We’ve all suffered
the frustration of being lost.
searched for something familiar to help us find our way—maybe
a sign, a landmark or perhaps we tried to retrace our steps. According
to research at The University of Texas at
Austin, there may be a better way to navigate.
Dr. Brian Stankiewicz,
assistant professor in the Department of Psychology and Center
for Perceptual Systems, studies spatial navigation
and object recognition. His research uses virtual reality environments
to help pinpoint the information and process needed to navigate
through large-scale spaces such as a building or city.
Brian Stankiewicz stands in front of a scene from a virtual
“Everyday we are able to navigate from one location to another,” Stankiewicz
said. “But how? Do we carry a mental map in our heads? Do
we know what a particular street corner looks like or do we simply
remember something like a road map? What I’m particularly
interested in is what we remember and store about an environment
so that when we return we are able to way-find and move to a particular
Just for fun, close your eyes and try to remember
your last commute. Maybe you went to work, school or a friend’s
it’s a place you travel to daily. What is it you remember
about your surroundings along the way?
A series of experiments
compared the importance of visual cues such as pictures on the
walls, doors and signs, versus topological
structures such as the way roads or hallways interconnect.
“We found that people learned the topological structure
more rapidly,” Stankiewicz
So next time you’re in a building or an area of town
that you frequently find yourself lost in, try paying more attention
to how the hallways or roads connect. Maybe they form a T- or L-shape.
Try building your own “mental map” of the location
and see if things improve on your next visit. You’ll be one
step closer to being a more efficient navigator.
put this to the test by creating human and robot models to predict
human behavior in different navigational situations
and to measure efficiency. If navigation was a video game, think
of the robot model as the competitor that always makes the perfect
score you’re trying to beat.
Imagine being dropped off in
random locations within a building and asked to find your way to
a target location. All the walls
are identical. The only difference is the way they connect. This
scenario is created in a virtual environment for the study.
Stankiewicz takes a sneak peak at virtual reality.
“Humans take about twice as many actions as it does the
robot model to complete this task,” Stankiewicz said.
attributes this to a breakdown in a process called hypothesis maintenance.
In the building, as the person looks around, he or
she is constantly making new observations. Maintenance occurs when
the person uses this new information to update his or her beliefs.
It is a type of mental checklist that allows a person to confirm
a location or rule out others.
During a second phase of the experiment,
this information was maintained on the subject’s behalf.
Arrows were displayed in a viewfinder to help the subject keep
track of where he or she had been.
“When they no longer have to keep track of this information
in their heads, we can get them to navigate almost optimally,” Stankiewicz
said. “When a subject is lost, they are most likely stressed
and frustrated, which can make the hypothesis maintenance process
even more difficult.”
Another series of experiments is the
development of a training regimen for low-vision navigation. Low
vision means the subject
can see, but his or her perception is greatly hindered as a result
of a variety of diseases, disorders and injuries that affect the
eye. Many people with low vision have age-related macular degeneration,
cataracts, glaucoma or diabetic retinopathy. According to “The
Lighthouse National Survey on Vision Loss: The Experience, Attitudes,
and Knowledge of Middle-Aged and Older Americans,” about
14 million Americans, about one out of every 20 people, have low
vision, and about 135 million people around the world have low
Stankiewicz models the viewfinder used to experience the
virtual reality environment.
“Most people with low vision can navigate through familiar
environments just fine,” Stankiewicz said. “It is when
they have to go to a novel environment that they may have trouble.”
led to the idea that if people could access a corresponding virtual
environment via their computer before visiting the real
location they could familiarize themselves before having to truly
“Our first question was, ‘How well matched does the
virtual environment have to be to the real one?’” Stankiewicz
Stankiewicz’s team ran a number of conditions. One
example included a low-resolution environment that was very sparse.
constructed walls, the bare minimum. The second was a high-resolution
environment using detailed video footage.
“When we took the subjects to the real environment they
were nearly as good after training on the low-resolution environment
were after training in the high-resolution one,” he said.
Once again, the emphasis is on learning the topological structure.
If the subjects were able to learn the basic layout, they were
able to navigate. Having more details in the environment didn’t
make a big difference.
Another piece of the low-vision training
research is creating a small handheld navigation device. For example,
a person about to
visit the Empire State Building could download a map of that building
to the device. Once in the building, the device would collect and
process information to determine its user’s location. It
would then give directions to his or her desired location.
future research will examine the differences in people’s
navigational strategies and the way they acquire information.
“Once we understand the parameters of what makes someone a good
or bad navigator, we can ultimately teach someone the strategies
to become a more efficient navigator,” he said.