Implementing a hybrid spatial discretisation within an agent based evacuation model

Within all evacuation and pedestrian dynamics models, the physical space in which the agents move and interact is represented in some way. Models typically use one of three basic approaches to represent space namely a continuous representation of space, a fine network of nodes or a coarse network of nodes. Each approach has its benefits and limitations; the continuous approach allows for an accurate representation of the building space and the movement and interaction of individual agents but suffers from relative poor computational performance; the coarse nodal approach allows for very rapid computation but suffers from an inability to accurately represent the physical interaction of individual agents with each other and with the structure. The fine nodal approach represents a compromise between the two extremes providing an ability to represent the interaction of agents while providing good computational performance. This dissertation is an attempt to develop a technology which encompasses the benefits of the three spatial representation methods and maximises computational efficiency while providing an optimal environment to represent the movement and interaction of agents. This was achieved through a number of phases. The initial part of the research focused on the investigation of the spatial representation technique employed in current evacuation models and their respective capabilities. This was followed by a comprehensive review of the current state of knowledge regarding circulation and egress data. The outcome of the analytical phases provided a foundation for eliciting the failings in current evacuation models and identifying approaches which would be conducive towards the sophistication of the current state of evacuation modelling. These concepts led to the generation of a blueprint comprising of algorithmic procedures, which were used as input in the implementation phase. The buildingEXODUS evacuation model was used as a computational shell for the deployment of the new procedures. This shell features a sophisticated plug-in architecture which provided the appropriate platform for the incremental implementation, validation and integration of the newly developed models. The Continuous Model developed during the implementation phase comprises of advanced algorithms which provide a more detailed and thorough representation of human behaviour and movement. Moreover, this research has resulted in the development of a novel approach, called Hybrid Spatial Discretisation (HSD), which provides the flexibility of using a combination of fine node networks, coarse node networks and continuous regions for spatial representations in evacuation models. Furthermore, the validation phase has demonstrated the suitability and scalability of the HSD approach towards modelling the evacuation of large geometries while maximising computational efficiency

Investigating the application of a hybrid space discretisation for urban scale evacuation simulation

The devastating effects of wildfires cannot be overlooked; these include massive resettlement of people, destruction of property and loss of lives. The considerable distances over which wild fires spread and the rates at which these fires can spread is a major concern as this places considerable challenges on the evacuation mechanisms that need to be put in place. It is therefore crucial for personnel, involved in evacuation planning, to obtain reliable estimates of evacuation times faster than real time, to assist their decision making in response to actual unfolding of events. In this work, we present a hybrid approach, which we refer to as the Hybrid Spatial Discretisation (HSD) for large scale evacuation simulation. The HSD integrates the three spatial representation techniques typically used for representing space usage in evacuation models; namely Coarse regions, Fine nodes and Continuous regions. In this work, we describe the core models constituting the HSD coupled with the approaches used for representing the transition of agents across the different spatial types. Using a large scale case, we demonstrate how the HSD can be used to obtain higher resolution of results where it is most required while optimising the use of available computational resources for the overall simulation. The HSD is seen to provide improvements in run times of more than 40% when compared to modelling the whole area using just the Fine node method

An agent based evacuation model utilising hybrid space discretisation

Egress models typically use one of three methods to represent the physical space in which the agents move: coarse network, fine network or continuous. In this work, we present a novel approach to represent space, which we call the 'Hybrid Spatial Discretisation' (HSD), in which all three spatial representations can be utilised to represent the physical space of the geometry within a single integrated software tool. The aim of the HSD approach is to encompass the benefits of the three spatial representation methods and maximise computational efficiency while providing an optimal environment to represent the movement and interaction of agents