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UCGIS Summer Assembly
Autonomous Urban Agents: a Santa Fe Approach to City
Knowledge
Stephen GuerinRedfish Group / Santa Fe Complex
Fabio CarreraWPI / MIT
SFCOMPLEX.ORG
SIMTABLE.COM
REDFISH.COM
WPI.EDU
FORMAURBIS.COM
Parallel convergence
SteveFabioS+FPipedreams
Parallel convergence
SteveFabioS+FPipedreams
Steve
Complexity theoryAutonomous agent modelingAmbient computing
Steve
Complexity theoryAutonomous agent modelingAmbient computing
Josh Thorp, stigmergic.net
Flocking and swarming
Ants and Pheromones
Steve
Complexity theoryAutonomous agent modelingAmbient computing
Steve
Complexity theoryAutonomous agent modelingAmbient computing
Crowd dynamics
Zozobra crowd dynamics
Pedestrian evacuations
Crowd Egress from Pittsburgh’s PNC Park
Transportation modeling
DC Metro Subway
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Empirical Traffic Flows for Calibration
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
Wildfire modeling
“Time of Arrival” Map
Steve
Complexity theoryAutonomous agent modelingAmbient computing
Steve
Complexity theoryAutonomous agent modelingAmbient computing
Surface Scanning with Structured Light
Run applet and download code at http://www.sandtable.org
MIT Reality Mining with Nathan Eagle
Reality Mining
Parallel convergence
SteveFabioS+FPipedreams
Parallel convergence
Steve
FabioS+FPipedreams
Fabio
1961-1977
1978 -1988
1977-1978
1988 - 2008
1996 - 2004
2007 -
½ Ma
½ Ve
½ SFe
Fabio
Venice Project CenterVisual perception and preferenceCity Knowledge
Fabio
Venice Project CenterVisual perception and preferenceCity Knowledge
Venice Project Center
•Founded in 1988•500+ alumni•125+ projects•10+ Awards•15+ Major media stories
10/2003
8/1999
9/2002
8/2003 9/20039/2005
Worldwide Recognition
Channel: National Geographic VideoSeries Title: Out There Program Title: City under SiegeAired around the world: 2002-today
National Geographic Video
National Geographic Video
20th Anniversary of VPC
•Web page•Blog•Venipedia (wiki)•Alumni Network (ning)•Project Repository (Dspace)
Fabio
Venice Project CenterVisual perception and preferenceCity Knowledge
Visual perception & preference
•Original MIT dissertation•Why do we like/dislike cities?•Structures and Activities•How Carl Steinitz changed my life
Fabio
Venice Project CenterVisual perception and preferenceCity Knowledge
City Knowledge
transforming municipalities
from hunter-gatherers
to farmers of urban information
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
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
Like politics, “all change is local” Change is filtered/allowed by municipalities with CK:
City departments implement information strategies Urban information is farmed-in at a fine grain Documentation becomes Information Intra- and Inter-departmental sharing is commonplace Regional patterns (SDI) emerge upon municipal
foundations
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
Structures are more stable and permanent Structural change can be captured as it occurs
Activities are more dynamic and fickle Activities can be frozen in time and space (snapshots)
with CK: Information about structures is routinely updated Activities are “spatialized” Activities are periodically frozen
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
There is a lot of “reality” already out there… But the amount of information is finite with CK the backlog can be completely captured
Urban change is rather 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
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
within CK: Space plays a key role in municipal information
farming Addresses are no longer primary spatial identifiers GIS means Geographic Indexing Systems Space indexes our datasets
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 Top-down is rigorous and structured…
… but is received as an “imposition” 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
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
1. Ownership & Operation2. Regulation3. Incentives/Disincentives4. Education & Information5. Rights6. Mitigation & Compensation
with CK: Municipalities consciously & creatively combine the 6
tools for Information Farming Policy/Plan Implementation
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
Parallel convergence
SteveFabioS+FPipedreams
Parallel convergence
SteveFabio
S+FPipedreams
S + F
Venice Simtable (EU Mobilis)EnergenceNASA DEWIdeagroupMarco Polo Airport
ABM and Venice Boat Traffic
Canal Logistics Venice, Italy
Energence
Marco Polo AirportInteractive Dynamic Master Planning
Parallel convergence
SteveFabioS+FPipedreams
Pipedreams
High-order geovisual primitivesPiping downhillAutonomous Urban Agents
Pipedreams
High-order geovisual primitivesPiping downhillAutonomous Urban Agents
High-order geovisual primitives
FilamentsThreadsFabricsTree MapsGeospatial SFI graph
Pipedreams
High-order geovisual primitivesPiping downhillAutonomous Urban Agents
Piping downhill
Visuals beyond GISConnecting the dotsDo your best and pipe the rest!
Pipedreams
High-order geovisual primitivesPiping downhillAutonomous Urban Agents
Autonomous Urban Agents
Mobile agentsStructure agentsBirth CertificatesA new paradigm?
Fabiocarrera@wpi.eduvenice2point0.blogspot.comvenice2point0.orgwww.wpi.edu/~carrera
