Experimental Study of Phase Transition in Pedestrian Flow

The transition between low and high density phases is a typical feature of systems with social interactions. This contribution focuses on simple evacuation design of one room with one entrance and one exit; four passing-through experiments were organized and evaluated by means of automatic image processing. The phase of the system, determined by travel time and occupancy, is evaluated with respect to the inflow, a controlled boundary condition. Critical values of inflow and outflow were described with respect to the transition from low density to congested state. Moreover, microscopic analysis of travel time is provided.Comment: To appear in proceedings of Pedestrian and Evacuation Dynamics 2014, Transportation Research Procedia, Elsevie

System Identification for the design of behavioral controllers in crowd evacuations

Behavioral modification using active instructions is a promising interventional method to optimize crowd evacuations. However, existing research efforts have been more focused on eliciting general principles of optimal behavior than providing explicit mechanisms to dynamically induce the desired behaviors, which could be claimed as a significant knowledge gap in crowd evacuation optimization. In particular, we propose using dynamic distancekeeping instructions to regulate pedestrian flows and improve safety and evacuation time. We investigate the viability of using Model Predictive Control (MPC) techniques to develop a behavioral controller that obtains the optimal distance-keeping instructions to modulate the pedestrian density at bottlenecks. System Identification is proposed as a general methodology to model crowd dynamics and build prediction models. Thus, for a testbed evacuation scenario and input?output data generated from designed microscopic simulations, we estimate a linear AutoRegressive eXogenous model (ARX), which is used as the prediction model in the MPC controller. A microscopic simulation framework is used to validate the proposal that embeds the designed MPC controller, tuned and refined in closed-loop using the ARX model as the Plant model. As a significant contribution, the proposed combination of MPC control and System Identification to model crowd dynamics appears ideally suited to develop realistic and practical control systems for controlling crowd motion. The flexibility of MPC control technology to impose constraints on control variables and include different disturbance models in the prediction model has confirmed its suitability in the design of behavioral controllers in crowd evacuations. We found that an adequate selection of output disturbance models in the predictor is critical in the type of responses given by the controller. Interestingly, it is expected that this proposal can be extended to different evacuation scenarios, control variables, control systems, and multiple-input multiple-output control structures.Ministerio de Economía y Competitivida

Geospatial analysis and living urban geometry

This essay outlines how to incorporate morphological rules within the exigencies of our technological age. We propose using the current evolution of GIS (Geographical Information Systems) technologies beyond their original representational domain, towards predictive and dynamic spatial models that help in constructing the new discipline of "urban seeding". We condemn the high-rise tower block as an unsuitable typology for a living city, and propose to re-establish human-scale urban fabric that resembles the traditional city. Pedestrian presence, density, and movement all reveal that open space between modernist buildings is not urban at all, but neither is the open space found in today's sprawling suburbs. True urban space contains and encourages pedestrian interactions, and has to be designed and built according to specific rules. The opposition between traditional self-organized versus modernist planned cities challenges the very core of the urban planning discipline. Planning has to be re-framed from being a tool creating a fixed future to become a visionary adaptive tool of dynamic states in evolution

Effects of communication efficiency and exit capacity on fundamental diagrams for pedestrian motion in an obscure tunnel|a particle system approach

Fundamental diagrams describing the relation between pedestrians speed and density are key points in understanding pedestrian dynamics. Experimental data evidence the onset of complex behaviors in which the velocity decreases with the density and different logistic regimes are identified. This paper addresses the issue of pedestrians transport and of fundamental diagrams for a scenario involving the motion of pedestrians escaping from an obscure tunnel. % via a simple one--dimensional particle system model. We capture the effects of the communication efficiency and the exit capacity by means of two thresholds controlling the rate at which particles (walkers, pedestrians) move on the lattice. Using a particle system model, we show that in absence of limitation in communication among pedestrians we reproduce with good accuracy the standard fundamental diagrams, whose basic behaviors can be interpreted in terms of the exit capacity limitation. When the effect of a limited communication ability is considered, then interesting non--intuitive phenomena occur. Particularly, we shed light on the loss of monotonicity of the typical speed--density curves, revealing the existence of a pedestrians density optimizing the escape. We study both the discrete particle dynamics as well as the corresponding hydrodynamic limit (a porous medium equation and a transport (continuity) equation). We also point out the dependence of the effective transport coefficients on the two thresholds -- the essence of the microstructure information

Multi-Agent Fitness Functions For Evolutionary Architecture

The dynamics of crowd movements are self-organising and often involve complex pattern formations. Although computational models have recently been developed, it is unclear how well their underlying methods capture local dynamics and longer-range aspects, such as evacuation. A major part of this thesis is devoted to an investigation of current methods, and where required, the development of alternatives. The main purpose is to utilise realistic models of pedestrian crowds in the design of fitness functions for an evolutionary approach to architectural design. We critically review the state-of-the-art in pedestrian and evacuation dynamics. The concept of 'Multi-Agent System' embraces a number of approaches, which together encompass important local and longer-range aspects. Early investigations focus on methods-cellular automata and attractor fields-designed to capture these respective levels. The assumption that pattern formations in crowds result from local processes is reflected in two dimensional cellular automata models, where mathematical rules operate in local neighbourhoods. We investigate an established cellular automata and show that lane-formation patterns are stable only in a low-valued density range. Above this range, such patterns suddenly randomise. By identifying and then constraining the source of this randomness, we are only able to achieve a small degree of improvement. Moreover, when we try to integrate the model with attractor fields, no useful behaviour is achieved, and much of the randomness persists. Investigations indicate that the unwanted randomness is associated with 2-lattice phase transitions, where local dynamics get invaded by giant-component clusters during the onset of lattice percolation. Through this in-depth investigation, the general limits to cellular automata are ascertained-these methods are not designed with lattice percolation properties in mind and resulting models depend, often critically, on arbitrarily chosen neighbourhoods. We embark on the development of new and more flexible methodologies. Rather than treating local and global dynamics as separate entities, we combine them. Our methods are responsive to percolation, and are designed around the following principles: 1) Inclusive search provides an optimal path between a pedestrian origin and destination. 2) Dynamic boundaries protect search and are based on percolation probabilities, calculated from local density regimes. In this way, more robust dynamics are achieved. Simultaneously, longer-range behaviours are also specified. 3) Network-level dynamics further relax the constraints of lattice percolation and allow a wider range of pedestrian interactions. Having defined our methods, we demonstrate their usefulness by applying them to lane-formation and evacuation scenarios. Results reproduce the general patterns found in real crowds. We then turn to evolution. This preliminary work is intended to motivate future research in the field of Evolutionary Architecture. We develop a genotype-phenotype mapping, which produces complex architectures, and demonstrate the use of a crowd-flow model in a phenotype-fitness mapping. We discuss results from evolutionary simulations, which suggest that obstacles may have some beneficial effect on crowd evacuation. We conclude with a summary, discussion of methodological limitations, and suggestions for future research

Linear and nonlinear Model Predictive Control (MPC) for regulating pedestrian flows with discrete speed instructions

Airports, shopping malls, stadiums, and large venues in general, can become congested and chaotic at peak times or in emergency situations. Linear Model Predictive Control (MPC) is an effective technology in generating dynamic speed or distance instructions for regulating pedestrian flows, and constitutes a promising interventional technique to improve safety and evacuation time during emergency egress operations. We compare linear and nonlinear MPC controllers and study the influence of using continuous vs. discrete control actions. We aim to evaluate the efficacy of simple instructions that pedestrians can easily follow during evacuations. Linear and Nonlinear AutoRegressive eXogenous models (ARX and NLARX) for prediction are identified from input?output data from strategically designed microscopic evacuation simulations. A microscopic simulation framework is used to design and validate different MPC controllers tuned and refined using the identified models. We evaluate the prediction models? performance and study how the controlled variable type, density, or crowd-pressure, influences the controllers? performance. As a relevant contribution, we show that MPC control with discrete instructions is ideally suited to design and deploy practical pedestrian flow control systems. We found that an adequate size of the set of speed instructions is critical to obtain a good balance between controllability and performance, and that density output control is preferred over crowd-pressure.Universidad de Alcal

A new algorithm for estimating pedestrian flows during massive touristic events, optimized for an existing camera setup

In questa tesi presento un nuovo algoritmo per l'analisi di filmati che permette di calcolare il flusso di persone che attraversano un passaggio anche in presenza di condizioni sfavorevoli della telecamera. Il lavoro di tesi si è concentrato sull'analisi di una serie di sequenze video precedentemente estratte da una telecamera di sicurezza rivolta verso il Ponte della Costituzione a Venezia, con lo scopo di stimare il flusso pedonale sul ponte. La scarsa qualità dei video dovuta alla bassa risoluzione ed il posizionamento non ottimale della telecamera, che provoca numerose sovrapposizioni, causano il fallimento di molte tecniche di computer vision esistenti, perciò è stato necessario creare una nuova soluzione. È stata inoltre effettuata una verifica dell'algoritmo attraverso un programma che lo implementa, analizzando sia dati artificiali che reali