Skip navigation

Implementing a hybrid spatial discretisation within an agent based evacuation model

Implementing a hybrid spatial discretisation within an agent based evacuation model

Chooramun, Nitish (2011) Implementing a hybrid spatial discretisation within an agent based evacuation model. PhD thesis, University of Greenwich.

[img] PDF
Nitish_Chooramun_2011.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (10MB)

Abstract

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.

Item Type: Thesis (PhD)
Additional Information: uk.bl.ethos.549229
Uncontrolled Keywords: buildingEXODUS, evacuation modelling, hybrid spatial discretisation,
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA76 Computer software
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis > Fire Safety Engineering Group
School of Computing & Mathematical Sciences > Department of Mathematical Sciences
Related URLs:
Last Modified: 23 Mar 2017 10:11
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/8073

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics