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Visual Analytics for Large-Scale Travel Models
Daniel Florian |
dan@inrosoftware.com
Software for
transportation
forecasting,
traffic
simulation and
mobility
analytics
www.inrosoftware.com
Transportation
forecasting
Multiscale
Traffic Simulation
Visual analytics for large-
scale
spatial and mobility data
New Generation Travel Models
Travel models are increasingly
disaggregate
• 30 Activity Based Models (ABM)
underway in North America
• Tour-based models in Australia
• Generally increasing market
segmentation, temporal and spatial
resolution
Data produced is on a different scale:
• Seattle ABM ~ 3 million people, 14
million activities, 1.6 million parcels
• Phoenix ABM ~ 4 million people, 20
million activities, 26000 MAZs
Challenges
Working with disaggregate mobility
data
• Computationally intensive
 Processing
 Querying
 Visualizing
• Aggregations
 All aggregations result in data loss
 Time consuming
• Reproducibility
• Mobility vs Spatial
Large-scale Traffic Simulation Models
• Metropolitan to regional scale
• Higher realism/fidelity “operational”
models
• Desire to inform demand models with
traffic simulation
Data produced is on a different scale:
• San Francisco ~ 700,000 veh demand
• Seattle ~ 460,000 vehicles veh
demand
Other models and mobility data
• Passive mobility data collection
 AVL, AFC
 Cell, GPS
 Trajectories
• Commercial freight and goods data
• Household travel surveys
• Mobile phones -> demand
• Land-use models
• We need
 Methods to explore this data
 And tools to work with them efficiently
A Lot of Model Data Still Goes Unseen
• Meaningful data from models, but very disaggregate
Opportunities
• Validation and QA
• Decision support and planning with integrated models
• “Socialization” of models
Visual analytics for large-scale spatial and mobility data
• Animate large-scale data sets in 3D
• Explore, chart and analyze data through interactive visual
queries
• Detailed and responsive scenes at the metropolitan and
regional level with millions of geometries in the frame
• Filter, color, query, chart
• Reproducible visual analytics with Python
CityPhi
Software for
transportation
forecasting,
traffic
simulation and
mobility
analytics
www.inrosoftware.com
Transportation
forecasting
Multiscale
Traffic Simulation
Visual analytics for large-
scale
spatial and mobility data

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Visual Analytics for Large Scale Travel Models

  • 1. Visual Analytics for Large-Scale Travel Models Daniel Florian | dan@inrosoftware.com
  • 3. New Generation Travel Models Travel models are increasingly disaggregate • 30 Activity Based Models (ABM) underway in North America • Tour-based models in Australia • Generally increasing market segmentation, temporal and spatial resolution Data produced is on a different scale: • Seattle ABM ~ 3 million people, 14 million activities, 1.6 million parcels • Phoenix ABM ~ 4 million people, 20 million activities, 26000 MAZs
  • 4. Challenges Working with disaggregate mobility data • Computationally intensive  Processing  Querying  Visualizing • Aggregations  All aggregations result in data loss  Time consuming • Reproducibility • Mobility vs Spatial
  • 5.
  • 6.
  • 7.
  • 8.
  • 9. Large-scale Traffic Simulation Models • Metropolitan to regional scale • Higher realism/fidelity “operational” models • Desire to inform demand models with traffic simulation Data produced is on a different scale: • San Francisco ~ 700,000 veh demand • Seattle ~ 460,000 vehicles veh demand
  • 10.
  • 11.
  • 12. Other models and mobility data • Passive mobility data collection  AVL, AFC  Cell, GPS  Trajectories • Commercial freight and goods data • Household travel surveys • Mobile phones -> demand • Land-use models • We need  Methods to explore this data  And tools to work with them efficiently
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21. A Lot of Model Data Still Goes Unseen • Meaningful data from models, but very disaggregate Opportunities • Validation and QA • Decision support and planning with integrated models • “Socialization” of models
  • 22. Visual analytics for large-scale spatial and mobility data • Animate large-scale data sets in 3D • Explore, chart and analyze data through interactive visual queries • Detailed and responsive scenes at the metropolitan and regional level with millions of geometries in the frame • Filter, color, query, chart • Reproducible visual analytics with Python CityPhi