions in a given space. The model approximates human behaviour based on statistics from existing crowd simulations. It uses spatial analysis, like the isovist and graph theory, for agent navigation and measuring architectural conditions. The proposal incorporates agent perception to provide feedback between people’s decision-making and the influence of the surrounding space. The thesis calculates architectural value using normalized passenger priorities based on typical processing and non-processing airport domains. The success of a terminal layout is dependent on the agent’s ability to complete airport processing and fulfill their priorities. The final value of an architectural layout is determined using statistical methods to provide a probability distribution of likely values. The proposed agent simulation and mathematical models are built using Unity software, which is used to perform several simulation tests in this thesis. Basic functional components of the simulation are validated using existing crowd modelling standards. Tests are also performed to illustrate how different agent perception and priorities influence the value of architectural spaces. Monte Carlo simulations are created for simple terminal layouts to illustrate how changing the floor plan of a security area affects the architectural value for departing passengers. Finally, the architectural values of two real airport terminals are compared against an established passenger experience survey in a basic simulation model. The results of the testing shows that the agent simulation can differentiate between different architectural conditions, within reason, depending on the passengers’ priorities

People detection and tracking using a network of low-cost depth cameras

Automaattinen ihmisten havainnointi on jo laajalti käytetty teknologia, jolla on sovelluksia esimerkiksi kaupan ja turvallisuuden aloilla. Tämän diplomityön tarkoituksena on suunnitella yleiskäyttöinen järjestelmä ihmisten havainnointiin sisätiloissa. Tässä työssä ensin esitetään kirjallisuudesta löytyvät ratkaisut ihmisten havainnointiin, seurantaan ja tunnistamiseen. Painopiste on syvyyskuvaa hyödyntävissä havaitsemismenetelmissä. Lisäksi esittellään kehitetty älykkäiden syvyyskameroiden verkko. Havainnointitarkkuutta kokeillaan neljällä kuvasarjalla, jotka sisältävät yli 20 000 syvyyskuvaa. Tulokset ovat lupaavia ja näyttävät, että yksinkertaiset ja laskennallisesti kevyet ratkaisut sopivat hyvin käytännön sovelluksiin.Automatic people detection is a widely adopted technology that has applications in retail stores, crowd management and surveillance. The goal of this work is to create a general purpose people detection framework. First, studies on people detection, tracking and re-identification are reviewed. The emphasis is on people detection from depth images. Furthermore, an approach based on a network of smart depth cameras is presented. The performance is evaluated with four image sequences, totalling over 20 000 depth images. Experimental results show that simple and lightweight algorithms are very useful in practical applications