10,657 research outputs found
Cloud Enabled Emergency Navigation Using Faster-than-real-time Simulation
State-of-the-art emergency navigation approaches are designed to evacuate
civilians during a disaster based on real-time decisions using a pre-defined
algorithm and live sensory data. Hence, casualties caused by the poor decisions
and guidance are only apparent at the end of the evacuation process and cannot
then be remedied. Previous research shows that the performance of routing
algorithms for evacuation purposes are sensitive to the initial distribution of
evacuees, the occupancy levels, the type of disaster and its as well its
locations. Thus an algorithm that performs well in one scenario may achieve bad
results in another scenario. This problem is especially serious in
heuristic-based routing algorithms for evacuees where results are affected by
the choice of certain parameters. Therefore, this paper proposes a
simulation-based evacuee routing algorithm that optimises evacuation by making
use of the high computational power of cloud servers. Rather than guiding
evacuees with a predetermined routing algorithm, a robust Cognitive Packet
Network based algorithm is first evaluated via a cloud-based simulator in a
faster-than-real-time manner, and any "simulated casualties" are then re-routed
using a variant of Dijkstra's algorithm to obtain new safe paths for them to
exits. This approach can be iterated as long as corrective action is still
possible.Comment: Submitted to PerNEM'15 for revie
OpenKnowledge at work: exploring centralized and decentralized information gathering in emergency contexts
Real-world experience teaches us that to manage emergencies, efficient crisis response coordination is crucial; ICT infrastructures are effective in supporting the people involved in such contexts, by supporting effective ways of interaction. They also should provide innovative means of communication and information management. At present, centralized architectures are mostly used for this purpose; however, alternative infrastructures based on the use of distributed information sources, are currently being explored, studied and analyzed. This paper aims at investigating the capability of a novel approach (developed within the European project OpenKnowledge1) to support centralized as well as decentralized architectures for information gathering. For this purpose we developed an agent-based e-Response simulation environment fully integrated with the OpenKnowledge infrastructure and through which existing emergency plans are modelled and simulated. Preliminary results show the OpenKnowledge capability of supporting the two afore-mentioned architectures and, under ideal assumptions, a comparable performance in both cases
Mean-Field-Type Games in Engineering
A mean-field-type game is a game in which the instantaneous payoffs and/or
the state dynamics functions involve not only the state and the action profile
but also the joint distributions of state-action pairs. This article presents
some engineering applications of mean-field-type games including road traffic
networks, multi-level building evacuation, millimeter wave wireless
communications, distributed power networks, virus spread over networks, virtual
machine resource management in cloud networks, synchronization of oscillators,
energy-efficient buildings, online meeting and mobile crowdsensing.Comment: 84 pages, 24 figures, 183 references. to appear in AIMS 201
The discrete dynamics of small-scale spatial events: agent-based models of mobility in carnivals and street parades
Small-scale spatial events are situations in which elements or objects vary in such away that temporal dynamics is intrinsic to their representation and explanation. Someof the clearest examples involve local movement from conventional traffic modelingto disaster evacuation where congestion, crowding, panic, and related safety issue arekey features of such events. We propose that such events can be simulated using newvariants of pedestrian model, which embody ideas about how behavior emerges fromthe accumulated interactions between small-scale objects. We present a model inwhich the event space is first explored by agents using ?swarm intelligence?. Armedwith information about the space, agents then move in an unobstructed fashion to theevent. Congestion and problems over safety are then resolved through introducingcontrols in an iterative fashion and rerunning the model until a ?safe solution? isreached. The model has been developed to simulate the effect of changing the route ofthe Notting Hill Carnival, an annual event held in west central London over 2 days inAugust each year. One of the key issues in using such simulation is how the processof modeling interacts with those who manage and control the event. As such, thischanges the nature of the modeling problem from one where control and optimizationis external to the model to one where this is intrinsic to the simulation
Encoding natural movement as an agent-based system: an investigation into human pedestrian behaviour in the built environment
Gibson's ecological theory of perception has received considerable attention within psychology literature, as well as in computer vision and robotics. However, few have applied Gibson's approach to agent-based models of human movement, because the ecological theory requires that individuals have a vision-based mental model of the world, and for large numbers of agents this becomes extremely expensive computationally. Thus, within current pedestrian models, path evaluation is based on calibration from observed data or on sophisticated but deterministic route-choice mechanisms; there is little open-ended behavioural modelling of human-movement patterns. One solution which allows individuals rapid concurrent access to the visual information within an environment is an 'exosomatic visual architecture" where the connections between mutually visible locations within a configuration are prestored in a lookup table. Here we demonstrate that, with the aid of an exosomatic visual architecture, it is possible to develop behavioural models in which movement rules originating from Gibson's principle of affordance are utilised. We apply large numbers of agents programmed with these rules to a built-environment example and show that, by varying parameters such as destination selection, field of view, and steps taken between decision points, it is possible to generate aggregate movement levels very similar to those found in an actual building context
Routing Diverse Evacuees with Cognitive Packets
This paper explores the idea of smart building evacuation when evacuees can
belong to different categories with respect to their ability to move and their
health conditions. This leads to new algorithms that use the Cognitive Packet
Network concept to tailor different quality of service needs to different
evacuees. These ideas are implemented in a simulated environment and evaluated
with regard to their effectiveness.Comment: 7 pages, 7 figure
Intelligent evacuation management systems: A review
Crowd and evacuation management have been active areas of research and study in the recent past. Various developments continue to take place in the process of efficient evacuation of crowds in mass gatherings. This article is intended to provide a review of intelligent evacuation management systems covering the aspects of crowd monitoring, crowd disaster prediction, evacuation modelling, and evacuation path guidelines. Soft computing approaches play a vital role in the design and deployment of intelligent evacuation applications pertaining to crowd control management. While the review deals with video and nonvideo based aspects of crowd monitoring and crowd disaster prediction, evacuation techniques are reviewed via the theme of soft computing, along with a brief review on the evacuation navigation path. We believe that this review will assist researchers in developing reliable automated evacuation systems that will help in ensuring the safety of the evacuees especially during emergency evacuation scenarios
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