Influence of Pre-bottleneck Diversion Devices on Pedestrian Flow

The existence of bottlenecks often leads to the stagnation of pedestrian gatherings, which seriously affects the efficiency of traffic and reduces the flow of pedestrians. Some studies have shown that setting devices in front of bottlenecks can promote pedestrian evacuation under certain conditions. In this paper, the effect of setting diversion devices in front of the exit on pedestrian flow is studied. From our observation, these diversion devices can form a buffer zone before the exit and affect pedestrian behaviors. The evacuation times are found to decrease as the devices became farther away from the exit. In our experiments, it is found that the effect of shunt piles on evacuation is better than in the case of safety barriers and without device conditions. Under the condition of setting up safety barriers approximately 1m and 3m in front of the exit, the evacuation times are extended by 0.88% and 2.67%. For shunt piles, the evacuation times are 11.53% and 14.96% shorter than that of those without a device regarding the different distances to exit (1m and 3m, respectively). In addition, setting up shunt piles reduces the time interval between two consecutive pedestrians. To sum up, in our experimental settings, the diversion devices can effectively improve the average speed ahead of the exit and promote evacuation to become more orderly, which reduces the congestion in the later period of evacuation. In other words, this study demonstrates that a reasonable layout of facilities can not only meet the daily functional requirements but also improve the efficient use of space in emergencies, reducing the probability of crowd conventions and jams

Urban tourism crowding dynamics: Carrying capacity and digital twinning

The increase in tourism activity globally has led to overcrowding, causing damage to local ecosystems and degradation of the tourism experience. To plan tourist activity it is necessary to define adequate indicators and understand the dynamics of tourist crowds. The main goals of this dissertation are the development of (1) an algorithm for assessing spatially fine-grained, physical carrying capacity (PCC) for a complex urban fabric, (2) an agent-based simulation model for the egress of participants in public open space tourism attraction events and (3) an agent-based simulation model using the PCC algorithm for tourism crowding stress analysis in urban fabric constrained scenarios. OpenStreetMap open-data was used throughout this research. The proposed PCC algorithm was tested in Santa Maria Maior parish in Lisbon that has a complex ancient urban fabric. The GAMA agent-based platform was used in the two simulation studies. The first compared two scenarios (normal and COVID-19) in three major public spaces in Lisbon and the second focused on the simulation of a real-time tourism crowding stress analysis scenario of visitors’ arrival at the Lisbon Cruise Terminal. The results show the proposed algorithm’s feasibility to determine the PCC of complex urban fabrics zones and its application as an initial reference value for the evaluation of real-time crowding stress, namely in simulations for assessing overtourism scenarios, both in public open spaces as in highly constrained urban fabrics.O aumento da atividade turística a nível global tem levado à superlotação, causando danos aos ecossistemas locais e degradação da experiência turística. Para planear a atividade turística é necessário definir indicadores adequados e entender as dinâmicas das multidões turísticas. Os principais objetivos desta dissertação são o desenvolvimento de (1) um algoritmo para avaliar a capacidade de carga física (CCF) de fino grão espacial para uma malha urbana complexa, (2) um modelo de simulação baseado em agentes para o escoamento de participantes em eventos de atração turística em espaços abertos e (3) um modelo de simulação baseado em agentes usando o algoritmo de CCF para análise do stress de aglomeração de turistas em cenários de malha urbana restritiva. Os dados abertos do OpenStreetMap foram usados nesta investigação. O algoritmo CCF proposto foi testado na freguesia de Santa Maria Maior, em Lisboa, que tem uma malha urbana antiga e complexo. A plataforma GAMA baseada em agentes foi usada nos dois estudos de simulação. O primeiro comparou dois cenários (normal e COVID-19) em três grandes espaços públicos de Lisboa e o segundo analisou o stress de aglomeração causado pela chegada de navios ao Terminal de Cruzeiros de Lisboa. Os resultados mostram a viabilidade do algoritmo proposto para determinar a CCF de zonas com tecidos urbanos complexos e a sua aplicação como valor de referência inicial para a avaliação do stress de superlotação em tempo real, nomeadamente na avaliação de cenários de aglomeração turística excessiva, tanto em espaços abertos, como em malhas urbanas intrincadas

Redefining the role of obstacles in pedestrian evacuation

The placement of obstacles in front of doors is believed to be an effective strategy to increase the flow of pedestrians, hence improving the evacuation process. Since it was first suggested, this counterintuitive feature is considered a hallmark of pedestrian flows through bottlenecks. Indeed, despite the little experimental evidence, the placement of an obstacle has been hailed as the panacea for solving evacuation problems. In this work, we challenge this idea and experimentally demonstrate that the pedestrians flow rate is not necessarily altered by the presence of an obstacle. This result - which is at odds with recent demonstrations on its suitability for the cases of granular media, sheep and mice - differs from the outcomes of most of existing numerical models, and warns about the risks of carelessly extrapolating animal behaviour to humans. Our experimental findings also reveal an unnoticed phenomenon in relation with the crowd movement in front of the exit: in competitive evacuations, an obstacle attenuates the development of collective transversal rushes, which are hazardous as they might cause falls.Fil: Garcimartín, A.. Universidad de Navarra; EspañaFil: Maza, D.. Universidad de Navarra; EspañaFil: Pastor, J. M.. Focke Meler Gluing Solutions S.A.; EspañaFil: Parisi, Daniel Ricardo. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Martín Gómez, C.. Universidad de Navarra; EspañaFil: Zuriguel, I.. Universidad de Navarra; Españ

Computational Study of Social Interactions and Collective Behavior During Human Emergency Egress.

Egress of occupants from a facility is normally straightforward. Problems arise when an emergency is present and many occupants are attempting to egress as quickly as possible, at which point egress can become life threatening. There are many reported events in history where emergency egress resulted in extensive loss of life and injuries. Egress research depends heavily on computational modeling because ethical and safety concerns preclude running experiments involving emergency crowd evacuations. However, to date, existing egress models rarely take into account meaningful social interactions and adherence to cultural norms, both of which are commonly present among egressing occupants and have significant influence on their egress response. The objective of this study is to develop a new methodology to address this gap using an Agent-Based computational platform. A novel method, termed Scalar Field Method (SFM), is proposed to accomplish this goal. The new technique draws on an analogy to a charged particle in an electromagnetic field to simulate the decision making process of an agent as it navigates through a facility and considers social interactions in its quest to egress. Two categories of social interactions are accounted for: 1) pre-existing social relationships associated with social identities, and 2) informal relations in collective behaviors such as lining up in counter-flow, queuing, and collective mobility. The latter is achieved by requiring an agent to establish informal and transient leader-follower relationships with others while adjusting its behavioral patterns as warranted by the situation. Simulation results demonstrate the model’s capabilities of handling social interactions, modeling reasonable egress behavior, and mimicking self-organized social gathering and collective behavior during egress. Comparisons with field studies show that the computational results correlate realistically with experimental data. A case study of the Station Nightclub fire that occurred in Rhode Island in 2003 and killed 100 occupants demonstrates that the proposed computational tools have strong potential for quantitatively exploring the influence of social level traits on egress situations.PhDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113381/1/calcite_1.pd

A discrete mathematical model for the dynamics of a crowd of gazing pedestrians with and without an evolving environmental awareness

In this article, we present a microscopic-discrete mathematical model describing crowd dynamics in no panic conditions. More specifically, pedestrians are set to move in order to reach a target destination and their movement is influenced by both behavioral strategies and physical forces. Behavioral strategies include individual desire to remain sufficiently far from structural elements (walls and obstacles) and from other walkers, while physical forces account for interpersonal collisions. The resulting pedestrian behavior emerges therefore from non-local, anisotropic and short/long-range interactions. Relevant improvements of our mathematical model with respect to similar microscopic-discrete approaches present in the literature are: (i) each pedestrian has his/her own dynamic gazing direction, which is regarded to as an independent degree of freedom and (ii) each walker is allowed to take dynamic strategic decisions according to his/her environmental awareness, which increases due to new information acquired on the surrounding space through their visual region. The resulting mathematical modeling environment is then applied to specific scenarios that, although simplified, resemble real-word situations. In particular, we focus on pedestrian flow in twodimensional buildings with several structural elements (i.e., corridors, divisors and columns, and exit doors). The noticeable heterogeneity of possible applications demonstrates the potential of our mathematical model in addressing different engineering problems, allowing for optimization issues as well

Multi-scale Models for Transportation Systems Under Emergency Conditions

The purpose of this study is to investigate human behavior in emergencies. More specifically, agent-based simulation and social force models were developed to examine the impact of various human and environmental factors on the efficiency of the evacuation process, through a series of case studies. The independent variables of the case studies include the number of exits, the number of passengers, the evacuation policies, and instructions, as well as the queue configuration and wall separators. The results revealed the location of the exits, number of exits, evacuation strategies, and group behaviors all significantly impact the total time of the evacuation. For the queue configuration, short aisles lower infection spread when rope separators were used. The findings provide new insights in designing layout, planning, practice, and training strategies for improving the effectiveness of the pedestrian evacuation process under emergency