# Presentation: 261773

## The National Household Travel Survey

- Nanda Srinivasan, Cambridge Systematics Inc.
- Nancy McGuckin, Travel Behavior Analyst

## About the NPTS...

_**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.

_**Target Population**__:_
-   Residents in households (all ages)
-   Group quarters are not included.

## 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

- What Kinds of Information Does the Survey Obtain?

## 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

## 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, < 250K
- 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)

## National Household Person and Vehicle Trip Rates

|  | Person Trips/Day | Vehicle Trips/Day | P-trips/
V-Trips |
| --- | --- | --- | --- |
| Work and Work Rel | 1.9 | 1.6 | 1.2 |
| Shop | 2.1 | 1.3 | 1.6 |
| Fam/Pers | 2.3 | 1.5 | 1.6 |
| Soc/Rec | 2.7 | 1.2 | 2.3 |
| Misc | 1.4 | 0.5 | 3.0 |
| All | 10.4 | 6.0 | 1.8 |

*Benchmarking*

## National Household-based Person Trips by Type

| Income | HBW | HBO | NHB | All |
| --- | --- | --- | --- | --- |
| <$35K | 0.4 | 3.3 | 4.0 | 7.7 |
| $35-60K | 0.7 | 4.8 | 6.0 | 11.5 |
| $60-80K | 0.9 | 5.8 | 7.2 | 13.9 |
| $80K+ | 0.9 | 6.3 | 8.0 | 15.1 |
| All | 0.6 | 4.4 | 5.5 | 10.6 |

*Benchmarking*

## 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

## 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

## In 2001, 9 areas were add-ons:

## Number of Local Samples in 2001

| JURISDICTION
 | Number of Local Samples Purchased | Number of National Samples (Free) | Total Number of Samples |
| --- | --- | --- | --- |
| HI ‐ Hawaii DOT |  1,694 | 19 | 1,713 |
| HI ‐ Oahu MPO |  1,751 | 55 | 1,806 |
| IA ‐ Des Moines MPO |  1,310 | 49 | 1,359 |
| KY ‐ Kentucky DOT  |  1,226 | 12 | 1,238 |
| MD ‐ Baltimore MPO |  3,804 | 231 | 4,035 |
| NY ‐ New York DOT | 11,887 | 1,536 | 13,423 |
| PA ‐ Lancaster MPO | 1,030 | 46 | 1,076 |
| TX ‐ Texas DOT |  4,065 | 1,478 | 5,543 |
| WI ‐ Wisconsin DOT  | 17,012 | 535 | 17,547 |
| Total samples | 43,779 | 3,961 | 47,740 |

**Notes:**
40,000 households in specific geographic areas added by local planning agencies

State Add-Ons:  Hawaii, Kentucky, New York, Texas, and Wisconsin

MPO Add-Ons:  Baltimore MD, Des Moines IA, Lancaster County PA, and Oahu HI.

## Some Applications:

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

## National Household Travel Survey Add-On Use at Wisconsin State DOT

- Courtesy: Kimon Proussaloglou, Cambridge Systematics Inc.

- State DOT Example

## 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

## Wisconsin MPO Models

**Eau Claire**

**Appleton/Oshkosh**

**Green Bay**

**Janesville/Beloit**

**Madison**

**Sheboygan**

**La Crosse**

**Wausau**

**Fond du Lac**

**Stevens Point**

**W. Rapids**

## 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

## NHTS Add-on as a Key Data Source

- Size and distribution of survey databases
- Household file (N=17,600)
- Person (N=41,000)
- Vehicle (N=38,000)
- Daily Trips (N=164,000)
- Long Distance Trips (N=44,000)
- Most recent long distance travel
- Stratified sampling plan
- Oversample individual MPOs
- Modeling at state and MPO levels
- NHTS sample-weighting approach

## NHTS – Location of Sampled Households

## Model Components

## Household Characteristics

## National Household Travel Survey Add-On Use in the Des Moines, Iowa, Metropolitan Area

- Courtesy: Adam Noelting,
- Des Moines Area MPO

- Small/Medium MPO example

## 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

## 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 1960’s

**Notes:**
The National Household Travel Survey is conducted roughly every 5 years, with 25,000 surveys taken nationally in 2001.  The NHTS looks at the amount and nature of personal travel in the United States.  

In 2001, the Des Moines Area MPO, equally with the Iowa DOT, participated in the NHTS Add-On program.

## 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

**Notes:**
Applied weighting factors to the vehicle trips to determine the trip types necessary for the Des Moines Area MPO’s Travel Demand Modeling process.

Non-Home Based trips are those with neither trip end at home.  For example, running errands, from home to a shopping mall is Home Based Other, but from shopping mall to grocery store is Non-Home Based.

## 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

**Notes:**
Transit usage accounted for .03 percent of all trips and 1.1 percent of work trips.

Although Mode Choice Modeling is not currently necessary, it may be needed in the future following increased efforts by the Des Moines Metropolitan Transit Authority and by the Transportation Management Association to increase transit ridership and to reduce total traffic on Des Moines metropolitan area roadways by 10 percent.  

The Des Moines MTA is also considering participation in FTA’s New Starts program, which would necessitate a Mode Choice model, no matter what the NHTS data states.

## Data Use: Travel Time Survey

## National Household Travel Survey Add-On Use in the Baltimore, MD, Metropolitan Area

- Courtesy: Charles Baber
- Baltimore MPO

- Large MPO example

## Auto-Ownership

## Vehicle Availability and Licensed DriversRelationship per Household 

**Inside Baltimore City **

**Drivers = **

**Vehicles**

**48%**

**Drivers < **

**Vehicles**

**5%**

**Drivers > **

**Vehicles**

**9%**

**Drivers **

**or **

**Vehicles **

**= 0**

**38%**

**Outside Baltimore City**

**Drivers = **

**Vehicles**

**66%**

**Drivers > **

**Vehicles**

**10%**

**Drivers **

**or **

**Vehicles **

**= 0**

**6%**

**Drivers < **

**Vehicles**

**18%**

## Motorized Person Trips by Purpose 

## Some General Issues

## Work Trips Have Declined as a Proportion of All Trips

- Work Travel as a Proportion of All Travel

- 0

- 10

- 20

- 30

- 40

- 1969

- 1977

- 1983

- 1990

- 1995

- 2001*

- Person Trips

- Person Miles of Travel

- Vehicle Trips

- Vehicles Miles of Travel

**Number (in Percent)**

## That’s Because Other Types of Trips are GrowingFaster than Work Trips

**Notes:**
The proportion of working aged people, that is 16 to 65 years old, who are workers is growing. 46 percent of the total population, and nearly 70 percent of people 16 and older are workers. Compared to 49% in Europe, 50% in Asia, and 51% in Australia.  Potentially, this proportion will continue to grow.

## And those Trips have Different Time-of-Day Profiles

## Traffic can be Worse Midday Saturday than During Weekday Peak Hours 

## More than Half of all Workers Stop During their Commutes to Work

## We Think We Know whatComplex Work Tours Look Like

**Home**

**Work**

**Boss’ Birthday**** **

**Lunch**

**Drop Child At Daycare**

**Pick**

**-**

**up Present for **

**Boss’ Birthday**

**Pick**

**-**

**up Groceries for Dinner**

**Pick Child up at Daycare**

## But Real Life is Messy

**Notes:**
Importantly, however, many non-work trips are planned around the work trip, such as dropping children at school or daycare.  Real life examples show that the time, location, and frequency of these other trips can be dictated by the work trip as people respond to the pressures of work and home. We need greater detail on the geography of stops made during commutes, and how these stops are affecting the work trip. This kind of detail can be obtained from a household travel survey.

## Usual Mode to Work

## Accessing NHTS Data

- Web-tool: _[http://nhts.ornl.gov](http://nhts.ornl.gov/)__ _
- SAS Data Set with Documentation Available at:
- http://nhts.ornl.gov/2001/html_files/download_directory.shtml

**Notes:**
To use the “Online Analysis” tool, click on the button at the top of the page, and click “Create a Table”.

**http://nhts.ornl.gov**

## Contact

***Contact***
**Susan.Liss@fhwa.dot.gov**
- _[Nanda.Srinivasan@fhwa.dot.gov](mailto:Nanda.Srinivasan@fhwa.dot.gov)__ _
- _[Nancy.Mcguckin@fhwa.dot.gov](mailto:Nancy.Mcguckin@fhwa.dot.gov)_
**202-366-0160**