19,734 research outputs found

    Pedestrian Flow Simulation Validation and Verification Techniques

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    For the verification and validation of microscopic simulation models of pedestrian flow, we have performed experiments for different kind of facilities and sites where most conflicts and congestion happens e.g. corridors, narrow passages, and crosswalks. The validity of the model should compare the experimental conditions and simulation results with video recording carried out in the same condition like in real life e.g. pedestrian flux and density distributions. The strategy in this technique is to achieve a certain amount of accuracy required in the simulation model. This method is good at detecting the critical points in the pedestrians walking areas. For the calibration of suitable models we use the results obtained from analyzing the video recordings in Hajj 2009 and these results can be used to check the design sections of pedestrian facilities and exits. As practical examples, we present the simulation of pilgrim streams on the Jamarat bridge. The objectives of this study are twofold: first, to show through verification and validation that simulation tools can be used to reproduce realistic scenarios, and second, gather data for accurate predictions for designers and decision makers.Comment: 19 pages, 10 figure

    Encoding natural movement as an agent-based system: an investigation into human pedestrian behaviour in the built environment

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    Gibson's ecological theory of perception has received considerable attention within psychology literature, as well as in computer vision and robotics. However, few have applied Gibson's approach to agent-based models of human movement, because the ecological theory requires that individuals have a vision-based mental model of the world, and for large numbers of agents this becomes extremely expensive computationally. Thus, within current pedestrian models, path evaluation is based on calibration from observed data or on sophisticated but deterministic route-choice mechanisms; there is little open-ended behavioural modelling of human-movement patterns. One solution which allows individuals rapid concurrent access to the visual information within an environment is an 'exosomatic visual architecture" where the connections between mutually visible locations within a configuration are prestored in a lookup table. Here we demonstrate that, with the aid of an exosomatic visual architecture, it is possible to develop behavioural models in which movement rules originating from Gibson's principle of affordance are utilised. We apply large numbers of agents programmed with these rules to a built-environment example and show that, by varying parameters such as destination selection, field of view, and steps taken between decision points, it is possible to generate aggregate movement levels very similar to those found in an actual building context

    Multi-agent simulations for emergency situations in an airport scenario

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    This paper presents a multi-agent framework using Net- Logo to simulate humanand collective behaviors during emergency evacuations. Emergency situationappears when an unexpected event occurs. In indoor emergency situation, evacuation plans defined by facility manager explain procedure and safety ways tofollow in an emergency situation. A critical and public scenario is an airportwhere there is an everyday transit of thousands of people. In this scenario theimportance is related with incidents statistics regarding overcrowding andcrushing in public buildings. Simulation has the objective of evaluating buildinglayouts considering several possible configurations. Agents could be based onreactive behavior like avoid danger or follow other agent, or in deliberative behaviorbased on BDI model. This tool provides decision support in a real emergencyscenario like an airport, analyzing alternative solutions to the evacuationprocess.Publicad

    Traffic Instabilities in Self-Organized Pedestrian Crowds

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    In human crowds as well as in many animal societies, local interactions among individuals often give rise to self-organized collective organizations that offer functional benefits to the group. For instance, flows of pedestrians moving in opposite directions spontaneously segregate into lanes of uniform walking directions. This phenomenon is often referred to as a smart collective pattern, as it increases the traffic efficiency with no need of external control. However, the functional benefits of this emergent organization have never been experimentally measured, and the underlying behavioral mechanisms are poorly understood. In this work, we have studied this phenomenon under controlled laboratory conditions. We found that the traffic segregation exhibits structural instabilities characterized by the alternation of organized and disorganized states, where the lifetime of well-organized clusters of pedestrians follow a stretched exponential relaxation process. Further analysis show that the inter-pedestrian variability of comfortable walking speeds is a key variable at the origin of the observed traffic perturbations. We show that the collective benefit of the emerging pattern is maximized when all pedestrians walk at the average speed of the group. In practice, however, local interactions between slow- and fast-walking pedestrians trigger global breakdowns of organization, which reduce the collective and the individual payoff provided by the traffic segregation. This work is a step ahead toward the understanding of traffic self-organization in crowds, which turns out to be modulated by complex behavioral mechanisms that do not always maximize the group's benefits. The quantitative understanding of crowd behaviors opens the way for designing bottom-up management strategies bound to promote the emergence of efficient collective behaviors in crowds.Comment: Article published in PLoS Computational biology. Freely available here: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.100244
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