The document discusses dynamic transportation data visualization. It defines dynamic data as being time- and space-sensitive, including real-time traffic data feeds, mobile GPS trajectory data, and simulation model outputs. It describes using open source tools like Google Earth, Python, and HDF5 databases to visualize this dynamic data through interactive maps and plots. Specific examples shown include GPS trajectories, origin-destination desire lines, traffic simulation outputs comparing build scenarios, and visualization of travel patterns across large regions. The document emphasizes that as transportation data grows, visualization is key to exploring and understanding travel behavior patterns revealed in the data.

1. Robert Tung, PhD
RST International
Metropia
TRB 2017 Annual Conference Visualization Lightning Talk
January 9, 2017 Washington D.C.

2.  Defining “Dynamic”:
◦ Time & Space sensitive
 Real Time, up-to-minute
 Type of Dynamic Data:
◦ Online real-time traffic data feed
 INRIX (region wide, link based)
◦ Mobile phone based GPS trajectory
 App based navigator & recorder (Metropia App)
◦ Simulation model outputs
 Meso-scopic DTA models (DynuStudio/DynusT)
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3.  Open Source & Open Format
◦ Google Earth + KML/KMZ
 High definition GIS & 3D mapping
◦ Python + matplotlib
 Easy mathematical & statistical plotting
◦ HDF5 database (Hierarchical Data Format)
 Efficient file storage & flexible API
◦ DynusT
 Powerful simulation DTA for large network
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9. GPS Trajectories
AM & PM OD Desire Lines
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10. Total Origins at TAZ
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11. RST | Metropia

12.  Congestion formation: Queues,
bottlenecks & gridlock
 Route choice changes due to operational
changes: incidents, work zones, tolling,
pricing, etc.
 Travel behavior changes in departure times
& O/D due to congestion and costs: ABM-
DTA integration
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13. RST | Metropia
No Build
Managed Lane

14. Created in DynuStudio
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15. Created in DynuStudio
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17. RST | Metropia
Created in DynuStudio

18. Total Coverage=850 SQ Miles
Created in DynuStudio
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19. Total Coverage=1300 SQ Miles
Created in DynuStudio
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20.  As we are entering “Data Rich” & “Big
Data” era, data analytics are increasingly
important
 Visualization is the heart of data
analytics for knowing & exploring the
underlying patterns of travel behaviors
 Effective visualization should be low
cost, creative & open format, with easy
data sharing
RST | Metropia

21. THANK YOU
rst@rstintl.net