What a User should Know when Selecting an Evacuation Model

In recent years, evacuation models have been increasingly applied in an attempt to understand the outcome of emergency egress scenarios

More thoughts on defaults

The developers of models used to simulate the evacuation from fire events, referred to here as egress models, are in a difficult position. It is in their interest to develop models that are quick and easy to employ, especially given the profusion of models and the expansion of application opportunities. At the same time, it is also in the model developers’ interest to reduce model misuse by inexpert users. Model misuse is characterized here as instances where results are produced through the use of inappropriate data and/or behavioural settings, which can lead to the generation of inappropriate or incredible results. While the authors advocate for the proper use of egress models in quantifying egress performance of a building design, the authors of this article are sceptical advocates of egress models, particularly in their design, their use in regulatory guidance, and the expertise of users. This paper represents an attempt to promote the proper use of egress models by suggesting a means to combat accidental model misuse. Previous work by the authors of this paper considered the availability of default values in simulation tools, and in particular egress models, and their potential for contributing to model misuse. Here, the term ‘default’ relates to a pre-set, fixed value (or distribution) for a parameter (e.g. the value for unimpeded walking speed) or the application of a specific behavioural algorithm in the model (e.g. agents travel along the path to their nearest exit). While the inclusion of default values enables out-of-the-box use of models without in-depth familiarization with input formats and data structures, defaults often represent optimistic and even unrealistic evacuation conditions or occupant behaviour, which can lead to model misuse. Most egress models provide default values for five core behavioural elements: pre-evacuation time, travel speeds, route usage and availability, and flow conditions. These five core behavioural elements typically need to be represented in order for the model to function at all. The authors suggest that bounding default settings, rather than optimistic values, should be provided for each of the core behavioural elements. In the context of this article, a bounding default setting is a value derived from relevant empirical data that prolongs the overall evacuation time produced for a particular design. If the model user wishes to decrease the conservative nature of a particular estimate or set of estimates, which will almost certainly be the case, he/she would then be required to explicitly justify the modification of the bounding default value. This approach then allows the immediate use of the model, but in effect forces the user to modify the settings in order to obtain a credible scenario for the purposes of design. These bounding values are not presented as values typically used in engineering scenarios. They are instead presented as values that would produce conservative results if used and would therefore typically require the user to modify the values in order to represent the scenario of interest. The bounding values suggested are therefore deliberately conservative in order to ensure both user intervention and user justification of this intervention to third parties reviewing the engineering process. The approach presented is designed to support model developers in their desire to have potential engineers use the model out-of-the-box, encouraging training and familiarization efforts, while aiding third party reviewers of the results, allowing them to compare any parameters employed with an accepted set of bounding parameter values. The use of bounding model default parameters is presented as an initial step in addressing accidental model misuse, with the acknowledgement that it would need to be refined and developed. However, this approach might also be integrated into other more substantive regulatory and licensing efforts should they be instigated

Pre-warning delay - staff response in emergencies

The pre-warning phase refers to the time between the start of an emergency incident and the raising of a general alarm to notify building occupants. This represents a delay in staff response as they interpret the cues available and determine the actions required. In some cases, the delay can be significant. In addition human errors can occur and procedural actions may need to be completed, causing additional delay and potentially complicating the notification process. The pre-warning concept and its theoretical basis were discussed in a previous paper by Gwynne et al (2010). In this paper, the concept is expanded with its application being extended from fires to other emergencies. An attempted is made to identify the general human activities that could be involved in pre-warning and to characterise the associated time delay. Examples of real incidents and drills are presented to illustrate the significance of this concept and the impact pre-warning delay and human errors could have upon the incident outcomes. The need for further research is also highlighted

Traffic dynamics during the 2019 Kincade wildfire evacuation

Traffic models are a useful tool for evacuation planning and management in case of wildfires. Despite the availability of several evacuation models, the number of datasets that can be used for their calibration and validation is limited. This paper presents key traffic flow data collected during the 2019 Kincade Fire. The data (69 116 data points from 24 locations) have been sourced from the Performance Measurement System of the California Department of Transportation. A set of commonly used models that describe the relationships between speed, flow and density has been fit to the data and compared to the model from the Highway Capacity Manual. In evacuation scenarios, the vehicle speed is about 3.5 km/h lower in comparison with the speed in routine scenarios, both for low and high traffic density. This demonstrates that dedicated models are needed for an accurate estimation of traffic evacuation times

The simulation of wildland-urban interface fire evacuation : The WUI-NITY platform

Wildfires are a significant safety risk to populations adjacent to wildland areas, known as the wildland-urban interface (WUI). This paper introduces a modelling platform called WUI-NITY. The platform is built on the Unity3D game engine and simulates and visualises human behaviour and wildfire spread during an evacuation of WUI communities. The purpose of this platform is to enhance the situational awareness of responders and residents during evacuation scenarios by providing information on the dynamic evolution of the emergency. WUI-NITY represents current and predicted conditions by coupling the three key modelling layers of wildfire evacuation, namely the fire, pedestrian, and traffic movement. This allows predictions of evacuation behaviour over time. The current version of WUI-NITY demonstrates the feasibility and advantages of coupling the modelling layers. Its wildfire modelling layer is based on FARSITE, the pedestrian layer implements a dedicated pedestrian response and movement model, and the traffic layer includes a traffic evacuation model based on the Lighthill-Whitham-Richards model. The platform also includes a sub-model called PERIL that designs the spatial location of trigger buffers. The main contribution of this work is in the development of a modular and model-agnostic (i.e., not linked to a specific model) platform with consistent levels of granularity (allowing a comparable modelling resolution in the representation of each layer) in all three modelling layers. WUI-NITY is a powerful tool to protect against wildfires; it can enable education and training of communities, forensic studies of past evacuations and dynamic vulnerability assessment of ongoing emergencies