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Southeast Michigan Council of Governments

Southeast Michigan Council of Governments. Development of a Traffic Count Database for Travel Model Calibration. Brian D. Mohr, Li-yang Feng, and Tom Bruff Southeast Michigan Council of Governments 11 th TRB Applications Conference Daytona Beach, FL May 7, 2007. * Detroit. St. Clair.

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Southeast Michigan Council of Governments

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  1. Southeast Michigan Council of Governments

  2. Development of a Traffic Count Database for Travel Model Calibration Brian D. Mohr, Li-yang Feng, and Tom Bruff Southeast Michigan Council of Governments 11th TRB Applications Conference Daytona Beach, FL May 7, 2007

  3. *Detroit

  4. St. Clair Macomb Oakland Livingston Washtenaw Wayne Monroe SEMCOG Region Communities: 234 Population:4.9 million Licensed drivers:3.4 million Annual VMT:49 billion Miles of road:23,000

  5. Presentation Overview Count source Regional traffic count database Travel model interface Model validation files Count source Count source

  6. Challenges • No consistency in count data format • No central database for storing counts • No efficient procedure for linking counts with model • No way to determine if counts sufficient for validation

  7. Solutions • Create regional traffic count database (RTCD) • Central repository for all counts • Source of counts for model, other apps • Create automated procedure for linking counts with model • Use power of GIS (linear referencing)

  8. RTCD Development Issues • Transferring data from multiple sources into common format • Michigan Department of Transportation (MDOT) • Local agencies (counties, cities) • Developing RTCD database structure • Coding counts with GIS attributes

  9. Traffic Count Database System (TCDS) • Software features • Web-based, friendly user interface • Direct uploading from traffic counters • Logical relational database structure • Numerous quality control measures • Provides SEMCOG easy access to counts from all seven counties, Detroit

  10. Importing MDOT’s Traffic Count Data • Challenges • Understanding MDOT’s count program • Three types of data: PTR, ITS, short counts • Different data format for each type • Solution: MDOT data conversion tool • Converts all data into common format • Flags “representative” PTR, ITS counts

  11. MDOT Data Conversion Tool

  12. SEMCOG’s Regional Traffic Count Database (RTCD) • Oracle database with three primary tables: • Count location descriptions • Counts • GIS (linear referencing) coding • Number of records in database • Locations: 28,080 • Counts available for validation: 58,750 • Total counts available: 342,049

  13. GIS (Linear Referencing) Coding • Counts coded with LRS attributes from base map (route/milepoint system) • All SEMCOG transportation data coded • Counts coded as segments Every point ( ) on road network represented by two coordinates: route number, milepoint Every count location ( ) represented by three coordinates: route number, beginning milepoint, ending milepoint

  14. Local agency counts (via TCDS) Regional Traffic Count Database (RTCD) Other counts MDOT counts (via conversion Tool)

  15. Local agency counts (via TCDS) Regional Traffic Count Database (RTCD) Travel model interface Model validation files Other counts MDOT counts (via conversion Tool)

  16. Model Validation File Creator • Required input • RTCD tables (locations, counts, GIS info) • TransCAD link definition table • Count alignment table • Desired statistical parameters • Output: data-based or model-based validation file

  17. Two Types of Model Validation Files • Data-based • Links assigned counts wherever possible • Not a statistically sound validation file • Model-based (statistical sample) • Links stratified by geographic area and functional class, sample randomly selected • Only some links will have counts assigned

  18. Model Validation File Creator

  19. Model Validation File Creator

  20. Matching Counts and Links Using Linear Referencing • Model links also coded with LRS attributes from GIS base map • Allows geographic comparison of count locations and model links

  21. Multiple Counts at Same Location • Count attributes used to match counts with appropriate model links • Hierarchy of preferred counts developed • Examples of preferred counts • Counts taken in same year as model validation year • Directional counts • Counts with shorter intervals

  22. Results • Entire process works successfully • Already used on 2002, 2005 highway networks in current model • Will be used soon with 2006 counts • RTCD data used in many transportation applications, including web data tool

  23. www.semcog.org

  24. Future Initiatives • Continue to improve count data quality • Append data from additional sources into RTCD • Fully automate importing of data into RTCD • Begin performing model validation with statistically generated sample of links

  25. Keys That Made This Project Successful • Establishing data formatting consistency • Effective communication, coordination with local agencies and MDOT • Establishing data quality controls throughout process • Use of GIS (linear referencing) • Automating tasks wherever possible

  26. Local agency counts (via TCDS) SEMCOG website Data-based validation files Regional Traffic Count Database (RTCD) Model Validation File Creator Other counts Model-based validation files MDOT counts (via conversion tool) Other transportation applications

  27. Development of a Traffic Count Database for Travel Model Calibration Brian D. Mohr, Li-yang Feng, and Tom Bruff Southeast Michigan Council of Governments 11th TRB Applications Conference Daytona Beach, FL May 7, 2007

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