Calibrating floor field cellular automaton models for pedestrian dynamics by using likelihood function optimization

Lovreglio, Ruggiero; Ronchi, Enrico; Nilsson, Daniel

doi:10.1016/j.physa.2015.06.040

Cited by 60 publications

(33 citation statements)

References 47 publications

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“…A range of approaches for calibrating model parameters have been suggested [2,[4][5][6][7][8]. They compare models to empirical data at a microscopic level (e.g.…”

Section: Introductionmentioning

confidence: 99%

Parameter Calibration in Crowd Simulation Models using Approximate Bayesian Computation

Bode

2020

Coll Dyn

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Simulation models for pedestrian crowds are a ubiquitous tool in research and industry. It is crucial that the parameters of these models are calibrated carefully and ultimately it will be of interest to compare competing models to decide which model is best suited for a particular purpose. In this contribution, I demonstrate how Approximate Bayesian Computation (ABC), which is already a popular tool in other areas of science, can be used for model fitting and model selection in a pedestrian dynamics context. I fit two different models for pedestrian dynamics to data on a crowd passing in one direction through a bottleneck. One model describes movement in continuous-space, the other model is a cellular automaton and thus describes movement in discrete-space. In addition, I compare models to data using two metrics. The first is based on egress times and the second on the velocity of pedestrians in front of the bottleneck. My results show that while model fitting is successful, a substantial degree of uncertainty about the value of some model parameters remains after model fitting. Importantly, the choice of metric in model fitting can influence parameter estimates. Model selection is inconclusive for the egress time metric but supports the continuous-space model for the velocity-based metric. These findings show that ABC is a flexible approach and highlight the difficulties associated with model fitting and model selection for pedestrian dynamics. ABC requires many simulation runs and choosing appropriate metrics for comparing data to simulations requires careful attention. Despite this, I suggest ABC is a promising tool, because it is versatile and easily implemented for the growing number of openly available crowd simulators and data sets.

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“…A range of approaches for calibrating model parameters have been suggested [2,[4][5][6][7][8]. They compare models to empirical data at a microscopic level (e.g.…”

Section: Introductionmentioning

confidence: 99%

Parameter Calibration in Crowd Simulation Models using Approximate Bayesian Computation

Bode

2020

Coll Dyn

View full text Add to dashboard Cite

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“…They include, for example, simulators of pedestrian Following the debate of the panic misconception, emergency evacuation research has focused on the application of different theories and models to increase the understanding of isolated decisions. This includes rationality-based theories of choice such as utility theories [4], the theory of affordances [29] psychological models [30,31], data-driven [32] or cognitive science-inspired models [33]. These models have shown reasonably good capabilities in capturing human behaviour and decision making during evacuations.…”

Section: Introductionmentioning

confidence: 99%

“…Model results highlight the benefits of announced evacuation drills and suggest that improving the accuracy of threat detection can prevent large inefficiencies associated with the cry wolf effect. dynamics during evacuation [2][3][4], which aims at representing human movement and associated behaviour in case of different scenarios and threats [6,7], or models of authority's recommendations [8].Human behaviour in evacuation scenarios has also been investigated using Virtual Reality tools, as they allow the investigation of individual and group decision making during evacuation [9][10][11][12]. Experimental work has been performed in order to validate such models and tools, including the study of different types of emergent behaviours related to evacuation dynamics [13][14][15][16][17].The main limitations of these tools is that they consider evacuation scenarios in isolation and they address only one of the two parties involved in an evacuation, either (i) the decision making of the authority (i.e.…”

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confidence: 99%

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The cry wolf effect in evacuation: A game-theoretic approach

Rigos

Mohlin

Ronchi

2019

Physica A: Statistical Mechanics and its Applications

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In today's terrorism-prone and security-focused world, evacuation emergencies, drills, and false alarms are becoming more and more common. Compliance to an evacuation order made by an authority in case of emergency can play a key role in the outcome of an emergency. In case an evacuee experiences repeated emergency scenarios which may be a false alarm (e.g., an evacuation drill, a false bomb threat, etc.) or an actual threat, the Aesop's cry wolf effect (repeated false alarms decrease order compliance) can severely affect his/her likelihood to evacuate. To analyse this key unsolved issue of evacuation research, a game-theoretic approach is proposed. Game theory is used to explore mutual best responses of an evacuee and an authority. In the proposed model the authority obtains a signal of whether there is a threat or not and decides whether to order an evacuation or not. The evacuee, after receiving an evacuation order, subsequently decides whether to stay or leave based on posterior beliefs that have been updated in response to the authority's action. Best-responses are derived and Sequential equilibrium and Perfect Bayesian Equilibrium are used as solution concepts (refining equilibria with the intuitive criterion). Model results highlight the benefits of announced evacuation drills and suggest that improving the accuracy of threat detection can prevent large inefficiencies associated with the cry wolf effect. dynamics during evacuation [2][3][4], which aims at representing human movement and associated behaviour in case of different scenarios and threats [6,7], or models of authority's recommendations [8].Human behaviour in evacuation scenarios has also been investigated using Virtual Reality tools, as they allow the investigation of individual and group decision making during evacuation [9][10][11][12]. Experimental work has been performed in order to validate such models and tools, including the study of different types of emergent behaviours related to evacuation dynamics [13][14][15][16][17].The main limitations of these tools is that they consider evacuation scenarios in isolation and they address only one of the two parties involved in an evacuation, either (i) the decision making of the authority (i.e. their orders/instructions) or (ii) the actions of the evacuees. In contrast, currently there is no framework available which is able to comprehensively consider optimal decision making strategies for an authority and an evacuee at the same time in case of several repeated emergency evacuation threats. Many tragedies have demonstrated the dilemmas that decision makers may face when dealing with emergency situations. For instance, in relation to the Costa Concordia disaster, the Italian court trial is evaluating the behaviour of captain Schettino who allegedly did not order the evacuation of the ship on time [18]. Apart from the Captain's negligence or a simply incorrect assessment of the situation, the analysis of the trade-offs between the cost of a useless evacuation (i.e., the risk of "ruining" the holid...

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“…Fourth, virtual reality experiments provide a new methodology for crowd behavior research. The data collected in a virtual environment can be used not only to validate and calibrate existing models [27], but also for further data mining.…”

Section: Introductionmentioning

confidence: 99%

A Heterogeneous Distributed Virtual Geographic Environment—Potential Application in Spatiotemporal Behavior Experiments

Shen

Gong

Liang

et al. 2018

IJGI

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Due to their strong immersion and real-time interactivity, helmet-mounted virtual reality (VR) devices are becoming increasingly popular. Based on these devices, an immersive virtual geographic environment (VGE) provides a promising method for research into crowd behavior in an emergency. However, the current cheaper helmet-mounted VR devices are not popular enough, and will continue to coexist with personal computer (PC)-based systems for a long time. Therefore, a heterogeneous distributed virtual geographic environment (HDVGE) could be a feasible solution to the heterogeneous problems caused by various types of clients, and support the implementation of spatiotemporal crowd behavior experiments with large numbers of concurrent participants. In this study, we developed an HDVGE framework, and put forward a set of design principles to define the similarities between the real world and the VGE. We discussed the HDVGE architecture, and proposed an abstract interaction layer, a protocol-based interaction algorithm, and an adjusted dead reckoning algorithm to solve the heterogeneous distributed problems. We then implemented an HDVGE prototype system focusing on subway fire evacuation experiments. Two types of clients are considered in the system: PC, and all-in-one VR. Finally, we evaluated the performances of the prototype system and the key algorithms. The results showed that in a low-latency local area network (LAN) environment, the prototype system can smoothly support 90 concurrent users consisting of PC and all-in-one VR clients. HDVGE provides a feasible solution for studying not only spatiotemporal crowd behaviors in normal conditions, but also evacuation behaviors in emergency conditions such as fires and earthquakes. HDVGE could also serve as a new means of obtaining observational data about individual and group behavior in support of human geography research.

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Calibrating floor field cellular automaton models for pedestrian dynamics by using likelihood function optimization

Cited by 60 publications

References 47 publications

Parameter Calibration in Crowd Simulation Models using Approximate Bayesian Computation

Parameter Calibration in Crowd Simulation Models using Approximate Bayesian Computation

The cry wolf effect in evacuation: A game-theoretic approach

A Heterogeneous Distributed Virtual Geographic Environment—Potential Application in Spatiotemporal Behavior Experiments

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