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 To explore the application of travel survey data for activity analysis and AB Model inputs: Fill data 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

Data Steps… 1. Bridge the trip purpose codes and activity types using three categories: subsistence/mandatory, maintenance, and discretionary 2. Re-code the trip file into home-to-home tours 3. 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 4. Examine Trends in activity patterns using traveler profiles

Step 1: Bridge Trip Purposes into Activity Types

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

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

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

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

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

93.2 percent of daily travel is in Home-to-Home tours 2.5 percent of daily travel tours start at home but don't return home at the end of the day 2.9 percent of daily travel tours start at a non-home location but return home 1.4 percent of daily travel tours neither start at home nor return home Step 2 – Code Home-to Home Tours Not all people begin and/or end the day at home

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

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

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

Step 3: Develop Traveler Profiles

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 Look for the groupings that define population segments for activity analysis: Step 3 – Develop Traveler Profiles

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 Early Findings Step 3 – Develop Traveler Profiles

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

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

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

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

What are the Trends in Activity Patterns?

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 Summary of Early Findings Step 4 – Examine Trends

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

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

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

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

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

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

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

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’

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?

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 General Schema of NHTS Trip Data Look at Shared Activities

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

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