National Academies Press: OpenBook
« Previous: Glossary of Terms
Page 61
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2019. Public Transit Rider Origin–Destination Survey Methods and Technologies. Washington, DC: The National Academies Press. doi: 10.17226/25428.
×
Page 61
Page 62
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2019. Public Transit Rider Origin–Destination Survey Methods and Technologies. Washington, DC: The National Academies Press. doi: 10.17226/25428.
×
Page 62
Page 63
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2019. Public Transit Rider Origin–Destination Survey Methods and Technologies. Washington, DC: The National Academies Press. doi: 10.17226/25428.
×
Page 63
Page 64
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2019. Public Transit Rider Origin–Destination Survey Methods and Technologies. Washington, DC: The National Academies Press. doi: 10.17226/25428.
×
Page 64

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

61 AECOM. Transit Survey White Paper. FSUTMSonline. Florida Department of Transportation Forecasting and Travel Trends Office. 2009. Available: http://www.fsutmsonline.net/images/uploads/reports/Transit_ Survey_White_Paper_v6_5-9-2011_edit.doc [accessed: December 2017]. Agrawal, A. W., S. Granger-Bevan, G. Newmark, and H. Nixon. Comparing Data Quality and Cost from Three Modes of On-Board Transit Passenger Surveys. Publication CA-MTI-15-1206. Mineta Transportation Insti- tute, San Jose, CA, 2015. Baltes, M. R. Customer Surveying for Public Transit: A Design Manual for Customer On-Board Surveys. Publication No. DTRS98-G-0032. National Center for Transit Research, Tampa, FL, 2002. Beatty, P., and D. Herrmann. To answer or not to answer: Decision processes related to survey item nonresponse. Pp. 71-86 in Survey Nonresponse, R. M. Groves, D. A. Dillman, J. L. Eltinge, and R. J. Little, eds., John Wiley & Sons, New York, 2002. Cambridge Systematics (CS), 1-Click | CS Software, Medford, MA. Available: http://camsys.software/products/ 1-click. Cherrington, L. K. Recommended Practices for Transit Onboard Surveys. Presented at 86th Annual Meeting of the Transportation Research Board, Washington, DC, Report No. 07-1908, 2007. Cervenka, K. Telephone interview with A. Zalewski, June 13, 2018. COTA (Central Ohio Transit Authority). 2013 On-Board Transit Survey. Columbus, 2014. Available: https:// www.cota.com/wp-content/themes/gotravel-child/images/upload/solicitations%20files/2017/09/25/ Exhibit%20A%2003_31_2014_COTA_2013_OnBoardSurvey_DraftReport.pdf. Cummins, B., G. Spitz, T. O’Malley, and M. Campbell. How Close is Close Enough? Statistical Equivalence of Onboard Versus Online Surveys of Transit Customers. Transportation Research Record: Journal of the Trans- portation Research Board, No. 2351, Transportation Research Board of the National Academies, Washington, D.C., 2013, pp. 23–29. CUTR (Center for Urban Transportation Research). GTFS-flex. University of South Florida, Tampa, 1996. Available: https://github.com/CUTR-at-USF/gtfs-flex [accessed Feb. 5 2018]. DemandTrans Solutions. Development of Transactional Data Specifications for Demand-Responsive Transpor- tation. TCRP G-16. Transportation Research Board of the National Academies, Washington, D.C., 2018. Available: http://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=4120 [accessed Feb. 5, 2018]. Dong, B., B. McHugh, and V. Shank. Multiple correspondence with A. Zalewski and A. Cohen April 2019. Dumas, R. Analyzing Transit Equity Using Automatically Collected Data. Chapter 2 in Origin, Destination, and Interchange Inference at the MBTA. Master’s thesis, Massachusetts Institute of Technology, 2017. ETC Institute, Valley Metro 2010-11 Transit On-Board Survey Final Report, Valley Metro Regional Public Transit Authority, December 2011. Available: https://www.valleymetro.org/sites/default/files/legacy-images/ uploads/projects/2010-2011_Transit_On-Board_Survey_Final_Report.pdf. FTA (Federal Transit Administration). Title VI Requirements and Guidelines for Federal Transit Administra- tion Recipients. FTA Circular 4702.1B. Washington, D.C., 2012. Available: https://www.transit.dot.gov/ regulations-and-guidance/fta-circulars/title-vi-requirements-and-guidelines-federal-transit. FTA (Federal Transit Administration). Overview of Stops. Washington D.C., 2013. FTA (Federal Transit Administration). Americans with Disabilities Act (ADA): Guidance. FTA Circu- lar 4710.1. Washington, D.C., 2015. Available: https://www.transit.dot.gov/sites/fta.dot.gov/files/docs/ Final_FTA_ADA_Circular_C_4710.1.pdf. FTA (Federal Transit Administration). National Transit Database: Chatham Area Transit 2016 Annual Agency Profile, 2016a. Available: https://www.transit.dot.gov/sites/fta.dot.gov/files/transit_agency_profile_doc/ 2016/40025.pdf. References

62 Public Transit Rider Origin–Destination Survey Methods and Technologies FTA (Federal Transit Administration). National Transit Database: Massachusetts Bay Transportation Authority 2016 Annual Agency Profile, 2016b. Available: https://www.transit.dot.gov/sites/fta.dot.gov/files/transit_ agency_profile_doc/2016/10003.pdf. FTA (Federal Transit Administration). National Transit Database (NTD): 2016 Metrics, 2016c. Available: https://www.transit.dot.gov/ntd/data-product/2016-metrics. Gordon, J., H. Koutsopoulos, N. Wilson, and J. Attanucci. Automated Inference of Linked Transit Journeys in London Using Fare-Transaction and Vehicle Location Data. In Transportation Research Record: Journal of the Transportation Research Board, No. 2343, Transportation Research Board of the National Academies, Washington, D.C., 2013, pp. 17–24. Hunsinger, E. Iterative Proportional Fitting for a Two-Dimensional Table. Presentation at University of California, Berkeley, Department of Demography, May 2008. Available: http://www.demog.berkeley.edu/∼eddieh/ IPFDescription/AKDOLWDIPFTWOD.pdf [accessed Feb. 2, 2018]. Israel, S. Telephone interview with A. Cohen and A. Zalewski, March 30 and June 15, 2018. Kittelson and Associates, Inc., Parsons Brinckerhoff, Inc., KFH Group, Inc., Texas A&M Transportation Institute, and Arup. TCRP Report 165: Transit Capacity and Quality of Service Manual, 3rd Edition. Transportation Research Board of the National Academies, Washington D.C., 2013. Kusakabe, T., and Y. Asakura. Behavioural Data Mining of Transit Smart Card Data: A Data Fusion Approach. Transportation Research Part C: Emerging Technologies, Vol. 46, 2014, pp. 179–191. Lor, M., B. J. Bowers, A. Krupp, and N. Jacobson. Tailored Explanation: A Strategy to Minimize Nonresponse in Demographic Items Among Low-income Racial and Ethnic Minorities. Survey Practice, Vol. 10, 2017, No. 3. Ma, X., Y. J. Wu, Y. Wang, F. Chen, and J. Liu. Mining Smart Card Data for Transit Riders’ Travel Patterns. Trans- portation Research Part C: Emerging Technologies, Vol. 36, 2013, pp. 1–12. MBTA (Massachusetts Bay Transportation Authority). Where’s Charlie? The Origin-Destination-Transfer (ODX) Model. Blog post, 2016a. Available: http://www.mbtabackontrack.com/blog/43-odx-model [accessed May 5, 2018]. MBTA (Massachusetts Bay Transportation Authority). Bus Crowding on the Street Network. Blog post, 2016b. Available: http://www.mbtabackontrack.com/blog/62-bus-crowding-on-the-street-network [accessed May 5, 2018]. MBTA (Massachusetts Bay Transportation Authority). Visualizing Origin and Destinations on the MBTA Bus and Rapid Transit Network Blog post 2017. Available: http://www.mbtabackontrack.com/blog/ 72-visualizing-origin-and-destinations-on-the-mbta-bus-and-rapid-transit-network [accessed May 5, 2018]. McHugh, B. K., B. Dong, J. D. Recker, and V. Shank. Conducting Onboard Transit Rider Surveys with Electronic Handheld Tablets: An Agencywide Consolidated Approach. In Transportation Research Record: Journal of the Transportation Research Board, No. 2643, Transportation Research Board of the National Academies, Washington, D.C., 2017, pp. 19–27. Memarian, B., H. Jeong, and D. Uhm. Effects of Survey Techniques on On-Board Survey Performance. Transport Policy, Vol. 21, 2012, pp. 52–62. Moore, J. C. The Effects of Questionnaire Design Changes on Asset Income Amount Nonresponse in Waves 1 and 2 of the 2004 SIPP Panel. Survey Methodology, Vol. 1, 2006, pp. 1–19. Moore, J. C., L. L. Stinson, and E. Welniak. Income Reporting in Surveys: Cognitive Issues and Measurement Error. pp. 155–174 In Cognition and Survey Research, M. G. Sirkiin, D. J. Herrmann, S. Schecter, N. Schwarz, J. M. Tanur, and R. Tourangeau, eds., John Wiley, New York, 1999. Neff, J., and L. Pham, A Profile of Public Transportation Passenger Demographics and Travel Characteristics Reported in On-Board Surveys. American Public Transportation Association, Washington, D.C., 2007. Okunieff, P. TCRP Synthesis 125: Multiagency Electronic Fare Payment Systems. Transportation Research Board of the National Academies, Washington, D.C., 2017. OneBusAway: The Open Source platform for Real Time Transit Info. University of Washington, Seattle. Available: https://onebusaway.org [accessed Feb. 5, 2018]. “OpenTripPlanner (OTP), Multimodal Trip Planning & Analysis,” [Online]. Available: http://www.opentrip planner.org [accessed Feb. 5, 2018]. Paget-Seekins, L., and A. Gartsman. Telephone interview with G. Macfarlane. April 4, 2018. Pelletier, M. P., M. Trépanier, and C. Morency. Smart Card Data Use in Public Transit: A Literature Review. Transportation Research Part C: Emerging Technologies, Vol. 19, No. 4, 2010, pp. 557–568. Pew Research Center. Internet Broadband Fact Sheet. Washington, D.C., 2018a. Available: http://www. pewinternet.org/fact-sheet/internet-broadband [accessed Feb. 8, 2018]. Pew Research Center. Mobile Fact Sheet. Washington, D.C., 2018b. Available: http://www.pewinternet.org/ fact-sheet/mobile [accessed Feb. 5, 2018]. Pew Research Center. Questionnaire Design. Washington, D.C., 2018c. Available: http://www.pewresearch.org/ methodology/u-s-survey-research/questionnaire-design [accessed Feb. 7, 2018]. ProtoGeo Oy. 2015. Moves [unknown version; Mobile application software]. https://moves-app.com.

References 63 Rahman, S., J. Wong, and C. Brakewood. Use of Mobile Ticketing Data to Estimate an Origin–Destination Matrix for New York City Ferry Service. In Transportation Research Record: Journal of the Transportation Research Board, No. 2544, Transportation Research Board of the National Academies, Washington, D.C., 2016, pp. 1–9. Richardson, A. J., E. S. Ampt, and A. H. Meyburg. Weighting and Expansion of Data. In Survey Methods for Transport Planning, Eucalyptus Press, Parkville, Australia, 1995. Schaller, B. TCRP Synthesis 63: On-Board and Intercept Transit Survey Techniques. Transportation Research Board of the National Academies, Washington D.C., 2005. Schmitt, D., On-Board Transit Rider Surveys: Synthesis of Practice, FSUTMSonline, Florida Department of Transportation Forecasting and Travel Trends Office, 2012. Available: http://www.fsutmsonline.net/images/ uploads/reports/On_Board_Survey_Synthesis.pdf [accessed December 2017]. Seaborn, C., J. Attanucci, and N. Wilson. Analyzing Multimodal Public Transport Journeys in London with Smart Card Fare Payment Data. In Transportation Research Record: Journal of the Transportation Research Board, No. 2121, Transportation Research Board of the National Academies, Washington, D.C., 2009, pp. 55–62. Silver, D., J. Seltzer, S. Hsieh, D. Seidl, and M. Rhindress. Do Seasons Really Matter in Transit Ridership Profiles and Activities? A Closer Look at Seasonal Differences in Travel Patterns from the Long Island Rail Road Origin and Destination Survey. Presented at 95th Annual Meeting of the Transportation Research Board, No. 16-3935, 2016. Singer, E., H. J. Hippler, and N. Schwarz. Confidentiality Assurances in Surveys: Reassurance or Threat? Inter- national Journal of Public Opinion Research, Vol. 4, No. 3, 1992, pp. 256–268. Sparks, G. Telephone interview with G. Macfarlane, March 29, 2018. Spitz, G., F. L. Niles, and T. J. Adler. TCRP Synthesis 69: Web-Based Survey Techniques. Transportation Research Board of the National Academies, Washington D.C., 2006. Tierney, K., S. Decker, K. Proussaloglou, T. Rossi, E. Ruiter, and N. McGuckin. Travel Survey Manual. No. FHWA- PL-96-029, 1996. Transit app. Montréal, Quebec. Available: https://transitapp.com [accessed Feb. 5, 2018]. TRB (Transportation Research Board). Expansion Factors for Transit Survey Responses. Research Needs Statement, Committee ABJ40, Travel Survey Methods, August 2007. Available: https://rns.trb.org/ dproject.asp?n=14119 [accessed January 2018]. Wang, W., J. Attanucci, and N. Wilson. Bus Passenger Origin-Destination Estimation and Related Analyses Using Automated Data Collection Systems. Journal of Public Transportation, Vol. 14, No. 4, 2011, pp. 131–150.

Next: Appendix A - Survey Questionnaire »
Public Transit Rider Origin–Destination Survey Methods and Technologies Get This Book
×
 Public Transit Rider Origin–Destination Survey Methods and Technologies
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

TRB’s Transit Cooperative Research Program (TCRP) Synthesis 138: Public Transit Rider Origin–Destination Survey Methods and Technologies captures the state of the practice among agencies of different sizes, geographic locations, and modes and evaluates the opportunities for and challenges of conducting surveys in an era of emerging technologies.

The report presents the reality and complexity of conducting origin–destination surveys and will allow agencies to compare what they are currently doing with what others are doing, get ideas about what other strategies are possible, and make better decisions about surveying in the future.

The report includes case examples of five transit systems that present an in-depth analysis of various survey strategies and include two agencies that have leveraged passive data to complement or eliminate origin–destination surveys.

READ FREE ONLINE

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  6. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  7. ×

    View our suggested citation for this chapter.

    « Back Next »
  8. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!