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Best Practices in Transit Rider Survey Data Collection Chris Tatham

Best Practices in Transit Rider Survey Data Collection Chris Tatham Sr. Vice President, CEO, ETC Institute 725 W. Frontier Circle Olathe, KS 66061 913-254-4512 ctatham@etcinstitute.com January 25, 2012. Agenda. Agenda. Challenges with Rider Survey Data Collection

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Best Practices in Transit Rider Survey Data Collection Chris Tatham

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  1. Best Practices in Transit Rider Survey Data Collection Chris Tatham Sr. Vice President, CEO, ETC Institute 725 W. Frontier Circle Olathe, KS 66061 913-254-4512 ctatham@etcinstitute.com January 25, 2012

  2. Agenda Agenda • Challenges with Rider Survey Data Collection • Methods to Address These Challenges • Closely Manage the Design & Distribution of the Sample • Use Tablet PCs & Personal Interviews • Carefully Plan and Conduct Data Expansion • Summary • Questions 2

  3. Challenges 3

  4. Challenges • Inadequate Development and Management of the Sample • Sampling plans are often developed using very little information on ridership • Usually limited to the total average ridership on a bus route or rail station, but little else is known • Distribution of the sample is often not monitored while in the field • Surveys are collected and the distribution is reviewed after the survey has been completed • IMPACT: Samples are not representative of the ridership 4

  5. Challenges (continued) • Very little effort is taken to gather data to support sample-expansion • Ride check data is usually available, but seldom reviewed before surveys are conducted • Inattention to automated counts misses a huge (and largely free!) opportunity • Major stops along a route are under-represented • End-of-the-Line locations are over-represented • Vehicle counts from P&R lots are available, but often not used – could provide as control totals for data expansion • IMPACT: Aggregate expansion only magnifies sampling errors 5

  6. Challenges (continued) • Severe attrition with self-administered surveys handed out to transit riders • Low participation rates • Biases in the types of people who respond • High rates of incomplete/illogical records • High rates of geo-coding failure • IMPACT: introduction of unknown biases related to ridership characteristics and travel patterns Response rates are often less than 20% and A Majority of the Completed Surveys A Often Unusable 6

  7. Methods to Address These Challenges 7

  8. Methods to Address these Challenges 1. Closely Manage the Design & Distribution of the Sample • Assemble data on existing ridership (first!) • Obtain counts from APCs, faregates, etc. • Undertake manual boarding/alighting counts if necessary • Consider on-to-off “survey” • Set Detailed Sampling Goals: • Don’t stop with aggregate goals for each route/station • Set goals for: • specific locations along each route • specific types of trips (Station A to B/Stop A to B • by time of day • by direction • Manage the goals while you are in the field 8

  9. GPS Based Scanners Captured More than 97% of the On-to-Off Flows in Honolulu 9

  10. Methods to Address these Challenges (continued) • Advantages of Personal Interview • More accurate • More complete • More representative • key groups are not under-represented • Advantages of Tablet PCs • Details about the study area/transit system can be pre-programmed • Can be programmed to interface with Google-Maps for real-time geocoding in the field • Manage sample distribution in the field • Real-time management of data collection in the field with IPadw/3G • Less time to administer (helps capture short trips) 2. Use Tablet PCs & Personal Interviews 10

  11. Tablet PC vs. Self Administered Combined results of pilot tests in Atlanta (2009), Phoenix (2010), and Nashville (2011) 11

  12. 01 12

  13. Options Presented at the Beginning of the Survey 03 13

  14. Survey Interfaces with Google-Earth in Real-Time 08a 14

  15. Key Locations, such as Park and Ride Lots Are Preloaded 13a 15

  16. Bus Route Shape Files Are Integrated 15 16

  17. Route Transfers Are Limited 18 17

  18. Summary Screen Ensures All Recorded Information Is Correct 25 18

  19. Reasons Tablet PCs Enhance Data Quality and Sampling Video Demonstration 19

  20. Methods to Address these Challenges (continued) • Control sample expansion at the least aggregate level possible • Ensures the proper distribution of trips along routes • Limited by density of samples at stops/stations • Often involves some aggregation of stops/stations • Better data supports better expansion: • Atlanta rail faregate data  station-to-station controls • Atlanta bus APC data  stop-on and stop-off controls • Phoenix rail counting task (ons, offs, on-to-offs)  station-to-station controls • Without good control totals you can’t ensure that your expanded data are representative 3. Carefully Plan and Conduct Data Expansion 20

  21. RTE 17 DESIRE LINES FROM ON => OFF COUNTS OCT 2011 – ALL FLOWS Good On-to-Off Flow Data Helps Plan For Data Expansion 21

  22. Simple Example of Data Expansion - RAIL 22

  23. If You Don’t Manage Your Sample, Your Data Could Look Like This 23

  24. What Do Personal Interviews Cost? 24

  25. Unit Costs Per Useable Survey Using the Tablet PC/Personal Interview • The Tablet PC/Personal Interview method facilitates • data expansion, which can lower the overall unit • cost per completed useable survey 25

  26. Summary • The methods discussed today can be used to enhance the overall quality of the data collected • Closely Manage the Design & Distribution of the Sample • Use Tablet PCs & Personal Interviews • Carefully Plan and Conduct Data Expansion • Take advantage of new technology • Give yourself enough time to do the survey right • Good training and oversight of the people administering the survey is always essential. Improvements in the quality of survey data will place pressure on transit agencies to collect better ridership data 26

  27. Questions ??? Chris Tatham Sr. Vice President, CEO ETC Institute 725 W. Frontier Circle Olathe, KS 66061 913-254-4512 ctatham@etcinstitute.com 27

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