1. Brian D. Mohr and Jilan Chen Southeast Michigan Council of Governments 11 th TRB Applications Conference Daytona Beach, FL May 8, 2007 SEMCOG Household Travel Survey: Data Processing and Reasonableness Checks

2. * Detroit

3. 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

4. Summary of data processing and reasonableness checks performed on 2004 household travel survey dataSummary of data processing and reasonableness checks performed on 2004 household travel survey data Survey background informationSurvey background information Calculation of survey expansion factorsCalculation of survey expansion factors Future initiatives and lessons learnedFuture initiatives and lessons learned Presentation Topics

5. New snapshot of regional travel behavior neededNew snapshot of regional travel behavior needed –Previous survey conducted in 1994 –Shorter term enhancements planned for four-step model –Possible future move to activity-based model Opportunity to partner with MDOTOpportunity to partner with MDOT Why Collect New Household Survey Data in 2004?

6. Combination of two household surveysCombination of two household surveys –Michigan Travel Counts –SEMCOG Travel Counts Survey similaritiesSurvey similarities –Consultants (MORPACE, PB, Brogan) –Activity-based survey design –Survey methodology –Relational database structure 2004 Household Travel Survey Background

7. Michigan Travel Counts SEMCOG Travel Counts Area surveyed State of Michigan Southeast Michigan Total households surveyed 15,0003,800 SE MI households surveyed 2,200 3,800 (for total of 6,000) Survey period Feb ’04–Mar ’05 Oct ’04–May ’05 Days surveyed Two days One day Prior residence? NoYes “Stop along the way” question? NoYes Transit focus? NoYes

8. Computer-Assisted Telephone Interviewing (CATI) logic checksComputer-Assisted Telephone Interviewing (CATI) logic checks MORPACE post-processing checksMORPACE post-processing checks Parsons Brinckerhoff interim auditsParsons Brinckerhoff interim audits SEMCOG interim auditsSEMCOG interim audits –Review of questionable records –Number of persons, workers, autos per household –Distributions of trip rates and trip lengths QA/QC Measures During Data Collection

9. SEMCOG’s Post-Processing Data Checks Database Integrity Checks Individual Field Checks Intra-Record Checks Inter-Record Checks Distribution Plots

10. Checked primary keys for each tableChecked primary keys for each table Checked relationships among tablesChecked relationships among tables –Person → household –Household → person –Trip → person Database Integrity Checks

11. Determined if attribute values fell within valid rangesDetermined if attribute values fell within valid ranges Corrected obvious errorsCorrected obvious errors Found explanations for unusual errors, clarified confusing field definitionsFound explanations for unusual errors, clarified confusing field definitions Individual Field Checks

12. Date versus day of weekDate versus day of week Related age fieldsRelated age fields Related transit pass/cost fieldsRelated transit pass/cost fields Related school variables, work variablesRelated school variables, work variables Fields containing geocoding informationFields containing geocoding information Origin/destination, arrival/departure fieldsOrigin/destination, arrival/departure fields Trip-table fields related to travel modes, travel costs, number of passengersTrip-table fields related to travel modes, travel costs, number of passengers Intra-Record Checks

13. Arrival location, time compared to subsequent departure location, timeArrival location, time compared to subsequent departure location, time Destination activity compared to subsequent origin activityDestination activity compared to subsequent origin activity Trip characteristics for members of same householdTrip characteristics for members of same household Inter-Record Checks

14. Distributions plotted for travel times, distances, speeds, activitiesDistributions plotted for travel times, distances, speeds, activities Distributions stratified by mode, purpose, geographic areaDistributions stratified by mode, purpose, geographic area Useful for identifying outlying dataUseful for identifying outlying data Distribution Plots

15. Overall assessmentOverall assessment –Excellent data quality –Vast majority of checks uncovered no errors Specific findings: database integrity, individual field checksSpecific findings: database integrity, individual field checks –Trip records discovered for “immobile” participants –Definition clarified for “stop” field Assessment of Data Quality

16. Specific findings (intra-record, inter-record, distribution checks)Specific findings (intra-record, inter-record, distribution checks) –22 records with incorrect day of week –587 locations missing geocoding attributes –29 records with identical arrival time and subsequent departure time –Work trips found for households with no workers –Outliers found in some distribution plots Assessment of Data Quality

17. All household locations mapped for both MDOT, SEMCOG surveysAll household locations mapped for both MDOT, SEMCOG surveys Used to separate households in region from households outside of regionUsed to separate households in region from households outside of region Used to check county attribute valuesUsed to check county attribute values Household Geocoding Checks

18. Suggestions for performing specific data checksSuggestions for performing specific data checks Opinion on reasonableness of basic survey statisticsOpinion on reasonableness of basic survey statistics Assistance on combining two surveysAssistance on combining two surveys Assistance with calculating expansion factorsAssistance with calculating expansion factors Consultation with Parsons

19. Concerns with second day of MDOT surveyConcerns with second day of MDOT survey –Personal trip-rates: dropped from 3.64 to 3.19 –Zero-trip households: increased from 8.1% to 11.0% DecisionsDecisions –Combine only first day of MDOT survey with SEMCOG survey –Calculate, apply expansion factors after combining surveys Combining the Surveys

20. Household size, auto ownership, number of workers = 64 stratification cellsHousehold size, auto ownership, number of workers = 64 stratification cells Spatial stratification (preferably by county)Spatial stratification (preferably by county) Lack of sufficient samples in some cellsLack of sufficient samples in some cells Balancing desire for precision, need for aggregationBalancing desire for precision, need for aggregation Survey Expansion Issues

21. Calculating Expansion Factors Cells with insufficient samples aggregatedCells with insufficient samples aggregated Initial expansion factors proposed based on experience from other urban areasInitial expansion factors proposed based on experience from other urban areas Four-dimensional algorithm by Parsons used to calculate final expansion factorsFour-dimensional algorithm by Parsons used to calculate final expansion factors

22. Using Draft Expansion Factors Category 2005 Households Expanded Data Percent Diff. HH Size = 1 519,891524,6710.9% HH Size = 2 598,931598,295-0.1% HH Size = 3 317,948338,8576.6% HH Size = 4+ 489,328464,667-5.0% Workers = 0 489,996490,2050.0% Workers = 1 745,816755,4071.3% Workers = 2 557,358563,2931.1% Workers = 3+ 132,929117,585-11.5% Overall1,926,0981,926,4900.02%

23. Using Final Expansion Factors Category 2005 Households Expanded Data Percent Diff. HH Size = 1 519,891519,8910.0% HH Size = 2 598,931598,9310.0% HH Size = 3 317,948317,9480.0% HH Size = 4+ 489,328489,3280.0% Workers = 0 489,996489,9960.0% Workers = 1 745,816745,8160.0% Workers = 2 557,358557,3580.0% Workers = 3+ 132,929132,9290.0% Overall1,926,0981,926,0980.00%

24. Perform additional QA/QC checksPerform additional QA/QC checks Analyze transit-focused survey datasetAnalyze transit-focused survey dataset Develop detailed survey analysis report (including 1994/2004 data comparison)Develop detailed survey analysis report (including 1994/2004 data comparison) Develop summary report (regional snapshot for public/media)Develop summary report (regional snapshot for public/media) Use data in modelUse data in model Future Initiatives

25. QA/QC essential from data collection through post-processingQA/QC essential from data collection through post-processing One travel day sufficient for our needsOne travel day sufficient for our needs GIS: useful tool for performing checksGIS: useful tool for performing checks Four-dimensional expansion factor calculation possibleFour-dimensional expansion factor calculation possible Lessons Learned

26. Brian D. Mohr and Jilan Chen Southeast Michigan Council of Governments 11 th TRB Applications Conference Daytona Beach, FL May 8, 2007 SEMCOG Household Travel Survey: Data Processing and Reasonableness Checks