RBSim 2

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RBSim 2
Monitoring and Management of Visitor Flows
in Recreational and Protected Areas January 30
February 2, 2002 Vienna, Austria

• Simulating the Complex Interactions Between Human
  Movement and the Outdoor Recreation environment

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Authors

• Robert Itami GeoDimensions Pty Ltd
• Rob Raulings eFirst
• Glen MacLaren GeoDimensions Pty Ltd
• Kathleen Hirst GIS Applications Pty Ltd
• Randy Gimblett University of Arizona
• Dino Zanon Parks Victoria
• Peter Chladek Parks Victoria

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RBSim 2 Recreation Behaviour Simulation

• Simulates human behaviour on linear recreation
  networks
• Allows recreation managers to test alternative
  management scenarios
• Simulates the interactions between
• Management actions
• Environmental conditions
• Human behaviour
• Generates statistical outputs to measure
  performance of a scenario against management
  objectives.

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RBSim technology framework

• RBSim integrates two technologies
• Geographic Information Systems (GIS) to capture
  environmental conditions and recreation
  facilities
• Intelligent agents to simulate human behaviour

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RBSim imports environmental data from GIS

• Road and Trail networks
• Facility locations (Parking lots, Visitor
  Centres, camp grounds)
• Facility attributes (visitor capacity, typical
  visit duration, site qualities)
• Elevation data (used to calculate slope, and
  intervisibility)

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Humans are modeled as Intelligent Autonomous
Agents

• An Autonomous agent is a system situated within
  and part of an environment that senses that
  environment and acts on it, over time, in pursuit
  of its own agenda and so as to affect what it
  senses (and acts on) in the future.
• Franklin and Graessner(1996)

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RBSim Simulation Architecture

• Object oriented
• Component based
• Modeled on reality

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RBSim Object Model
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Road and Trail Network

• Links road speed, slope, width, surface, travel
  restrictions
• Nodes Facilities, Capacities, Site Qualities

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Global Events

• Event Name
• Event Start Time
• Event End Time

Event Rain storm Start time 415pm End Time
430pm
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Arrival Curves

• Arrival Curves plot arrival rates for each
  entrance for each travel mode over a 24 hour day.

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Agents

• Agent Travel Modes
• Cars
• Buses
• Helicopters
• Pedestrian
• Agent Personality Preferences for site
  attractions
• Agent Rules
• Trip Planning Logic

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Agent Rules

• Rules are comprised of triggers or events
  generated by changes in the internal state of the
  agent, changes in the network or changes in
  global events.
• The behavior generated by a rule causes the agent
  to find a new path to the facility.

IF Travelmode car AND Locale 12
Apostles AND LocaleEntry True THEN Find Carpark
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Way Finding Logic of Agents

• Alternative paths are determined by
• Preferences for site attractions
• Travel Time to alternative destinations
• Time remaining in Agents trip
• The number of facilities along a trail that
  satisfies the current motivation list
• The available capacity of facilities.
• Agents use a combination of fuzzy logic, gravity
  models, network algorithms and rules to maxmise
  satisfaction and minimise travel time.

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Way finding Example Loch Ard Gorge
Because agents have different personalities,
level of fitness, and trip durations, the trip
planning logic results in different choice
behavior between agents.
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Typical Trips

• Entry and Exit nodes
• Destinations
• Arrival Curves
• Agent Type
• Mode of Travel

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Management Scenarios

• Scenarios allow managers to combine different
  network configurations, facilities, arrival rates
  and events to create a rich set of options.

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Simulation Engine

• Generates agents
• Executes event schedules such as opening and
  closing of gates, sunrise and sunset, and weather
  events.
• Schedules statistical outputs

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Example 12 Apostles Master plan

• Before and after simulation
• Visitor growth projected to 10 years
• Impact on facilities
• Impact on visitor satisfaction
• Impact on visitor movement patterns

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Crowding, lack of parking, long queues
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Scenarios

• Growth in visitor numbers
• Increase car and bus parking
• Relocate parking
• New Visitor Centre
• New toilet block
• Vehicular/Pedestrian separation

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Scenarios
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Simulation Runs
Scenario 1 Pre-master plan
Scenario 2 2001 Master plan
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Results

• Visitor duration
• Visitor Satisfaction
• Impact of visitor numbers on facility capacity

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Visitor duration
Previous Facility - 2001
Current Facility - 2001
Actual - Easter 2001
Actual - Easter 2001
(Average)

• RBSim accurately modelled the increase in visitor
  duration for the new masterplan.

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Visitor satisfaction Visual Encounters
Crowding at peak times increases dramatically in
2011
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Visitor Satisfaction crowding
Opening overflow parking causes crowding at
boardwalks
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Visitor Satisfaction Average queuing times for
parking
Average queuing times at car parks increase to
almost 2 minutes in 2011
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Facility Management available car parking
The car park is full from 100 PM TO 500 by 2006.
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Management recommendations

• Bus parking will need to be managed between 300
  pm to 500 pm within 5 years (eg. use informal
  spaces near the visitor centre).
• Limit car arrivals after 100 pm in 10 years or
  build an extension to the car park.
• Viewing platforms will have to be increased in
  capacity in the 5 to 10 year time horizon if the
  overflow car park is used or if the car park is
  extended further.

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Conclusions

• RBSim is an effective framework for examining the
  impacts of recreation infrastructure on visitor
  movement.
• Simulation provides a comprehensive tool for
  managing high use recreation settings.
• Simulation can assist managers in refining
  facility management plans and the impact on
  visitor flows and satisfaction.

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Future research - behaviour

• More behavioural research is required to validate
  choice behaviour for a wide range of recreator
  types and environmental settings.
• We hope to develop a library of agents that
  represent typical profiles and behaviour.
• Study the effectiveness of alternative management
  controls on behavioural outcomes.
• Study the management decision making process to
  determine most effective means of integrating
  simulation technology into the decision making
  process.

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Future R D - RBSim

• Add probabilistic rules
• Expose a wider range of simulation states for
  agent rules.
• Develop standard/automated statistical methods
  for summarizing simulation outputs.
• Link behavioural simulations to other
  environmental impact models.
• Develop new classes of agents.

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• The beginning