SEMCOG Household Travel Survey: Data Processing and Reasonableness Checks

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

2. *Detroit

3. 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

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

5. Why Collect New Household Survey Data in 2004? • New 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 MDOT

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

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

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

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

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

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

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

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

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

16. Assessment of Data Quality • 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

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

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

19. Combining the Surveys • Concerns 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% • Decisions • Combine only first day of MDOT survey with SEMCOG survey • Calculate, apply expansion factors after combining surveys

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

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

22. Using Draft Expansion Factors

23. Using Final Expansion Factors

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

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

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