State-of-the-art crowd motion simulation models
TL;DR: This paper provides a broad, but not exhaustive overview of the crowd motion simulation models of the last decades and argues that any model used for crowd simulation should be able to simulate most of the phenomena indicated in this paper.
Abstract: Currently, pedestrian simulation models are used to predict where, when and why hazardous high density crowd movements arise. However, it is questionable whether models developed for low density situations can be used to simulate high density crowd movements. The objective of this paper is to assess the existent pedestrian simulation models with respect to known crowd phenomena in order to ascertain whether these models can indeed be used for the simulation of high density crowds and to indicate any gaps in the field of pedestrian simulation modeling research. This paper provides a broad, but not exhaustive overview of the crowd motion simulation models of the last decades. It is argued that any model used for crowd simulation should be able to simulate most of the phenomena indicated in this paper. In the paper cellular automata, social force models, velocity-based models, continuum models, hybrid models, behavioral models and network models are discussed. The comparison shows that the models can roughly be divided into slow but highly precise microscopic modeling attempts and very fast but behaviorally questionable macroscopic modeling attempts. Both sets of models have their use, which is highly dependent on the application the model has originally been developed for. Yet, for practical applications, that need both precision and speed, the current pedestrian simulation models are inadequate.
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TL;DR: The empirical evidence in this area is largely disperse and even in some cases mixed and contradictory, requiring a more unified system of terminologies and problem definitions as well as unified measurement methods in order for the findings of different studies to become replicable and comparable.
Abstract: Introduction The safety of humans in crowded environments has been recognised as an important and rapidly growing research area with significant implications for urban planning, event management, building design, fire safety engineering and rescue service to name a few. This stream of research is aimed at guiding safe designs and effective evacuation plans by simulating emergency scenarios and estimating measures such as total evacuation time. A large body of research has also been dedicated to the development of modelling tools with the capability to identify (and thus prevent) circumstances that lead to crowd discomfort, crashes or disasters in mass gatherings and public facilities. It has, however, been argued that the empirical knowledge in this area has lagged behind the theoretical developments and computational capabilities. This has left the descriptive power of the existing models for reproducing the natural behaviour of humans questionable given that in many cases there is a lack of reliable and well-conditioned data for model validation or calibration purposes. Methods With the vast majority of the empirical knowledge in this fast-growing and interdisciplinary field being very recent, a survey of the existing literature is still missing. Here, we gather together the existing empirical knowledge in this area in a comprehensive review (based on surveying more than 160 studies restricted to those published in peer-reviewed journals since 1995) in order to help bridge this gap. We introduce for the first time a categorisation system of the relevant data collection techniques by recognising seven general empirical approaches. We also differentiate between various aspects of human behaviour pertinent to crowd behaviour by putting them into perspective in terms of three general levels of “decision making”. We also discuss the advantages and disadvantages offered by each data collection technique. Major gaps and poorly-explored topics in the current literature are discussed. Findings and applications Our major conclusion is that the empirical evidence in this area is largely disperse and even in some cases mixed and contradictory, requiring a more unified system of terminologies and problem definitions as well as unified measurement methods in order for the findings of different studies to become replicable and comparable. We also showed that the existing body of empirical studies display a clear imbalance in addressing various aspects of human behaviour with certain (but crucial) aspects (such as “pre-movement time” and “choice of activity”) being poorly understood (as opposed to our knowledge and amount of data about “walking behaviour” for example). Our review also revealed that previous studies have predominantly displayed a stronger tendency to study the behaviour based on aggregate measures as opposed to individual-level data collection attempts. We hope that this collection of findings sets clearer avenues for advancing the knowledge in this area, guides future experiment designs and helps researchers form better-informed hypotheses and choose most suitable data collection methods for their question in hand.
216 citations
TL;DR: A microscopic simulation model for pedestrian behavior analysis at signalized intersection using the social force theory has been developed and it was concluded that the model enables to visually represent pedestrian crossing behavior as in the real world.
Abstract: Limited pedestrian behavior models shed light on the case at signalized crosswalk, where pedestrian behavior is characterized by group or individual evasion with surrounding pedestrians, collision avoidance with conflicting vehicles, and response to signal control and crosswalk boundary. This study fills this gap by developing a microscopic simulation model for pedestrian behavior analysis at signalized intersection. The social force theory has been employed and adjusted for this purpose. The parameters, including measurable and non-measurable ones, are either directly estimated based on observed dataset or indirectly derived by maximum likelihood estimation. Last, the model performance was confirmed in light of individual trajectory comparison between estimation and observation, passing position distribution at several cross-sections, collision avoidance behavior with conflicting vehicles, and lane-formation phenomenon. The simulation results also concluded that the model enables to visually represent pedestrian crossing behavior as in the real world.
198 citations
TL;DR: In this article, a review of the use of optimisation models for pedestrian evacuation and design problems is presented, which is classified according to the problem type that is studied, the level of model realism, and the modelling or solution technique.
190 citations
TL;DR: It is shown that crowds of real human subjects moving and interacting in an immersive three-dimensional virtual environment exhibit typical patterns of real crowds as observed in real-life crowded situations, and that herding spontaneously emerges from a density effect without the need to assume an increase of the individual tendency to imitate peers.
Abstract: Understanding the collective dynamics of crowd movements during stressful emergency situations is central to reducing the risk of deadly crowd disasters. Yet, their systematic experimental study remains a challenging open problem due to ethical and methodological constraints. In this paper, we demonstrate the viability of shared three-dimensional virtual environments as an experimental platform for conducting crowd experiments with real people. In particular, we show that crowds of real human subjects moving and interacting in an immersive three-dimensional virtual environment exhibit typical patterns of real crowds as observed in real-life crowded situations. These include the manifestation of social conventions and the emergence of self-organized patterns during egress scenarios. High-stress evacuation experiments conducted in this virtual environment reveal movements characterized by mass herding and dangerous overcrowding as they occur in crowd disasters. We describe the behavioural mechanisms at play under such extreme conditions and identify critical zones where overcrowding may occur. Furthermore, we show that herding spontaneously emerges from a density effect without the need to assume an increase of the individual tendency to imitate peers. Our experiments reveal the promise of immersive virtual environments as an ethical, cost-efficient, yet accurate platform for exploring crowd behaviour in high-risk situations with real human subjects.
165 citations
TL;DR: In this article, the authors present an agent-based modeling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations.
Abstract: This paper discusses the development of an agent-based modeling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typically done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Initial tests with case studies involving traffic management center impacts on various network events such as accidents show the potential of the system.
155 citations
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TL;DR: Computer simulations of crowds of interacting pedestrians show that the social force model is capable of describing the self-organization of several observed collective effects of pedestrian behavior very realistically.
Abstract: It is suggested that the motion of pedestrians can be described as if they would be subject to ``social forces.'' These ``forces'' are not directly exerted by the pedestrians' personal environment, but they are a measure for the internal motivations of the individuals to perform certain actions (movements). The corresponding force concept is discussed in more detail and can also be applied to the description of other behaviors. In the presented model of pedestrian behavior several force terms are essential: first, a term describing the acceleration towards the desired velocity of motion; second, terms reflecting that a pedestrian keeps a certain distance from other pedestrians and borders; and third, a term modeling attractive effects. The resulting equations of motion of nonlinearly coupled Langevin equations. Computer simulations of crowds of interacting pedestrians show that the social force model is capable of describing the self-organization of several observed collective effects of pedestrian behavior very realistically.
5,716 citations
TL;DR: A model of pedestrian behaviour is used to investigate the mechanisms of panic and jamming by uncoordinated motion in crowds, and an optimal strategy for escape from a smoke-filled room is found, involving a mixture of individualistic behaviour and collective ‘herding’ instinct.
Abstract: One of the most disastrous forms of collective human behaviour is the kind of crowd stampede induced by panic, often leading to fatalities as people are crushed or trampled. Sometimes this behaviour is triggered in life-threatening situations such as fires in crowded buildings; at other times, stampedes can arise during the rush for seats or seemingly without cause. Although engineers are finding ways to alleviate the scale of such disasters, their frequency seems to be increasing with the number and size of mass events. But systematic studies of panic behaviour and quantitative theories capable of predicting such crowd dynamics are rare. Here we use a model of pedestrian behaviour to investigate the mechanisms of (and preconditions for) panic and jamming by uncoordinated motion in crowds. Our simulations suggest practical ways to prevent dangerous crowd pressures. Moreover, we find an optimal strategy for escape from a smoke-filled room, involving a mixture of individualistic behaviour and collective 'herding' instinct.
4,334 citations
TL;DR: This article considers the empirical data and then reviews the main approaches to modeling pedestrian and vehicle traffic, including microscopic (particle-based), mesoscopic (gas-kinetic), and macroscopic (fluid-dynamic) models.
Abstract: Since the subject of traffic dynamics has captured the interest of physicists, many surprising effects have been revealed and explained. Some of the questions now understood are the following: Why are vehicles sometimes stopped by ``phantom traffic jams'' even though drivers all like to drive fast? What are the mechanisms behind stop-and-go traffic? Why are there several different kinds of congestion, and how are they related? Why do most traffic jams occur considerably before the road capacity is reached? Can a temporary reduction in the volume of traffic cause a lasting traffic jam? Under which conditions can speed limits speed up traffic? Why do pedestrians moving in opposite directions normally organize into lanes, while similar systems ``freeze by heating''? All of these questions have been answered by applying and extending methods from statistical physics and nonlinear dynamics to self-driven many-particle systems. This article considers the empirical data and then reviews the main approaches to modeling pedestrian and vehicle traffic. These include microscopic (particle-based), mesoscopic (gas-kinetic), and macroscopic (fluid-dynamic) models. Attention is also paid to the formulation of a micro-macro link, to aspects of universality, and to other unifying concepts, such as a general modeling framework for self-driven many-particle systems, including spin systems. While the primary focus is upon vehicle and pedestrian traffic, applications to biological or socio-economic systems such as bacterial colonies, flocks of birds, panics, and stock market dynamics are touched upon as well.
3,117 citations
01 Jan 1971
1,912 citations
Book•
01 Jan 1971
TL;DR: For instance, the authors argues that the way strangers relate in public is part of a design by which friends and acquaintances manage their relationship in the presence of bystanders, and argues that, taken together, this forms part of an inquiry into the rules for co-mingling, or public order.
Abstract: Until recently, to be in a "public place" meant to feel safe. That has changed, especially in cities. Urban dwellers sense the need to quickly react to gestural cues from persons in their immediate presence in order to establish their relationship to each other. Through this communication they hope to detect potential danger before it is too late for self-defense or flight. The ability to read accurately the "informing signs" by which strangers indicate their relationship to one another in public or semi-public places without speaking, has become as important as understanding the official written and spoken language of the country. In Relations in Public, Erving Goff man provides a grammar of the unspoken language used in public places. He shows that the way strangers relate in public is part of a design by which friends and acquaintances manage their relationship in the presence of bystanders. He argues that, taken together, this forms part of a new domain of inquiry into the rules for co-mingling, or public order. Most people give little thought to how elaborate and complex our everyday behavior in public actually is. For example, we adhere to the rules of pedestrian traffic on a busy thoroughfare, accept the usual ways of acting in a crowded elevator or subway car, grasp the delicate nuances of conversational behavior, and respond to the rich vocabulary of body gestures. We behave differently at weddings, at meals, in crowds, in couples, and when alone. Such everyday behavior, though generally below the level of awareness, embodies unspoken codes of social understandings necessary for the orderly conduct of society.
1,743 citations