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Using NHTS to Estimate Activity Patterns

Using NHTS to Estimate Activity Patterns. Heather Contrino, Travel Surveys Team Leader FHWA Office of Highway Policy Information Nancy McGuckin, Travel Behavior Analyst Yuki Nakamoto, SAS Programmer Extraordinaire Planning Applications Conference, 2007. Objectives.

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Using NHTS to Estimate Activity Patterns

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  1. Using NHTS to Estimate Activity Patterns Heather Contrino, Travel Surveys Team Leader FHWA Office of Highway Policy Information Nancy McGuckin, Travel Behavior Analyst Yuki Nakamoto, SAS Programmer Extraordinaire Planning Applications Conference, 2007

  2. Objectives To explore the application of travel survey data for activity analysis and AB Model inputs: • Filldata gaps for transportation planners, • Provide guidance on key determinants of travel, • Support benchmarking and testing during transition time from four-step to new generation, and • Assess trend behavior in use of time/activity

  3. Data Steps… • Bridge the trip purpose codes and activity types using three categories: subsistence/mandatory, maintenance, and discretionary • Re-code the trip file into home-to-home tours • Develop profiles of traveler types (developed with CART) to look at time spent in each activity type, and time spent in travel for each activity type • Examine Trends in activity patterns using traveler profiles

  4. Step 1: Bridge Trip Purposes into Activity Types

  5. Step 1 – Bridging Trips and Activities Percent of Trips within Mandatory/Subsistence Category Source: 2001 NHTS

  6. Step 1 – Bridging Trips and Activities Percent of Trips within Maintenance Category Source: 2001 NHTS

  7. Step 1 – Bridging Trips and Activities Percent of Trips within Discretionary Category Source: 2001 NHTS

  8. Step 1 – Bridging Trips and Activities Result: Maintenance activities account for the largest share of trips Source: 2001 NHTS

  9. Step 2: Code the NHTS into home-to-home tours

  10. Step 2 – Code Home-to Home Tours Not all people begin and/or end the day at home

  11. Step 2 – Code Home-to Home Tours Some home-to-home tours are complex, including households with multiple workers and many activities

  12. Step 2 – Code Home-to Home Tours But most home-to-home tours are simple Home

  13. Step 2 – Code Home-to Home Tours 26 percent of tours include subsistence activities: Note: People can have more than one activity at a location Home

  14. Step 3: Develop Traveler Profiles

  15. Step 3 – Develop Traveler Profiles Look for the groupings that define population segments for activity analysis: • Start with characteristics that determine travel from CART (Cluster Analysis Regression Tree), e.g.: • Worker status • Vehicle Availability • Presence of Children (we used ‘dependants’ who do not drive) • Sex • Then run the number of activities, time in activities, travel time, total out-of-home time, etc by these profile demographics • Then do it for 1995 and look to see if any trends emerge

  16. Step 3 – Develop Traveler Profiles Early Findings • Worker status showed greatest difference in time spent in activities out-of-home: • Workers spend more time out-of-home and less time in maintenance and discretionary activities • Non-workers spend nearly as much time in daily travel as do workers. • Less work may not equal less travel • Presence of dependants/children effected both working and non-working women’s time in maintenance activities

  17. Step 3 – Develop Traveler Profiles Workers spend more time in out-of-home activities – slightly over 8 hours per day Source: 2001 NHTS

  18. Step 3 – Develop Traveler Profiles This is true even if there are fewer vehicles than drivers… Source: 2001 NHTS

  19. Step 3 – Develop Traveler Profiles Non-workers spend nearly as much time in daily travel as do workers… Source: 2001 NHTS

  20. Step 3 – Develop Traveler Profiles Even when there are fewer vehicles than drivers… Source: 2001 NHTS

  21. What are the Trends in Activity Patterns?

  22. Step 4 – Examine Trends Summary of Early Findings • Altogether, people are spending more time at home; just under 30 minutes a day -- (is this Internet effects? Social changes? Big screen TVs? Not aging cohorts within adult men—I checked by age group) • Workers are reporting more time in mandatory activities and more minutes of travel every day for mandatory • Workers are spending less time in out-of-home discretionary activities, but slightly more time in travel for discretionary • All groups are spending much less time in out-of-home maintenance activities, but slightly more time in travel for maintenance

  23. Since 1995, both men and women report spending more time at home… Step 4 – Examine Trends

  24. Step 4 – Examine Trends And workers are reporting more time in mandatory/subsistence activities Source: NHTS Data Series

  25. Step 4 – Examine Trends While just slightly more time in travel for mandatory activities Source: NHTS Data Series

  26. Step 4 – Examine Trends All groups are spending less time in out-of-home maintenance activities as compared to 1995 Source: NHTS Data Series

  27. Step 4 – Examine Trends And slightly more time in travel for out-of-home maintenanceactivities… Source: NHTS Data Series

  28. Step 4 – Examine Trends All workers are spending less time in out-of-home discretionaryactivities Source: NHTS Data Series

  29. Step 4 – Examine Trends But all groups are spending more time in travel fordiscretionary activities Source: NHTS Data Series

  30. Summary • Overall, most tours are simple • Workers and non-workers have similar daily amounts of time in travel (is there a minimum threshold to ‘travel time budgets’?) • Non-workers travel more and spend more time in Maintenance and Discretionary activities Less time constraint ≠ less travel As baby-boomers retire will they travel more for maintenance and discretionary activities? • Trends show workers spending less time in maintenance if people are substituting/multi-tasking at work then let’s not just focus on substitution ‘at-home’

  31. Further Analysis • Look at the complexity of tours/activity patterns related to urban area size Are simple tours less likely in large metro areas? • Look at shared activities/shared ride Still haven’t untangles inter-household interaction/decision making aspect Auto constraint of less cars than drivers didn’t show much difference in behavior • Suggestion: try to separate shopping more precisely into maintenance or discretionary • Suggestion: better data on work-at-home and at-work multi-tasking • Other suggestions on data gaps?

  32. Look at Shared Activities General Schema of NHTS Trip Data Shared activity between household members This schema does not include children’s activities, which is available in NHTS and also more likely to result in shared activity and travel

  33. Look at shared ride Carpool Fam-pool All 1990 HBW 24.5% 75.5% 100% 2001 HBW 17.0% 83.0% 100% 2001 Work Tours 26.3% 73.7% 100% All=All Multi-Occupant Vehicle Trips

  34. Thank You! Visit our website: http://nhts.ornl.gov Contact: Nancy.McGuckin@dot.gov Heather.Contrino@dot.gov

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