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A Google-Map-Based Arterial Traffic Information (GATI) System

A Google-Map-Based Arterial Traffic Information (GATI) System. Authors: Yao-Jan Wu Dr. Yinhai Wang Dr. Dalin Qian. Date: 10/03/2007. Outline. Introduction System Architecture Database Design Implementation Conclusion and Future work. Introduction System Architecture

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A Google-Map-Based Arterial Traffic Information (GATI) System

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  1. A Google-Map-Based Arterial Traffic Information (GATI) System Authors: Yao-Jan Wu Dr. Yinhai Wang Dr. Dalin Qian Date: 10/03/2007

  2. Outline • Introduction • System Architecture • Database Design • Implementation • Conclusion and Future work

  3. Introduction • System Architecture • Database Design • Implementation • Conclusion and Future work

  4. Web Based Traffic Information System • Washington State Department of Transportation • Puget Sound Traffic Flow Map

  5. Google-based Traffic Information System • Seymour, E.J. Miller, B.(2007). Google-Based Mapping System for Traffic Management Center Web Navigation, TRB • http://daltrans.org/

  6. Arterial Traffic Information System • Bellevue Real-Time Traffic Map • Not in right scale • Less interactive • Research? Source: http://www.ci.bellevue.wa.us/

  7. Introduction • System Architecture • Database Design • Implementation • Conclusion and Future work

  8. System Architecture STAR Lab

  9. Introduction • System Architecture • Database Design • Traffic Data from the City of Bellevue • Pre-process • Implementation • Conclusion and Future work

  10. Traffic Data from the City of Bellevue • The city of Bellevue [Liang, 2006] • 177 signalized intersections • More than 840 advance detector • Around 465 links (varied).

  11. Pre-process • Locate all intersections (nodes) • Build up link-intersection relation table • Import Data into Database • Link Data • Intersection Data • Traffic Data

  12. Incident code Link ID Smooth Occupancy Plan # running Link # Smooth Volume Cycle length Color code Traffic Data • All link data • One minute update file (with all the links for the flow map) • Filename name: 0607121314.csv

  13. Incident code Link ID Smooth Occupancy Plan # running Link # Smooth Volume Cycle length Color code All link data • Link description • Fxxxddmn (e.g. F001EBT1) • xxx= Intersection # • dd= Direction (EB, WB, NB, SB) • m= Movement: (L)eft, (T)hru, (R)ight • n= # of lanes

  14. Weekday Link ID volume Volume+K Plan# Link Description Occupancy Cycle length Date Time Color code All link data • Color code [Liang, 2006] • 1,2=green (light) • 3=yellow (Moderate) • 4=red (Heavy) • 5=black (Severe) • 0=gray (No data)

  15. Locate all intersections • Saving Data with GXmlHttp (Ajax!) • Do it manually with reference to the Map of Signalized Intersection

  16. All Intersections

  17. Incident code Link ID Smooth Occupancy Plan # running Link # Smooth Volume Cycle length Color code Build up link-intersection relation table • Do it manually with reference to the Map of Signalized Intersection

  18. Database • Three tables have to be built in MySQL database • Traffic data table • Link Data table • Link_Intersection table

  19. Relationships among tables

  20. Introduction • System Architecture • Database Design • Implementation • Conclusion and Future work

  21. Interface

  22. Flowchart

  23. FTP Downloader • Functions • Data Downloading • Generate real-time XML data • Update database • Archive data feeds

  24. Traffic Flow Map

  25. Conclusion and Future Work • Conclusion • Low cost (MySQL, Apache server, PHP, etc) • Easy to implement • Future work • More traffic information can be shown • Analytical tools • Versatile Query Real-time evaluation (Arterial, network) functions

  26. More Info • STAR Lab (http://www.uwstarlab.org/)

  27. 2008 TRB Annual Meeting Washington D.C. • GATI Ver.2

  28. Questions? yaojan@u.wasington.edu

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