The National Household Travel Survey

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The National Household Travel Survey
Nanda Srinivasan, Cambridge Systematics
Inc. Nancy McGuckin, Travel Behavior Analyst
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About the NPTS

• Target Population
• Residents in households (all ages)
• Group quarters are not included.

• Survey Method
• RDD list-assisted sample
• Pre-contact letter with incentive
• Telephone recruit--travel-diary mail out
• Telephone retrieval using Computer Assisted
  Telephone Interviews (CATI)
• Information Collected
• All trips, all purposes, all modes on an assigned
  day for all people.
• Long-distance trips for the previous four weeks.

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What Kinds of Information Does the Survey Obtain?

• Demographic information, worker and immigrant
  status, general occupation, web-use, etc.
• Vehicle information and fuel cost/efficiency
• Time of day and purpose for work and non-work
  travel, mode, occupancy, transit access and
  egress
• Usual travel to work matching census, with more
  detail on work-at-home

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Major Users and Uses

• Federal (DOT)
• Federal (Non-DOT)
• State DOT
• MPOs
• Universities
• Research Entities

• Descriptive Statistics
• Travel Models
• Traffic Safety
• Long Distance Travel
• Land-use Models
• Elderly
• Race and Gender
• Transit Planning
• Mobility/Congestion
• Travel Behavior Trends

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Currently, Local Communities Use the National
Travel Data by

• Benchmarking
• Based on nation-wide estimates
• Households from MSAs of similar size, e.g. 3M,
  1-3M, 500K-1M, 250-500K,
• Households from the same Census Region (4) or
  Census Division (9)
• Buying additional samples of the national survey.
  
• (The Add-on Program)
• Transferring travel data from households in
  clusters of Census Tracts like their local area.
• (The Transferability Project)

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National Household Person and Vehicle Trip Rates
Benchmarking
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National Household-based Person Trips by Type
Benchmarking
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Four Ways to Get Household Travel Data

• Conduct local household travel surveys
• Purchase Add-On samples to national survey
• Use transferable estimates from census clusters
• Use default values from areas of similar size or
  region of country

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Add-on Benefits

• No local staff work to write RFP, review
  proposals, manage and administer contract
• Final product is quality-tested file that is
  weighted, edited, documented and ready-to-run
• Local control over sample size and strata
• Trip origins and destinations geocoded with high
  accuracy
• National sample cases in your area included
  without additional cost
• Local funding match has been historically waived

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In 2001, 9 areas were add-ons
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Number of Local Samples in 2001
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Some Applications

• Inputs to Travel Demand Forecasting
• Air Quality Analysis
• Trend Analysis
• Trip Chaining
• Comparison with Census
• Special Studies

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National Household Travel Survey Add-On Use at
Wisconsin State DOT
State DOT Example
Courtesy Kimon Proussaloglou, Cambridge
Systematics Inc.
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Project Objectives Statewide Model

• Decision-making support to the Long Range Plan
• Passenger model
• Policy-sensitive multimodal evaluation framework
• Diversion among routes Corridor 2020, Intercity
  corridors, Key metropolitan corridors
• Diversion to improved intercity modes
• Freight model - intercity commodity flows
• Linkages to WisDOT management systems
• TAFIS
• STN and WISLR

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Wisconsin MPO Models
Wausau
Eau Claire
Stevens Point
W. Rapids
Green Bay
Appleton/Oshkosh
La Crosse
Sheboygan
Fond du Lac
Madison
Janesville/Beloit
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Integration of Statewide and MPO Models

• Consistency in
• Travel data sources NHTS add-on
• Zonal structure and socioeconomic inputs
• Network detail and input assumptions
• Software platform and overall model approach
• MPO model results within the MPO boundaries
• Best practical approach to model integration
• External station trip data from statewide model

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NHTS Add-on as a Key Data Source

• Size and distribution of survey databases
• Household file (N17,600)
• Person (N41,000)
• Vehicle (N38,000)
• Daily Trips (N164,000)
• Long Distance Trips (N44,000)
• Most recent long distance travel
• Stratified sampling plan
• Oversample individual MPOs
• Modeling at state and MPO levels
• NHTS sample-weighting approach

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NHTS Location of Sampled Households
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Model Components
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Household Characteristics
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National Household Travel Survey Add-On Use in
the Des Moines, Iowa, Metropolitan Area
Small/Medium MPO example
Courtesy Adam Noelting, Des Moines Area MPO
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Des Moines Area MPO

• Des Moines Area MPO Population, 2000 U.S. Census
  395,072
• Population of Four-County Study Area, 2000 U.S.
  Census 470,041
• Des Moines Area MPO Area 500 Square Miles
• Four-County Study Area 2,319 Square Miles

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NHTS Add-On

• Des Moines Area Metropolitan Planning
  Organization (MPO), in cooperation with the Iowa
  Department of Transportation (DOT), participated
  in the 2001 NHTS add-on survey
• The last time extensive travel data was collected
  for the Des Moines area was the 1960s

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Data Use Travel Demand Modeling

• Necessary for creation of Year 2030 LRTP
• Utilized 7,506 vehicle trips to determine
  Non-Home Based (NHB), Home-Based Other (HBO), and
  Home-Based Work Trips (HBW)
• Expected NHB trips to rise, due to from increased
  trip chaining
• NHB did not increase significantly, validating
  previous model inputs
• HBO and HBW trip percentages both increased over
  previous inputs
• Used household size and vehicles/hhld to update
  cross-classification trip rates
• Data showed smaller household sizes and more
  vehicles /hhld
• Cross-classification tables aided the calibration
  of the model

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Data Use Mode Choice Modeling and Travel Time
Survey

• Transit usage evaluated
• Transit usage accounted for less than 1 percent
  of total trips and approximately 1 percent of
  work trips
• Mode Choice Modeling not warranted by transit use
  percentage
• From the 2001 NHTS Add-on data, in terms of
  person trips, the afternoon/evening commute is
  the most heavily traveled time of day
• Lunchtime also is more heavily traveled than the
  morning commute hours

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Data Use Travel Time Survey
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National Household Travel Survey Add-On Use in
the Baltimore, MD, Metropolitan Area
Large MPO example
Courtesy Charles Baber Baltimore MPO
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Auto-Ownership
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Vehicle Availability and Licensed
DriversRelationship per Household
Inside Baltimore City
Outside Baltimore City
Drivers Drivers
Drivers Vehicles
Vehicles
Vehicles
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48
5
Drivers
Drivers
Vehicles
Vehicles
9
10
Drivers
Drivers
Drivers
Vehicles
or
or
66
Vehicles
Vehicles
0
0
38
6
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Motorized Person Trips by Purpose
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Some General Issues
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Work Trips Have Declined as a Proportion of All
Trips
Work Travel as a Proportion of All Travel
Number (in Percent)
40
30
20
10
0
1969
1977
1983
1990
1995
2001
Person Trips
Person Miles of Travel
Vehicle Trips
Vehicles Miles of Travel
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Thats Because Other Types of Trips are
GrowingFaster than Work Trips
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And those Trips have Different Time-of-Day
Profiles
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Traffic can be Worse Midday Saturday than During
Weekday Peak Hours
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More than Half of all Workers Stop During their
Commutes to Work
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We Think We Know whatComplex Work Tours Look Like
Pick
-
up Present for
Boss Birthday
Drop Child At Daycare
Home
Work
Pick Child up at Daycare
Boss Birthday
Lunch
Pick
-
up Groceries for Dinner
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But Real Life is Messy
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Usual Mode to Work
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Accessing NHTS Data

• Web-tool http//nhts.ornl.gov
• SAS Data Set with Documentation Available at
• http//nhts.ornl.gov/2001/html_files/download_dire
  ctory.shtml

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http//nhts.ornl.gov
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Contact Susan.Liss_at_fhwa.dot.gov Nanda.Srinivasan_at_f
hwa.dot.gov Nancy.Mcguckin_at_fhwa.dot.gov 202-366-
0160