Highway
istration

The Exploratory Advanced Research Program Fact Sheet

Understanding Long-Distance

Traveler Behavior

Supporting a Long-Distance Passenger Travel Demand Model

Exploratory Advanced Research Next Generation Transportation Solutions

Long-Distance Modeling

Highway infrastructure planning, high-speed rail
development, and airport growth all depend on
long-distance travel markets. To ensure
infrastructure can meet growing demands in
these areas there is a need to model and analyze
passenger behavior. Interest in long-distance
passenger modeling for statewide models has
already been seen in California, Ohio, and
Arizona, and high-speed rail studies have been
conducted in Florida, California, and the
Northeast Corridor; however, these models have
been based on traditional travel demand
forecasting methods rather than a_ robust
understanding of underlying behavior and how
and why long-distance passenger movements
differ from other passenger travel.

Exploring Passenger Travel

Long-distance travel behavior will be explored in
several key areas that move beyond traditional
methods used for existing statewide models.
For example, long-distance trips are scheduled
weeks or months in advance of the trip and
typically last several days or weeks. There are
also significant seasonal effects that can
influence long-distance travel, unlike short-
distance travel which remains similar day-to-day.
Both leisure and business travel are more
sensitive to changes in the economy than short-
distance travel and leisure activities will often
differ from business activities as they are
planned and executed with different goals and
choices. Party size can also have a significant
effect on mode and destination choices.

Current Techniques and Challenges

Several observations have been made based on
current modeling techniques. Recreational
travel models typically adopt a similar structure
to business and other travel, despite broad
differences between the two. Business models
are generally more time-sensitive and less
concerned with party size as a mode choice
variable when compared to recreational travel
models. For example, a business traveler on a
long-distance trip is more likely to fly regardless
of expense or the number of colleagues
traveling in the party. A family on vacation,
however, may decide to drive to save money
even if the trip takes longer. Although advanced
integrated activity-based models are currently
operational, these are limited to an estimate of
average weekday travel and do not account for
scheduling, influence of other trips, other
travelers, or social character.

An additional challenge is that no single
dataset offers all the required features for
estimating and applying long-distance travel


com
att Tilghman

Publication No.
FHWA-HRT-13-095
HRTM-30/9-13(1M)E

Understanding Long-Distance Traveler Behavior

Supporting a Long-Distance Passenger Travel Demand Model

demand forecasting models in the United States.
A series of datasets have been identified for
exploring long-distance models and the results
will be a modeling framework that can be re-
estimated once national long-distance travel
data become available. The research team will
use their experience to bridge the gap between
ideal modeling design and implementing a tool that
will be of practical use to planners.

Delivering a National Model

The ultimate goal of this study is to explore new
approaches for a national model that is
estimated, calibrated, and validated on available
long-distance travel data in the United States
and can subsequently be updated with new
long-distance travel data for use in planning
applications around the country. In the short
term, this project will examine possible new
frameworks for a national model that identify
specifications based on statistical analysis of
available data.

“The framework being developed can provide
a foundation for subsequent implementation of
an innovative national passenger forecasting
model,” said Brad Gudzinas at FHWA. “The
products of this research are first steps toward
providing the tools needed to identify significant
future travel trends and, ultimately, to make
more informed decisions about policy and
infrastructure investments,” he added.

Learn More

For more information on this EAR Program
project, contact Brad Gudzinas, FHWA Office of
Highway Policy Information, at 202-366-5024
(email: brad.gudzinas@dot.gov).

EXPLORATORY ADVANCED RESEARCH

What Is the Exploratory
Advanced Research Program?

FHWA‘s_ Exploratory Advanced Research
(EAR) Program focuses on long-term, high-
risk research with a high payoff potential.
The program addresses underlying gaps
faced by applied highway research
programs, anticipates emerging issues
with national implications, and reflects
broad transportation industry goals and
objectives.

To learn more about the EAR Program,
visit the Exploratory Advanced Research
Web site at www.fhwa.dot.gov/
advancedresearch. The site features
information on research solicitations,
updates on ongoing research, links to
published materials, summaries of past
EAR Program events, and details on
upcoming events. For additional
information, contact David Kuehn at FHWA,
202-493-3414 (email: david.kuehn@dot.gov),
or Terry Halkyard at FHWA, 202-493-3467
(email: terry.halkyard@dot.gov).