School egress data: comparing the configuration and validation of five egress modelling tools

Cuesta, Arturo; Ronchi, Enrico; Gwynne, S.; Kinsey, Michael; Hunt, Aoife; Alvear, Daniel

doi:10.1002/fam.2405

Cited by 34 publications

(24 citation statements)

References 11 publications

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“…This is done by selecting those values from existing databases, when available, (see for instance [1][2][3]) or by making reasonable assumptions. Evacuation data is therefore needed to model and simulate occupants' behaviour [4,5] as well as to validate existing and new evacuation models [6,7].…”

Section: Introductionmentioning

confidence: 99%

Evacuation Data from a Hospital Outpatient Drill The Case Study of North Shore Hospital

Rahouti

Lovreglio²,

Jackson³

et al. 2020

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Assessing the fire safety of buildings is fundamental to reduce the impact of this threat on their occupants. Such an assessment can be done by combining existing models and existing knowledge on how occupants behave during fires. Although many studies have been carried out for several types of built environment, only few of those investigate healthcare facilities and hospitals. In this study, we present a new behavioural data-set for hospital evacuations. The data was collected from the North Shore Hospital in Auckland (NZ) during an unannounced drill carried out in May 2017. This drill was recorded using CCTV and those videos are analysed to generate new evacuation model inputs for hospital scenarios. We collected pre-movement times, exit choices and total evacuation times for each evacuee. Moreover, we estimated pre-movement time distributions for both staff members and patients. Finally, we qualitatively investigated the evacuee actions of patients and staff members to study their interaction during the drill. The results show that participants were often independent from staff actions with a majority able to make their own decision.

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Section: Introductionmentioning

confidence: 99%

Evacuation Data from a Hospital Outpatient Drill The Case Study of North Shore Hospital

Rahouti

Lovreglio²,

Jackson³

et al. 2020

Coll Dyn

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“…The proposed method assumes that there are three possible exit and access points, both for flights and landings of stairs—inside, center, and outside—similarly to the proposal of Cuesta et al 10 …”

Section: The Proposed Methodsmentioning

confidence: 99%

“…Cuesta and Gwyne 10,14,15 found that there was variability in the routes taken by people on landings, and consequently, the possibility of significant variation in speeds, so that they have expanded the possible routes on the landings of stairs to three. However, they did not present further details about the speeds resulting from this variable.…”

Section: Introductionmentioning

confidence: 99%

Method for collecting data of children descending movement on stairs in schools

Ono

Valentim

Vittorino³

2020

Fire and Materials

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Summary A method to collect the times and travel routes in predefined sections of stairs is presented, in order to obtain walking velocities of children. Twenty‐seven possible travel paths on landings and nine possible travel paths on flights are proposed and the equations developed to calculate them are presented. Experiments were carried out where data were not collected from fire drills, as usually are, but from the movement of unimpeded individuals descending stairs using this method. The technique used to collect data was the observation of video recordings via a closed‐circuit television system. Seven hundred and eighty‐three students ranging from 6 to 10 years of age and from three different schools participated in the experiments. Particularly, movements on stair flights and landings were analyzed separately for a group of 54 students of the first grade (6 years‐old), for a comparative analysis of the distances and velocities obtained with methods used by other researchers and significant differences were found. In addition, by the present method, the dispersion of velocity values in a population was studied; thus, the shape of its frequency distribution could be verified. An uncertainty estimative of the method is presented together with the discussion of its usage difficulties.

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“…Figure 4 shows the histograms of the observed data. The analysis also included datasets collected during a semi-announced evacuation trial in a school building [16,17] (i.e. students had no warning, while the teaching staff had some prior warning in the trial).…”

Section: Datasetsmentioning

confidence: 99%

“…Datasets are usually presented in the following format: average, standard deviation, maximum and minimum values. Information such as sample sizes, data collection techniques and the background conditions are occasionally provided [16,17]. Nevertheless, in most cases, neither the raw data is available nor the type of PDF is defined.…”

Section: Introductionmentioning

confidence: 99%

A Method to Assess the Accuracy of Pseudo-Random Number Sampling Methods from Evacuation Datasets

et al. 2018

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We propose a method for assessing the accuracy of Pseudo-random Number Sampling Methods (PNSMs) for evacuation modelling purposes. It consists of a systematic comparison between experimental and generated distributions. The calculated weighted relative error (Ew_rel) is based on the statistical parameters as central moments (mean, standard deviation, skewness and kurtosis) to shape the distribution. The case study involves the Box Muller transform, the Kernel-Epanechnikov, the Kernel-Gaussian and the Picewise linear generating samples from eight evacuation datasets fitted against normal, lognormal and uniform distributions. Keeping in mind that the Bos Muller method has two potential sources of error (i.e. distribution fitting and sampling), this method produces plausible results when generating samples from the three types of distributions (Ew_rel < 0.30 for normal, lognormal and uniform distributions). We also fund that the Kernel Gaussian and the Kernel Epanechnikov methods are well accurate in generating samples from normal distributions (Ew_rel < 0.1) but potentially inaccurate when generating samples from uniform and lognormal distributions (Ew_rel > 0.80). Results suggest that the Picewise linear is the most accurate method (Ew_rel = 0.01 normal; Ew_rel = 0.04 lognormal; Ew_rel = 0.009 uniform). This method has the advantage of sampling directly from empirical datasets i.e. no previous distribution fitting is needed. While the proposed method is used here for evacuation modelling, it can be extended to other fire safety engineering applications.

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School egress data: comparing the configuration and validation of five egress modelling tools

Cited by 34 publications

References 11 publications

Evacuation Data from a Hospital Outpatient Drill The Case Study of North Shore Hospital

Evacuation Data from a Hospital Outpatient Drill The Case Study of North Shore Hospital

Method for collecting data of children descending movement on stairs in schools

A Method to Assess the Accuracy of Pseudo-Random Number Sampling Methods from Evacuation Datasets

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