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Kvintus - an agent-based model of recreational behavior


Published on is an agent-based model of recreational behavior. It is based on Repast and Goggle Map.
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Published in: Technology
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Kvintus - an agent-based model of recreational behavior

  1. 1. Agent-based simulation of recreative behavior Kick off, MaFreiNa, Vienna July 8, 2008 Hans Skov-Petersen Forest & landscape Denmark University of Copenhagen [email_address] Acknowledgement of the project team: Bernhard Snizek and Pimin Kefaloukos
  2. 2. <ul><li>Agent-based models are based on individual software robots… </li></ul><ul><li>That have knowledge, objectives, affordances and abilities. </li></ul><ul><li>They can perceive and comprehend their environment (and each other) and </li></ul><ul><li>make (spatial) decisions on that basics. </li></ul><ul><li>ABM’s operate in discrete time steps </li></ul><ul><li>Randomness is applied to many involved processes </li></ul><ul><li>… accordingly two model runs will not result in exactly the same </li></ul>Definition of ABM
  3. 3. <ul><li>Situations/phenomena </li></ul><ul><li>Where the actions and behavior of individuals are known and the overall system is less understood </li></ul><ul><li>Where the behavior and attitudes of individuals are considered significant </li></ul><ul><li>Where the behavior and attitudes are expected to change manner during the model run </li></ul><ul><li>Where monitoring is impracticable to perform </li></ul><ul><li>Where a high degree of participant’s understanding is required </li></ul>Why ABM? <ul><li>Fields of application </li></ul><ul><li>Pedestrian behavior </li></ul><ul><li>Evacuation models </li></ul><ul><li>Traffic models </li></ul><ul><li>Models of recreational behavior </li></ul>
  4. 4. <ul><li>At each time step… </li></ul><ul><li>Time is checked, </li></ul><ul><li>entry points are checked, </li></ul><ul><li>agents are born, and </li></ul><ul><li>agents are perceiving, comprehending and reacting (moving) </li></ul>Time handling in ABM’s
  5. 5. <ul><li>Wildlife disturbance in Hestehaven/Ringelmosen </li></ul><ul><li>The problem in general </li></ul><ul><li>Expected applications of the model </li></ul>The present application
  6. 6. <ul><li>Visitor behavior </li></ul><ul><li>Field interviews </li></ul><ul><li>Sketch maps </li></ul><ul><li>Automatic counters </li></ul>Data sources Photo: Torben Lynge Madsen <ul><li>Animal (roe deer) behavior </li></ul><ul><li>GPS </li></ul><ul><li>Environment (GIS) – raster and vector.. </li></ul><ul><li>Path net work </li></ul><ul><li>Land cover </li></ul><ul><li>Terrain (DEM) </li></ul><ul><li>Entry points </li></ul><ul><li>And more… </li></ul>
  7. 7. <ul><li>The XML-file configuration </li></ul><ul><li>Base settings </li></ul><ul><li>Agent types </li></ul><ul><li>State types </li></ul><ul><li>Time tables </li></ul><ul><li>Entrypoints </li></ul>Simulation definition (the XML-file)
  8. 8. <ul><li>Base settings </li></ul><ul><li>Environmental data </li></ul><ul><li>Timing and scheduling </li></ul><ul><li>Output </li></ul>XML: Base settings
  9. 9. <ul><li>Fixed routes and way point navigation </li></ul><ul><li>Fixed location that have to be visited </li></ul><ul><li>Waiting at locations </li></ul><ul><li>Stray factors </li></ul>Visitor behavior (States and transitions) <ul><li>Browsing navigation (Choices made along the way) </li></ul><ul><li>Direction of path options </li></ul><ul><li>Nature type (land cover ) </li></ul><ul><li>Other agents in sight </li></ul>Stray factor: 1.2 <ul><li>Transitions can be: </li></ul><ul><li>Scheduled or </li></ul><ul><li>Event driven (*) </li></ul>
  10. 10. <ul><li>Options and requirements </li></ul><ul><li>Speed, mode (network or raster (*)) </li></ul><ul><li>Waypoints, strayfactors, weigths (*) </li></ul><ul><li>edgeChoiceFuntions, rasterChoiceFunctions (*) </li></ul><ul><li>Misc. choicefunctions (*) </li></ul><ul><li>Numeric- and categoricTransitionFunctions (*) </li></ul>XML: State definition Waypoint state Choice state
  11. 11. <ul><li>Misc. choicefunctions (*) </li></ul><ul><li>Slope </li></ul><ul><li>Angle to origon/destination </li></ul><ul><li>U-turn restrictions </li></ul><ul><li>Encounters with other agents </li></ul>XML: State definition <ul><li>Event transitionsfunctions (*) </li></ul><ul><li>Being scared by a visitor (animal agent) </li></ul><ul><li>Seeing a bench and sitting down </li></ul><ul><li>Encounters with other agents </li></ul><ul><li>Etc. </li></ul>
  12. 12. <ul><li>Options and requirements </li></ul><ul><li>Name, time availability </li></ul><ul><li>Scheduled states (relative to instantiation) </li></ul>XML: Agent types
  13. 13. <ul><li>Agents are created according to </li></ul><ul><li>A time table applied to the entire model and </li></ul><ul><li>Scales for each entry points </li></ul>Scheduling
  14. 14. <ul><li>Entrypoints </li></ul><ul><li>Name </li></ul><ul><li>Time table </li></ul><ul><li>Agent distribution </li></ul><ul><li>Scale </li></ul>XML: Entry points
  15. 15. <ul><li>Timetables </li></ul><ul><li>Name </li></ul><ul><li>Periods of two hours (agents are born randomly during the periods) </li></ul>XML: Time tables
  16. 16. <ul><li>Based on absolute schedules and.. </li></ul><ul><li>Ranges which refers to… </li></ul><ul><li>Activity types (states) which again are defined by… </li></ul><ul><li>Nature type preferences </li></ul><ul><li>… yet another feature to come </li></ul>Roe deer behavior
  17. 17. <ul><li>The logging tales place as </li></ul><ul><li>Summery of moods (an agent being encounters or not) at location </li></ul><ul><li>Use loads on network edges </li></ul><ul><li>Temporal profiles of mood summaries (a facility under construction) </li></ul>Logging and results Stray factor: 1.2
  18. 18. <ul><li>Google map based viewer </li></ul><ul><li>Powered by the generic ABM library REPAST ( </li></ul><ul><li>Background maps are based on Gmap </li></ul><ul><li>Agents are served by the model as WFS of Java Script Notation Objects (JSNO) </li></ul><ul><li>At present the server persists on a local host (no need to try to google it….) </li></ul>Run time visualization <ul><li>Hopes for the future… </li></ul><ul><li>Start/stop model from GUI </li></ul><ul><li>‘ Slow down’ model </li></ul><ul><li>Tracking of individual agents </li></ul><ul><li>Status information </li></ul><ul><li>XML-editing </li></ul><ul><li>Network (and other GIS-info) visible </li></ul><ul><li>Different color for different moods </li></ul>
  19. 19. Thank you for your attention EXIT Hans Skov-Petersen Forest & landscape Denmark University of Copenhagen [email_address] Acknowledgement of the project team: Bernhard Snizek and Pimin Kefaloukos (Kostas)
  20. 20. <ul><li>Visibility models applied to ABM’s </li></ul><ul><li>Simple distance (moor neighborhoods) </li></ul><ul><li>Simple view sheds (incl. distances) </li></ul><ul><li>Based on probabilities of visual contact given different land cover types </li></ul>Visual encounters I
  21. 21. <ul><li>Legend: </li></ul><ul><li>Yellow: Highly visible </li></ul><ul><li>Red: Poorly visible </li></ul><ul><li>Transparent: Invisible (due to terrain) </li></ul>Visual encounters II