Ucgis Summer 09 Final

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Ucgis Summer 09 Final

  1. 1. Autonomous Urban Agents: a Santa Fe Approach to City Knowledge Stephen Guerin Redfish Group / Santa Fe Complex Fabio Carrera WPI / MIT
  2. 2. WPI.EDU FORMAURBIS.COM REDFISH.COM SIMTABLE.COM SFCOMPLEX.ORG
  3. 3. Steve Fabio S+F Pipedreams
  4. 4. Steve Fabio S+F Pipedreams
  5. 5. Complexity theory Autonomous agent modeling Ambient computing
  6. 6. Complexity theory Autonomous agent modeling Ambient computing
  7. 7. Flocking and swarming Josh Thorp, stigmergic.net
  8. 8. Ants and Pheromones
  9. 9. Complexity theory Autonomous agent modeling Ambient computing
  10. 10. Complexity theory Autonomous agent modeling Ambient computing
  11. 11. Zozobra crowd dynamics
  12. 12. Pedestrian evacuations
  13. 13. Crowd Egress from Pittsburgh’s PNC Park
  14. 14. DC Metro Subway
  15. 15. Empirical Traffic Flows for Calibration 8000 9000 7000 8000 6000 7000 6000 5000 Traffic Volume Traffic Volume 5000 4000 4000 3000 3000 2000 2000 1000 1000 0 0 00:00 - 01:00 04:00 - 05:00 08:00 - 09:00 12:00 - 13:00 16:00 - 17:00 20:00 - 21:00 9/1/2006 9/5/2006 9/9/2006 9/13/2006 9/17/2006 9/21/2006 Date Time of Day Left Turn Thru 1 Thru 2 Thru 3 0 0 0 0 0 0 Left Turn Thru 1 Thru 2 Thru 3 0 0 0 0 0 0
  16. 16. Cova, T.J., and Church, R.L. (1997) Modelling community evacuation vulnerability using GIS. International Journal of Geographical Information Science, 11(8): 763-784 Cova, T.J., and Johnson, J.P. (2002) Microsimulation of neighborhood evacuations in the urban-wildland interface. Environment and Planning A, 34(12): 2211-2229 Cova, T.J., and Johnson, J.P. (2003) A network flow model for lane-based evacuation routing. Transportation Research Part A: Policy and Practice, 37(7): 579-604 Cova, T.J. (2005) Public safety in the urban-wildland interface: Should fire-prone communities have a maximum occupancy? Natural Hazards Review, 6(3): 99-108 Cova, T.J., Dennison, P.E., Kim, T.H., and Moritz, M.A. (2005) Setting wildfire evacuation trigger-points using fire spread modeling and GIS. Transactions in GIS, 9(4): 603-617
  17. 17. Complexity theory Autonomous agent modeling Ambient computing
  18. 18. Complexity theory Autonomous agent modeling Ambient computing
  19. 19. Run applet and download code at http://www.sandtable.org
  20. 20. Reality Mining MIT Reality Mining with Nathan Eagle
  21. 21. Steve Fabio S+F Pipedreams
  22. 22. Steve Fabio S+F Pipedreams
  23. 23. 1961-1977 ½ Ma 1977-1978 1978 -1988 ½ Ve 1988 - 2008 1996 - 2004 ½ SFe 2007 -
  24. 24. Venice Project Center Visual perception and preference City Knowledge
  25. 25. Venice Project Center Visual perception and preference City Knowledge
  26. 26. Venice Project Center •Founded in 1988 •500+ alumni •125+ projects •10+ Awards •15+ Major media stories
  27. 27. Worldwide Recognition 10/2003
  28. 28. National Geographic Video Channel: National Geographic Video Series Title: Out There Program Title: City under Siege Aired around the world: 2002-today
  29. 29. National Geographic Video
  30. 30. 20th Anniversary of VPC • Web page • Blog • Venipedia (wiki) • Alumni Network (ning) • Project Repository (Dspace)
  31. 31. Venice Project Center Visual perception and preference City Knowledge
  32. 32. Visual perception & preference •Original MIT dissertation •Why do we like/dislike cities? •Structures and Activities •How Carl Steinitz changed my life
  33. 33. Venice Project Center Visual perception and preference City Knowledge
  34. 34. City Knowledge
  35. 35. Premises of CK  Municipalities are the locus of change  Cities = Structures + Activities  Reality = Backlog + Future Change  Space Is the Glue  Middle-out = Top-down + Bottom-up  Government only has 6 tools for implementation and data collection
  36. 36. Premises of CK  Municipalities are the locus of change   Cities = Structures + Activities Like politics, “all change is local”   Reality = is filtered/allowed by municipalities Change Backlog + Future Change   Space Is the Glue with CK:  Middle-out = Top-down information strategies  City departments implement + Bottom-up  Government onlyfarmed-in at a fine grain  Urban information is has 6 tools for  Documentation becomes Information implementation and data collection  Intra- and Inter-departmental sharing is commonplace  Regional patterns (SDI) emerge upon municipal foundations
  37. 37. Premises of CK  Municipalities are the locus of change  Cities = Structures + Activities  Reality = Backlog stable and permanent  Structures are more + Future Change Space Is the Glue   Structural change can be captured as it occurs  Activities are more dynamic and fickle  Middle-out = Top-down + Bottom-up   Activities can be frozen in time tools for (snapshots) Government only has 6 and space with CK:  implementation and data collection  Information about structures is routinely updated  Activities are “spatialized”  Activities are periodically frozen
  38. 38. Premises of CK  Municipalities are the locus of change  Cities = Structures + Activities  Reality = Backlog + Future Change   Spaceis atheof “reality” already out there… There Is lot Glue  Middle-out = Top-down + Bottom-up  But the amount of information is finite  Government only can be completely captured  with CK the backlog has 6 tools for  implementationrather data collection Urban change is and slow so, with CK  all Structural change is captured at the source  snapshots of activities are creatively obtained  with CK, municipal information is “farmed” daily
  39. 39. Premises of CK  Municipalities are the locus of change  Cities = Structures + Activities  Reality = Backlog + Future Change  Space Is the Glue   Middle-out = Top-down + Bottom-up within CK:  Government key role in municipal information farming  Space plays a only has 6 tools for implementation andprimary spatial identifiers  Addresses are no longer data collection  GIS means Geographic Indexing Systems  Space indexes our datasets
  40. 40. Premises of CK  Municipalities are the locus of change  Cities = Structures + Activities  Reality = Backlog + Future Change  Space Is the Glue  Middle-out = Top-down + Bottom-up   Government only has 6structured… Top-down is rigorous and tools for implementation an “imposition”collection … but is received as and data and resisted  Bottom-up is passionate and self-interested… … but unstructured, unscalable and unsustainable  with CK:  Pure top-down and bottom-up approaches disappear  Middle-out combines the positive traits of both
  41. 41. Premises of CK 1. Ownership & Operation 2. Regulation  Municipalities are the locus of change 3. Incentives/Disincentives  Cities = Structures + Activities 4. Education & Information  Reality = Backlog + Future Change 5. Rights  Space Is the Glue 6. Mitigation & Compensation  Middle-out = Top-down + Bottom-up  Government only has 6 tools for implementation and data collection  with CK:  Municipalities consciously & creatively combine the 6 tools for  Information Farming  Policy/Plan Implementation
  42. 42. City Knowledge and Santa Fe  Presentation in 2007  Santa Fe Institute WPI Connection  Nicholas De Monchaux  Meeting Redfish – Steve Guerin  The WPI Santa Fe Project Center
  43. 43. Steve Fabio S+F Pipedreams
  44. 44. Steve Fabio S+F Pipedreams
  45. 45. Venice Simtable (EU Mobilis) Energence NASA DEW Ideagroup Marco Polo Airport
  46. 46. Marco Polo Airport Interactive Dynamic Master Planning
  47. 47. Steve Fabio S+F Pipedreams
  48. 48. High-order geovisual primitives Piping downhill Autonomous Urban Agents
  49. 49. High-order geovisual primitives Piping downhill Autonomous Urban Agents
  50. 50. Filaments Threads Fabrics Tree Maps Geospatial SFI graph
  51. 51. High-order geovisual primitives Piping downhill Autonomous Urban Agents
  52. 52. Visuals beyond GIS Connecting the dots Do your best and pipe the rest!
  53. 53. High-order geovisual primitives Piping downhill Autonomous Urban Agents
  54. 54. Mobile agents Structure agents Birth Certificates A new paradigm?
  55. 55. Fabio carrera@wpi.edu venice2point0.blogspot.com venice2point0.org www.wpi.edu/~carrera Steve stephen.guerin@redfish.com www.redfish.com www.sfcomplex.org

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