Comparative Analysis of Global Positioning System–Based and Travel Survey–Based Data
Abstract
This paper examines the driver demographics, driver travel characteristics, and driver adherence to survey protocol considerations that affect the likelihood of underreporting in a household travel survey. The research considers both the likelihood of vehicle driver trip underreporting and the level of vehicle driver trip underreporting by using a joint binary choice-ordered response discrete model. The empirical analysis uses the Global Positioning System–equipped sample of households from the 2004 Kansas City (Kansas and Missouri) Household Travel Survey which also provided travel diary information. The empirical results provide important insights about underreporting tendencies in household travel surveys. In particular, adults younger than 30 years of age; men; individuals with less than a high school education; unemployed individuals; individuals working in clerical and manufacturing professions; workers employed at residential land uses; individuals who make many trips, travel long distances, and trip chain; and respondents who fail to use a travel diary to log their travel before telephone retrieval of their patterns are associated with more underreporting. The underlying factors that influence whether an individual underreports are different from the factors that affect the level of underreporting.
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References
1. Wolf J. Oliviera M. and Thompson M. Impact of Underreporting on Mileage and Travel Time Estimates: Results from Global Positioning System-Enhanced Household Travel Survey. In Transportation Research Record: Journal of the Transportation Research Board, No. 1854, Transportation Research Board of the National Academies, Washington, D.C., 2003, pp. 189–198.
2. Zmud J. and Wolf J. Identifying the Correlates of Trip Misreporting—Results from the California Statewide Household Travel Survey GPS Study. Presented at 10th International Conference on Travel Behaviour Research, Lucerne, Switzerland, Aug. 2003.
3. Battelle Memorial Institute. Global Positioning Systems for Personal Travel Surveys. Lexington Area Travel Data Collection Test. Final Report to Office of Highway Information Management. FHWA, Washington, D.C., 1997. www.fhwa.dot.gov/ohim/lextrav.pdf.
4. Casas J. and Arce C. H. Trip Reporting in Household Travel Diaries: A Comparison to GPS-Collected Data. Presented at 78th Annual Meeting of the Transportation Research Board, Washington, D.C., 1999.
5. NuStats. Year 2000 Post-Census Regional Travel Study, GPS Study Final Report. Southern California Association of Governments, Los Angeles, 2004.
6. NuStats. Pittsburgh Travel View Household Travel Survey. Southwestern Pennsylvania Corporation, Pittsburgh, 2002.
7. NuStats. Household Travel Survey Final Report of Survey Methodology. East-West Coordinating Council, St. Louis, 2003.
8. NuStats. Household Travel Survey Final Report of Survey Results. East–West Coordinating Council, St. Louis, Mo., 2003.
9. Pierce B. Casas J. and Giaimo G. T. Estimating Trip Rate Underreporting: Preliminary Results from the Ohio Household Travel Survey. Presented at 82nd Annual Meeting of the Transportation Research Board, Washington, D.C., 2003.
10. Forrest T. L. and Pearson D., Comparison of Trip Determination Methods in Household Travel Surveys Enhanced by a Global Positioning System. In Transportation Research Record: Journal of the Transportation Research Board No. 1917, Transportation Research Board of the National Academies, Washington, D.C., 2005, pp. 63–71.
11. Pearson D. Household Survey Trip Underreporting: Case Study in Laredo, Texas. Presented at 84th Annual Meeting of the Transportation Research Board, Washington, D.C., 2005.
12. Tyler/Longview Household Travel Survey Documentation. Texas Department of Transportation, Austin, 2003.
13. NuStats. Kansas City Household Travel Survey: GPS Study Final Report. Mid-America Regional Council, Kansas City, Mo., 2004.
14. Wolf J. Applications of New Technologies in Travel Surveys. Presented at Seventh International Conference on Travel Survey Methods, Playa Herradura, Costa Rica, 2004.
15. Wolf J. Loechl M. Meyers J. and Arce C. Trip Rate Analysis in GPS-Enhanced Personal Travel Surveys. Presented at International Conference on Transport Survey Quality and Innovation, Kruger Park, South Africa, 2001.
16. McGuckin N. and Murakami E. Examining Trip-Chaining: Comparison of Travel by Men and Women. In Transportation Research Record: Journal of the Transportation Research Board, No. 1693, TRB, National Research Council, Washington, D.C., 1999, pp. 79–85.
17. Levinson D. How Patterns Changed from ‘68 to ‘88. ITS Review, Vol. 20, No. 2 1997, pp. 2–3.
18. Taylor B. Beyond the Gender Gap. ITS Review, Vol. 20, No. 2, 1997, p. 4.
19. Badoe D. A. and Steuart G. N. Underreporting of Trips in Travel Survey Conducted by Telephone. Presented at 78th Annual Meeting of the Transportation Research Board, Washington, D.C., 1999.
20. Kostyniuk L. P. Wargelin L. Purvis C. and Vaughn K. Improving the Accuracy of Trip-Chaining Information in Activity/Travel Surveys. Presented at International Conference on Transport Survey Quality and Innovation, Kruger Park, South Africa, 2001.
21. Wargelin L. and Kostyniuk L. P. Proxy Respondents in Household Travel Surveys. Presented at Seventh International Conference on Travel Survey Methods, Playa Herradura, Costa Rica, 2004.
22. Popuri Y. D. and Bhat C. R. On Modeling Choice and Frequency of Home-Based Telecommuting. In Transportation Research Record: Journal of the Transportation Research Board, No. 1858, Transportation Research Board of the National Academies, Washington, D.C., 2003, pp. 55–60.
23. Misra R. and Bhat C. Activity-Travel Patterns of Nonworkers in the San Francisco Bay Area: Exploratory Analysis. In Transportation Research Record: Journal of the Transportation Research Board, No. 1718, TRB, National Research Council, Washington, D.C., 2000, pp. 43–51.
24. Ben-Akiva M. and Lerman S. R. Discrete Choice Analysis. MIT Press, Cambridge, Mass., 1985.
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Article first published: January 2006
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