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Integrating spatio-temporal data in agent-based simulations for emergency navigation support

Zhiyong Wang

In cooperation with Sisi Zlatanova

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Content

Background

Research question

Research methodology

The prototype system architecture

Use cases

Data and software

Proposed timetable

Planned Publications

Disaster management and Emergency navigation

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Pros and cons of GIS tools

Pros

database management

spatial analysis

geographical visualization

……….

Cons

dynamic modelling

simulation

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Agent based Modeling of Simulation

Agent is: - a piece of code to describe dynamic phenomena (moving people, events, plume...) An agent-based model (ABM) is: - a class of computational models - provides simulation of actions and interactions of autonomous agents (both individual or groups)

The goal is assessing effects on the dynamic system as a whole (e.g. disaster management, evacuation, natural phenomena, etc. )

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Examples of Agent-based modeling

http://www.xjtek.com/anylogic/demo_models/11/

Predator Prey model Swarm following the leader

http://www.youtube.com/watch?v=f510pmahpE8

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Pros and cons of Agent Model simulation

Pros

Complex dynamics

Behavior and interaction between agents

Prediction

……….

Cons

Data used are mostly simulated(no real data)

Predetermined model

Integration of GIS and Agent-Based Model Simulation

Agents and Networks: Commuting Arena Evacuation Simulation in EPT

http://www.youtube.com/watch?v=ixTiuLwlLSc&feature=related

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Deficiencies of the existing integration of ABM and GIS

Uses lacks real data

Uses real maps and 3D models but hardly real-time

data ( e.g. GPS tracks, plume movement)

Rigid input parameters

Predefined model (No correction)

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Dynamic Data Driven Application System (DDDAS)

DDDAS formulates simulation models and methods with:- dynamically measured data, - algorithms, - system tools, - mathematical and statistical advances

The challenges are: - how to incorporate additional data -how to dynamically steer the measurement process?

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Main Research question

Is integration of spatial data (static such as

2D/3D models and dynamic such as real time

measurements) into agent-based simulations

able to better support the emergency

navigation considering human movements and

moving disasters?

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The prototype system architecture

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1. Research questions related to GIS

What kind of information will be needed for agent-based simulation?

How to derive the network from these information

What kind of relationships between agents and spatio-temporal objects

will support the simulation?

What kind of data model should be used for management of the dynamic

data that includes the real-time data, the information of moving objects

(disasters, pedestrian, vehicles, etc.)

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2. Research questions related to Agents

How many types of agents should be developed?

What kind of user profile should be considered for route determination

under emergencies?

What kind of rules should be designed for agents to dictate their

behaviors?

How can we evaluate the behaviors of the agents(e.g. rescue vehicle

agent, etc.)?

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3. Research questions related to routing

What kind of routing algorithms should be considered?

What kind of re-routing strategy should be designed for the agent to avoid

obstacles and disasters?

How does the agent-based simulation system provide navigation services

for both first responders and citizens?

On what kind of network (2D and 3D) the algorithms will be run?

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4.Research questions to DDDAS

What kinds of real-time information can be incorporated into the

simulation model?

How to correct the agent-based model with real-time data?

How to verify and validate the developed simulation model?

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Research Methodology

Literature study and technology requirementsLiterature study and technology investigations Conceptual design1. Design a multi-agent simulation framework for moving objects (considering GPS tracks)2. Extend the multi-agent simulation network by considering disaster models (considering real measurements)

Implementationdeveloping prototypeValidation and AdaptationConduct tests in different scenarios Make improvement based on the test results.

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Use case 1: Agent-based modeling of human movements during disasters

Flee

Jam Different pattern s of human movements

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Demo 1: updating positions with GPS tracks

During the demo is running you have to explain in when GPS tracks will be used

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Use case 2: Agent-based approach for emergence navigation considering the dynamics of disasters

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Demo 2: moving plume updated with measurements obtained from the field

{position, type of geometry, moving speed, direction}

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Software and DataSoftware:Programing language: JavaProgramming tools: Eclipse, Java 3D, Java OpenGL Visualization tool: BentleyAgent-based modelling toolkit: REPAST, MASONDBMS: PostGIS or Oracel Spatial

Data: available 2D and 3D data

Year 1Literature study and technology investigationsCreate the agents for modeling the movements of rescuers corrected with GPS tracking Make predictions based on mathematical models Implement the data models for moving objects Test the prototype system in the road network Improve the system based on test resultsExtend the work into 3D environment

Proposed timetable

Year 2: Design and implement a multi-agent system for emergency navigation Connect the multi-agent simulation model with the disaster model Extend the work into 3D environment Year 3:Test the agent-based simulation system in different scenarios Improve the models of agents. Year 4Extend the work considering the disasters andcommunication between agentsAssess and improve our systems. Write the thesis.

Proposed timetable

Regular reports 2 or 3 conference papers per yeare.g. ISCRAM, AAMAS, DDDAS,UDMS etc.2 papers in reviewed scientific journalse.g. Computational Geosciences, Computers and Geosciences, international journal of emergency response

Planned publications

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Thanks for your attention!Any questions and suggestions?