Pedestrian Leadership and Egress Assistance Simulation Environment (PLEASE)

Over the past decade, researchers have been developing new ways to model pedestrian egress especially in emergency situations. The traditional methods of modeling pedestrian egress, including ow-based modeling and cellular automata, have been shown to be poor models of human behavior at an individual level, as well as failing to capture many important group social behaviors of pedestrians. This has led to the exploration of agent-based modeling for crowd simulations including those involving pedestrian egress. Using this model, we evaluate different heuristic functions for predicting good egress routes for a variety of real building layouts. We also introduce reinforcement learning as a means to represent individualized pedestrian route knowledge. Finally, we implement a group formation technique, which allows pedestrians in a group to share route knowledge and reach a consensus in route selection. Using the group formation technique, we consider the effects such knowledge sharing and consensus mechanisms have on pedestrian egress times

Pedestrian, Crowd, and Evacuation Dynamics

This contribution describes efforts to model the behavior of individual pedestrians and their interactions in crowds, which generate certain kinds of self-organized patterns of motion. Moreover, this article focusses on the dynamics of crowds in panic or evacuation situations, methods to optimize building designs for egress, and factors potentially causing the breakdown of orderly motion.Comment: This is a review paper. For related work see http://www.soms.ethz.c

Experimental study of pedestrian flow through a bottleneck

In this work the results of a bottleneck experiment with pedestrians are presented in the form of total times, fluxes, specific fluxes, and time gaps. A main aim was to find the dependence of these values from the bottleneck width. The results show a linear decline of the specific flux with increasing width as long as only one person at a time can pass, and a constant value for larger bottleneck widths. Differences between small (one person at a time) and wide bottlenecks (two persons at a time) were also found in the distribution of time gaps.Comment: accepted for publication in J. Stat. Mec

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

Simulation-Based Dynamic Passenger Flow Assignment Modelling for a Schedule-Based Transit Network

The online operation management and the offline policy evaluation in complex transit networks require an effective dynamic traffic assignment (DTA) method that can capture the temporal-spatial nature of traffic flows. The objective of this work is to propose a simulation-based dynamic passenger assignment framework and models for such applications in the context of schedule-based rail transit systems. In the simulation framework, travellers are regarded as individual agents who are able to obtain complete information on the current traffic conditions. A combined route selection model integrated with pretrip route selection and entrip route switch is established for achieving the dynamic network flow equilibrium status. The train agent is operated strictly with the timetable and its capacity limitation is considered. A continuous time-driven simulator based on the proposed framework and models is developed, whose performance is illustrated through a large-scale network of Beijing subway. The results indicate that more than 0.8 million individual passengers and thousands of trains can be simulated simultaneously at a speed ten times faster than real time. This study provides an efficient approach to analyze the dynamic demand-supply relationship for large schedule-based transit networks

Quickest Paths in Simulations of Pedestrians

This contribution proposes a method to make agents in a microscopic simulation of pedestrian traffic walk approximately along a path of estimated minimal remaining travel time to their destination. Usually models of pedestrian dynamics are (implicitly) built on the assumption that pedestrians walk along the shortest path. Model elements formulated to make pedestrians locally avoid collisions and intrusion into personal space do not produce motion on quickest paths. Therefore a special model element is needed, if one wants to model and simulate pedestrians for whom travel time matters most (e.g. travelers in a station hall who are late for a train). Here such a model element is proposed, discussed and used within the Social Force Model.Comment: revised version submitte