Scalable context-dependent analysis of emergency egress models

  1. Lookup NU author(s)
  2. Professor Michael Harrison
Author(s)Massink M, Latella D, Bracciali A, Harrison MD, Hillston J
Publication type Article
JournalFormal Aspects of Computing
Year2012
Volume24
Issue2
Pages267-302
ISSN (print)0934-5043
ISSN (electronic)1433-299X
Full text is available for this publication:
Pervasive environments offer an increasing number of services to a large number of people moving within these environments, including timely information about where to go and when, and contextual information about the surrounding environment. This information may be conveyed to people through public displays or direct to a person’s mobile phone. People using these services interact with the system but they are also meeting other people and performing other activities as relevant opportunities arise. The design of such systems and the analysis of collective dynamic behaviour of people within them is a challenging problem. We present results on a novel usage of a scalable analysis technique in this context. We show the validity of an approach based on stochastic process-algebraic models by focussing on a representative example, i.e. emergency egress. The chosen case study has the advantage that detailed data is available from studies employing alternative analysis methods, making cross-methodology comparison possible. We also illustrate how realistic, context-dependent human behaviour, often observed in emergency egress, can naturally be embedded in the models, and how the effect of such behaviour on evacuation can be analysed in an efficient and scalable way. The proposed approach encompasses both the agent modelling viewpoint, as system behaviour emerges from specific (discrete) agent interaction, and the population viewpoint, when classes of homogeneous individuals are considered for a (continuous) approximation of overall system behaviour.
PublisherSpringer
URLhttp://dx.doi.org/10.1007/s00165-011-0188-1
DOI10.1007/s00165-011-0188-1
Actions    Link to this publication