1. Southeast Michigan Council of Governments

2. 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 Development of a Traffic Count Database for Travel Model Calibration

3. * Detroit

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

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

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

7. Create regional traffic count database (RTCD)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 modelCreate automated procedure for linking counts with model Use power of GIS (linear referencing)Use power of GIS (linear referencing) Solutions

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

9. Software featuresSoftware 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, DetroitProvides SEMCOG easy access to counts from all seven counties, Detroit Traffic Count Database System (TCDS)

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

13. MDOT Data Conversion Tool

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

15. Counts coded with LRS attributes from base map (route/milepoint system)Counts coded with LRS attributes from base map (route/milepoint system) All SEMCOG transportation data codedAll SEMCOG transportation data coded Counts coded as segmentsCounts coded as segments GIS (Linear Referencing) Coding 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

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

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

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

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

20. Model Validation File Creator

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

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

24. Entire process works successfullyEntire 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 toolRTCD data used in many transportation applications, including web data tool Results

25. www.semcog.org

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

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

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

29. 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 Development of a Traffic Count Database for Travel Model Calibration