4.3. Activity Participation, Trip Behavior, and
Travel Times
Another procedure used to determine the effect of non-sighted navigation on
people’s lives is to examine the activities they participate in, how often
they participate, and how long it takes to make the necessary trips.
Conventional accessibility measures have long used these types of data to help
determine how much time or effort is required to access various locations.
These models have a utility function, which often assumes that people
want to minimize time or distance in their daily trips. In the travel
environment faced by certain groups, especially those with limited vision, an
examination is called for to determine whether time or distance expense is really
the utility that they desire to minimize.
For instance, they might want to avoid busy or dangerous intersections, shop
at stores with familiar layouts or personnel, or stay on a bus instead of making
a transfer, even though these choices might increase travel time or distance.
Instead of searching for the most optimal spatial location, activities might
be more focused on making sure the actual task or trip purpose can be performed
easily and with less stress.
For a blind person, these are not “incorrect” decisions, as typical
models would indicate. There are other problems when using conventional
accessibility methods to measure blind people’s accessibility, and, before
discussing the data on time and trip behavior these other problems and difficulties
are discussed, and an analysis is made of how conventional measures might not
be suitable for the study of certain groups.
In Section 2.3 , Measuring Accessibility
, accessibility measures and problems associated with accurate modeling were
introduced. In its most basic form, “accessibility” is a measure
of an individual’s freedom to participate in activities in the
environment (Weibull, 1980) . Previously, a discussion of some of the
restrictions on independent travel was made, such as time penalties, safety
concerns, and the fear and stress that are faced by a traveler without vision.
These restrictions diminish the individual’s freedom to participate in
accessing urban opportunities.
Conventional accessibility measures assume “perfect knowledge” of
the environment by users, meaning that they know of all choices for all activities.
Just like a visitor or new resident in a town who makes “incorrect”
spatial decisions, many blind people can have trouble quickly assimilating enough
spatial knowledge to afford them completely rational decision making. The
lack of access to printed signs, distal cues, and spatial and environmental information,
as well as confinement to fixed transit and learned walking routes of travel,
all restrict spatial knowledge acquisition. Because of this, blind people
might be unaware of changes and opportunities in the environment, even including
what is available across a street or around the corner from their normal path.
Anecdotal evidence is replete with stories about blind people not being
aware of changes in the urban landscape and of making “incorrect”
spatial decisions because of the lack of spatial knowledge. Work on feasible
opportunity sets (Golledge et al., 1994) shows the effect of an individual’s
spatial knowledge on the size and spatial configuration of the available choice
set of locations when making spatial decisions. Therefore, the blind person
with restricted spatial awareness is an imperfectly informed decision-maker and
might be faced with a limited opportunity or choice set when making spatial search
decisions.
When working with a subset of the general public, such as people with visual impairment,
it is necessary to make sure not to confuse a measure of place or location
accessibility with individual accessibility (how easily a person can
actually reach activity locations). Individual accessibility is determined
not by the number of opportunities that are close by, but whether or not these
opportunities are within reach, considering the person’s life situation
and adaptive capacity (Dyck, 1989) . Conventional accessibility models based
on the proximity of locations of urban opportunities cannot account for the personal,
highly diverse differences of human behavior and skills. They often tend
to actually reflect place accessibility, more than a measure of an individual’s
accessibility. Therefore, it is inappropriate to mistakenly attribute the
locational or place accessibility, such as of a traffic zone or
census tract, to a person in that area (Pirie, 1979) . This conceptual framework
is important in understanding the “true” accessibility experienced
by blind people.
Because persons who are legally blind do not drive cars, they are often transit-dependent
and, in addition, might need to make several transfers to reach a location.
These rides, and especially the transfers, can introduce much more travel time
randomness into their trip. In many cities, it is not easy to plan an arrival
time when using transit and making transfers, and this certainly adds a great
deal of variance to trip times. In addition, people with vision restrictions
might have to budget more time for unforeseen barriers, unfamiliar environments,
or new obstacles in the environment. Time constraints, spatial knowledge
acquisition and processing, fear of new environments, safety concerns, and stress
all figure in the spatial search equation for the blind. For these reasons,
traditional measures of access that rely on location-based properties do not capture
the true accessibility of this group.
For the general public in the built environment, all locations are accessible
from all other locations. There might be high levels of time, effort, or
expense to overcome, but locations can be reached. For people who
use wheelchairs, areas and locations still exist that cannot be reached,
no matter how much effort is expended. The same appears to be true, in
many situations and locations, for many visually impaired people when traveling
independently.
In previous sections, documentation was provided on the difficulty of tasks (see
Section 3.2 User Rated Difficulty of Transit Tasks )
and the increased travel time required by navigation without sight (see Section
3.1 Caltrain Field Test ). However, restrictions to access and travel
go far beyond the increased effort and time. There are locations that are
so difficult to access that they form a barrier as formidable as a physical barrier
is for users of wheelchairs. If a street cannot be crossed, or a bus stop
or entrance can’t be found, that one task can cause the whole trip to be
abandoned. Even one difficult street crossing can cause an entire area
of the environment to become totally inaccessible. In addition, a series
of difficult tasks, especially in an unfamiliar area, can cause a trip to not
be attempted at all because of daily time constraints and increased apprehension
and fear. Therefore, there are some trips that are not taken by this group
even though there are no true physical barriers preventing them. Access
for the blind is restricted by more than time constraints, they also face barriers,
such as the lack of spatial information, fear, confusion, safety concerns, and
other perceived stressful situations. Thus, independent travel for the
blind can be blocked by the effect of the environment on the potential traveler.
These types of barriers to travel are not addressed in conventional measures
that deal mostly with the physical relationship between locations.
Gender bias and ethnic or minority bias can also occur in traditional accessibility
measures. Kwan (1998a, 1999) says that conventional spatial accessibility
measures of access to jobs or shops are meaningless for women whose activity choices
were continually complicated by additional time constraints due to their gender
roles. It is postulated here that people with vision restrictions also
can face many constraints on their travel time and spatial knowledge, and that
these can be quite different than those faced by the typical traveler.
People with vision impairments might try to maximize a different utility than
simple time or distance reduction, due to apprehension while in new environments
and situations. This, for example, leads to the belief that there also
exists a “disabled bias” to conventional accessibility models.
In addition, different levels of an individual’s physical mobility (or mode
of travel) can affect the distance or time effort of the shortest accessible path
in small-scale areas, like buildings, such as the graphic display referred to
by Okunuki, Church, & Marston (1999) or larger scale areas, such as a campus
sidewalk network (Church & Marston, in press) . Thus, there are often
longer but still “correct” shortest paths that are used to overcome
physical and other barriers in the environment.
Travel times have long been used as a measure of accessibility to various locations
and functions. There is little agreement, however, on how to interpret
these data. For example, a long work commute might represent a successful
professional’s trip from a desired and isolated residential area to a
prestigious job in the central city. Conversely, a long work trip might
be the result of a spatial mismatch between an employer-abandoned inner city
and an employer-rich suburban area. This situation often requires a long
and arduous transit trip with many transfers in order to find employment.
A short work trip might be the result of child-care and other gender-role constraints
on suburban women whose choices of jobs are from the many female-oriented jobs
available in the suburban area. In the past, short work trips were often
associated with blue-collar workers who, for economic reasons, lived near the
factory or warehouse. However, a short trip can also result from a highly
paid worker’s decisions to live in or near the central city.
The same inconsistencies are also found in other trip types, such as shopping,
social, or recreational activities. People with cars and economic resources
might choose to live far from commercial locations and
prefer to shop or recreate at various and prestigious places scattered around
the urban area. A short shopping trip could represent a person on a limited
budget who is forced to walk and must perform these activities at a location
close to home. Conversely, an inner-city resident might be forced to take
long trips by transit to find a full-service grocery store. A short recreation-based
trip might indicate that the only affordable spot is one they can walk to, while
a long trip might be made by an economically successful person choosing to travel
a long distance to play golf at different courses. For these reasons,
it is impossible to assess a “correct” interpretation of the true
meaning of travel times and accessibility. Examples of both long and
short activity travel times are examined in the following data from the blind
subjects in this experiment.
In this section, the data collected about transit trip times, walking times,
and the total roundtrip time taken to access various urban opportunities are
reported. Data were collected during the pre-test interview about subjects’
current weekly travel activities. Subjects reported the number of trips
they made for nine different activity purposes. They also reported the
roundtrip transit time and also their walk time.
4.3.2.1. Travel Time by Activity Type
Table 4.5 shows the mean roundtrip transit travel time,
the walking time, and the total trip time in minutes. Activities are shown
sorted from the longest trip to the shortest trip. Some subjects did
not report walk time for their transit trip (cabs and other at-location pickups)
and others walked the entire trip without using a vehicle. For these reasons,
the total trip times are not the simple sum of the total transit and walk times
shown on the table.
Table 4. 5 Transit Time, Walk
Time, and Total Travel Time
|
Trip Activity
|
Transit Time
|
Walk Time
|
Total Trip Time
|
|
Round Trip Time In Minutes
|
|
Work
|
107
|
33
|
136
|
|
Education
|
63
|
33
|
84
|
|
Social
|
75
|
30
|
82
|
|
Entertainment
|
65
|
23
|
72
|
|
Religious
|
75
|
37
|
59
|
|
Recreation
|
44
|
33
|
54
|
|
Medical
|
38
|
16
|
38
|
|
Shop
|
25
|
27
|
35
|
|
Banking
|
18
|
23
|
26
|
|
Mean of those making trip
|
503
(8.4 Hours)
|
250
(4.2 Hours)
|
586
(9.8 Hours)
|
|
Mean for all 30 subjects
|
193
(3.2 Hours)
|
105
(1.8 Hours)
|
298
(5.0 Hours)
|
Many people did not make all types of trips. The mean travel time for all
the subjects was 3.2 hours in-vehicle and 1.8 hours walking, for a total of 5.0
hours of travel per week. The data in the table and that discussed below
are only for those who reported making a trip for that activity. The mean
weekly travel time for those who made trips was 9.8 hours, with 8.4 hours riding
a vehicle and 4.2 hours walking. The use of private car rides was very
low, as reported in another part of the interview. Almost all trips were
made independently using public transportation, and the term transit is used here
to include any vehicle ride.
The mean transit time for those who made work trips was 107 minutes; they walked
33 minutes, and the total roundtrip time was 136 minutes. There were 17
trips reported, and 17 people reported transit use and two people did not report
any walk time. The longest work trip was 390 minutes and the shortest was
30 minutes.
The mean transit time for those who made trips to participate in educational activities
was 63 minutes; they walked 33 minutes, and the total roundtrip time was 84 minutes.
There were eight trips reported, six people reported transit use and walking,
one reported transit only, and one reported walking only. The longest education
trip was 165 minutes and the shortest was 30 minutes.
The mean transit time for those who made trips for social activities was 75 minutes;
they walked 30 minutes, and the total roundtrip time was 82 minutes. There
were 25 trips reported, 12 people reported transit use and walking, nine reported
transit only, and four reported walking only. The longest social trip was
270 minutes and the shortest was 10 minutes.
The mean transit time for those who made entertainment trips was 65 minutes; they
walked 23 minutes, and the total roundtrip time was 72 minutes. There were
16 trips reported, 10 people reported transit use and walking, three reported
transit only, and three reported walking only. The longest entertainment
trip was 150 minutes and the shortest was 20 minutes.
The mean transit time for those who made religious trips was 75 minutes; they
walked 37 minutes, and the total roundtrip time was 59 minutes. There were
12 trips reported, three people reported transit use and walking, one reported
transit only, and eight reported walking only. The longest trip was 200
minutes and the shortest was 10 minutes.
The mean transit time for those who made trips to recreational locations was 44
minutes; they walked 33 minutes, and the total roundtrip time was 54 minutes.
There were nine trips reported, four people reported transit use and walking,
one reported transit only, and four reported walking only. The longest
trip was 105 minutes and the shortest was two minutes.
The mean transit time for those who made medical trips was 38 minutes; they walked
16 minutes, and the total roundtrip time was 38 minutes. There were six
trips reported, three people reported transit use and walking, one reported transit
only, and two reported walking only. The longest trip was 60 minutes and
the shortest was 20 minutes.
The mean transit time for those who made shopping trips was 25 minutes; they walked
27 minutes, and the total roundtrip time was 35 minutes. All 30 subjects
reported making shopping trips, 10 people reported transit use and walking, eight
reported transit only, and 12 reported walking only. The longest trip was
130 minutes and the shortest was two minutes.
The mean transit time for those who made banking trips was 18 minutes; they walked
23 minutes, and the total roundtrip time was 26 minutes. There were 15
trips reported, three people reported transit use and walking, no one reported
transit only, 11 reported walking only, and one person reported no extra time
(ATM at the store). The longest trip was 65 minutes and the shortest was
10 minutes.
There is a large variation in reported total trip times and
trip frequency. The mean weekly travel time was 5.0 hours. Figure
4.1 shows the data for each subject sorted from lowest to highest weekly trip
times.
Figure 4. 1 Travel Times per Person
One subject reported travel of only 20 minutes per week,
while another traveled 40 minutes per week. Three more traveled between
1.2 and 1.7 hours per week for a total of five who traveled two or fewer hours
during the entire week. Ten subjects reported total travel time between
2.5 and 3.8 hours per week. Five traveled between 5.1 and 5.9 hours, while
another six reported times between 6.3 and 8.0 hours. Three reported
times of 8.8 to 9.4 hours, and one person (a salesman) reported 15.5 hours of
weekly travel. To better understand these data, it must be kept in mind
that these subjects were not among the estimated 30% of blind people that Clark-Carter,
et al. (1986) say never leave the home for independent travel.
These subjects had the training, skills, and motivation, to travel to the test
site in downtown San Francisco. Most subjects did not live in the City
and so many traveled quite a few miles from across the Bay or from South Bay
areas. It must, therefore, be expected that mean travel times and the
number of trips reported would be even lower when considering the entire population
of people with vision restrictions.
4.3.3. Activity Participation
and Trip Frequencies
A compelling reason to live in a large urban area, especially
for those who do not drive a car, is the large range of activities and urban
opportunities that are available and easily accessible through mass transit.
When considering all the daily activities a person has to choose from, the following
data provide blunt evidence that people with vision restrictions face limitations
in their activities and travel, and that there are major restrictions and barriers
that affect everyday life activities for this group.
Figure 4.2 displays the number of trips reported by the
subjects, sorted from lowest to highest frequency. The mean number of
trips reported was 12.1 per week.
Figure 4. 2 Total Trips per Person
The activities and trips that subjects reported included any function that took
place outside the home. The data on individual activity participation show
a wide range, and the variation warrants a closer look at individual behavior.
Nine subjects (30%) participated in only seven or less activities in an
entire week (one per day.) Three subjects left their home for two activities
during a week, one apiece reported 2.5, 3.5, and 4.0 trips, two took five trips
and one took seven. Another 13 subjects (43%) reported 14 or fewer activities
per week. From the sample of 30 blind subjects who were active and skilled
enough to navigate to the test site, fully 73% participated in two or less activities
outside their home per day. Another five subjects reported between
15 and 21 trips per week, and one made 23 trips. Two subjects reported
high trip and activity participation of 32 and 35 trips per week. These
two young adults were part of a residential program, had useful vision, and were
very social. They reported many trips to visit friends in adjacent apartments
and regarded their many trips to the local “hangout” corner store
as either social or shopping.
The previous section reported on the number of trips actually made by the test
subjects. There is more to understand about trip and activity behavior of
the blind than just explanatory statistics and descriptions of actual trip frequency
patterns and distribution. Trip frequencies and activity participation data
are widely used by marketing professionals, and urban and transportation planners.
A major principle in transportation planning is that, by removing barriers
to access and increasing throughput, accessibility in the system can be increased,
and no one seems to deny that curbs and stairs are major barriers to activities
for those using a wheelchair.
Transportation planners can easily compute the effect on accessibility of improvements
such as wheelchair accessible buses, a new limited-access highway, a new transit
line, an express mode, or the elimination of airport service by comparing trip
behavior before and after the change. Urban planners can judge the effects
on accessibility in the environment caused by the installation of curb-cuts and
ramps, a new pedestrian mall, or a parking structure. They can determine
the effect of a big-box mall at the edge of town on downtown business by comparing
previous and current trip behavior after the change. Although accessibility
models can help estimate these changes, these types of comparisons of trip data
can only be made after the change has been implemented.
The ability to make such comparisons in order to understand accessibility for
the blind has been limited, if not impossible. If people’s sight
could be restored, it might be possible to make such comparisons. If RIAS
was already fully installed in an urban area, comparisons of the data before and
after the installation could easily be made. Some kind of comparison of
the blind subjects’ data to other data is called for, but a simple comparison
to data from the sighted would not uncover much of importance. Since there
is no full urban installation of RIAS, hypothetical travel behavior information
was collected from the subjects. In order to research the accessibility
of this group, some questions were asked that have not been researched before.
Prior to subjects’ exposure to RIAS but after the actual weekly trip
data were collected, it was asked if there were trips that subjects did not make
because of problems with their visual impairments’ effect on their independent
travel and the efficient use of transit. The actual questions asked were:
“Do you sometimes avoid trips or
activities because of your visual impairment and the difficulties of independent
travel?”
“If YES, how often during a week
do you avoid these types of trips or activities because of your visual impairment
and difficulties of independent travel?”
The questions were worded this way to try and avoid any frivolous or fantasy desires
or activities. Of the 30 subjects, 20 (67%) said that they avoid some trips
because of travel problems caused by their vision loss. Those who said
they avoided some trips reported how many and what types of trips were not taken.
During the field experiment, subjects experienced transfers to different transit
modes, including a large terminal and street environments that were rich in RIAS
installations. After the experiment, subjects reported how many more trips
they would make if RIAS was as richly installed in their environment as they were
at the test site. All but one subject (97%) reported they would make additional
trips with the addition of RIAS in their daily activity space.
Collecting data on currently desired, but not taken, extra trips and trips they
perceived they would make with RIAS installed produced three data sets to examine.
The actual trip data
The actual trip data plus the desired
but not taken trips (total trips currently desired)
The actual trips plus those trips they would make if RIAS was installed (total
trips they would make with RIAS)
In the discussion, the terms “actual,” “desired,” and
“would make with RIAS” are used to identify these three data sets.
The desired trip data when added to the actual trip data gives a type of control
group for comparison. These data represent the “best-case”
scenario as reported by the subjects if they did not have travel problems relating
to their blindness. Comparison of these three data sets reveal which
and how many trips vision impairment and transit access currently limit and
if the addition of directional and identity cues through a navigation system
is estimated to reduce or cancel these limitations. If “would make
with RIAS” trips are less than the (control group) desired trips that
would show that there were other problems associated with the limitations of
navigation without sight. If the “would make with RIAS” trips
were higher than the desired trips, it would show that the system was perceived
to open up more participation in activities and urban opportunities than the
subjects had previously considered possible. If that is the case, it
suggests that the lack of spatial cues in the environment is a limiting factor
in blind travel. Just like the elimination of physical barriers for those
using wheelchairs, this would show that it is the environment and its barriers
that limit movement and travel, and not the people and their visual condition.
The “desired but denied” data reveals “pent-up”
demand that is not currently being met. The “would make with RIAS”
data reveals what transportation planners call hidden demand .
Highway engineers know that after carefully planning the future capacity of
a new highway, based on existing travel data, the road is soon at full capacity
not long after completion. Thus, there was a hidden demand that
was not revealed until the new link was available. The demand is hidden
because people change and increase their use based on the new accessibility
offered.
Table 4.6 shows the three data sets. Since all 30 of the subjects did
not make all types of trips, the number who reported them is shown as (N=).
The different trip types are sorted with the most frequent currently
conducted activities first. The average number of actual trips reported
was 12.1 trips per week.
Table 4. 6
Actual and Desired Trip Making Behavior
|
N =
The # of
subjects who reported making this type of trip
|
Actual Trips
Made
|
Actual +
Desired Trips
Not Made
|
Actual +
Extra Trips
With RIAS
|
|
N =
|
Mean
Trips
|
N =
|
Mean
Trips
|
N =
|
Mean
Trips
|
|
Shopping
|
30
|
2.6
|
30
|
3.3
|
30
|
4.9
|
|
Social
|
25
|
3.1
|
28
|
3.6
|
27
|
5.0
|
|
Work
|
17
|
4.7
|
17
|
5.0
|
24
|
6.7
|
|
Entertainment
|
16
|
1.4
|
20
|
2.0
|
25
|
2.7
|
|
Banking
|
15
|
1.3
|
19
|
1.5
|
25
|
1.7
|
|
Religious
|
12
|
2.2
|
14
|
2.6
|
15
|
2.6
|
|
Recreation
|
9
|
2.3
|
19
|
2.2
|
25
|
3.1
|
|
Education
|
8
|
3.5
|
13
|
2.6
|
23
|
3.2
|
|
Medical
|
6
|
1.3
|
6
|
1.3
|
8
|
1.2
|
|
Other
|
0
|
0
|
1
|
1
|
0
|
0
|
|
Total Trips
|
30
|
12.1
|
30
|
15.8
|
30
|
25.0
|
When the trips that they did not make because of travel limitations were added,
the average number of trips they desired rose to 15.8, a 31% increase. This
is a realization that the number of trips they do make now is 23% less than
what they desire. The subjects’ data inform that there are strong
limitations on daily activities that are associated with loss of vision, independent
travel, and transit use. After using RIAS, subjects perceived that they
would make 25.0 trips per week, a 107% increase, or, they estimated they are
only making 52% of the trips they would make with RIAS.
All subjects already made shopping trips, and no subjects thought they were
missing any work or medical trips. For all other activities, an increased
number of people thought they would participate if it weren’t for the
problems of independent travel and transit use related to their vision loss.
If they could use RIAS, still more people expressed an interest in participating
in all activities.
For the currently desired trips, the mean frequency increased for all activities
except recreation and education. Both of these activities had high increases
in the number of participants, and the total number of trips was higher, but
the mean was lower. For the “would make with RIAS” trips,
more people desired to participate in activities than they currently did for
every activity type, and except for social (with one less person), more people
said they would participate than they had expressed in the “desired but
denied” question. The total number of trips per activity was higher
than the actual and the perceived data in all cases. The frequency mean
was slightly lower for medical trips, and it was equal for religious trips.
A comparison of the three data sets shows that many activities are denied to
these blind subjects in both number and frequency. Even more important,
it shows that travelers perceive the lack of simple environmental cues as a
major cause of this limitation and that, with the addition of these cues, blind
people could make more trips and more could participate in these activities.
This is an example of what has been earlier described as functional
barriers to travel and transit, and the elimination of these barriers should
substantially increase accessibility and activity participation. To see
how these barriers limit travel for different activities, the percentage change
both in the number of people who said they would participate and in the number
of trips they said they would make is discussed.
Figure 4.3 shows theincrease by percent of the ‘desired” and “would
make with RIAS” trips over the actual trips reported. The data
are ordered from high to low, based on the desired but denied trip data.
About 2/3 of the subjects were congenitally blind and had never experienced
vision. The rest also had no current chance of regaining sight.
Their acceptance of the restrictions of vision loss on their everyday travel
was quite evident from their rather conservative estimates of the number of
trips they thought they were denied because of their vision loss. They
expressed a desire to take an additional 99% more trips to recreational events
and 79% more trips for entertainment purposes. It could be argued that
these two activities are the most discretionary of the group, and, therefore,
the ones that are first eliminated because of any problems. Banking, religious,
shopping, and education trips were desired from 40% to 21% more than their actual
frequency. They only desired to make 6% more work trips, and none desired
to make more medical trips
Figure 4. 3
Additional Trips Desired and Estimated
After experiencing RIAS at the experiment site, subjects appear to have learned
much about what could be accomplished easily and safely using the additional
cues. Before trying the system, only 20 subjects (67%) thought they were
missing any trips, but after usage 29 (97%) thought they would make more trips.
The number of trips they said they would make with RIAS was much higher
than they had originally thought they were missing. Discretionary trips,
such as recreation and entertainment, were still the two highest in terms of
the increase, but at a much higher rate, 269% and 198% respectively. Estimated
education trips increased by 165%, banking trips by 110%, and work trips were
perceived as increasing by 100%. Next in decreasing order were shopping
(87%), social (73%), religious (45%), and medical trips up 27%.
This section examines how perceived trip behavior changed for individual subjects.
Of the 30 subjects, only one person, who already took 13.5 trips per week, reported
she would not make any more trips with RIAS. Five subjects said they
would make between 12% and 49% more weekly trips, and another five said they
would make between 50% and 99% more trips. Ten subjects said they would
make between 100% and 199% more trips, four more between 200% and 299%, two
between 300% and 399%, and two reported extra trips between 400% and 499%.
One person, who currently made only two trips a week, reported 12 extra trips
if using RIAS, for a 600% increase. Clearly there is a hidden demand
for more activities if travel and transit was made more accessible, a demand
for inclusion and participation that has not been previously understood.
Activity participation can also reveal the degree of access. Figure 4.4
shows the increased number of people who said they would attend to new activities
The data are again sorted from highest increase to lowest for those that
reported activities that they were denied because of transit and travel limitations
relating to their blindness.
Figure 4. 4 Additional Desired and
Estimated Subject Participation
For the desired trips not taken, recreation and education trips had the highest
demand by additional participants; a 111% and 63% increase, respectively, over
the actual number of current participants. Banking, entertainment, religious,
and social trips were estimated to increase, by 27% to 12%, for the number who
would participate. No one reported that they did not participate in work
strictly because of independent travel limitations. They also felt they
were able to meet their medical trip needs, and, since all subjects made current
shopping trips, there was no increased desire in that category. These
numbers seem to be in line with what one would expect. Except for the
first two discretionary activities, the estimate of foregone participation was
quite low or non-existent for critical functions like work and medical.
If all 30 subjects participated in each of the nine activities, the total number
of person-activities would be 270. The actual trip data showed 138 person-activities.
Subjects indicated that they currently wanted access to an additional 28 person-activities
for a total desired participation of 166 person-activities, an increase of current
unmet demand or desire of 20%.
The possibility of making new activities part of their everyday lives with RIAS
was quite evident in the number of people who said they would participate in
more and new activities. The total number of person-activities perceived
if using RIAS was 202, an increase of 64 from their current level of participation.
This is a hiddendemand or desire for 46% more subject-
participation in totally new activity types, after exposure to the experimental
test site with its auditory cues.
The “desired” data showed that recreation and education activities
had the highest percentage of increase of subjects wanting to participate.
The same pattern held true for the number of additional people who said they
would make those kinds of trips if RIAS was installed. Education was
said to attract 188% more people if they could use RIAS. The number of
people currently making education trips was eight, and five more thought they
were being denied those kinds of trips. But, after using RIAS, 15 additional
people stated a desire to attend educational activities. Clearly, this
group valued education, but problems of access kept the number of current participants
quite small. With RIAS, 178% more subjects desired participation in recreation
activities then their current level while 67% and 56% more people reported banking
and entertainment activities, respectively. The next two activities that
subjects said they would make were not even chosen in the “desired, but
denied” question. Originally, there were 17 people who made work
trips, and no additional people desired to make them. However, after
experiencing RIAS, an additional seven, or a 41% increase, said they would participate
in work activities and make those types of trips. In addition, six people
reported making current medical trips, and no one expressed that they postponed
these kinds of trips because of their inability to travel independently.
However, an additional two, or 33%, said they would make that kind of trip if
RIAS was installed. An additional 25% said they would attend religious
activities, and 8% more said they would make social trips. As everyone
already made shopping trips, there were no additional participants noted.
4.3.4. Summary of Current Activity Participation, Unmet and
Hidden Demand
This section has presented data showing travel times, trip frequency, and
activity participation. A summary of the basic findings for these blind
subjects shows:
Many subjects do not travel very much,
and their trips can be quite short. These people do not often leave home
to participate in activities, and their trips appear to be quite close to their
home, restricting their activities to familiar areas. They are denied access
to opportunities that are available to others in the same area.
For those who do venture out into the
wider environment, their trips are often quite long.
Activity participation was quite low for
many subjects. Three people left home only 2 times during a week, 30% of
subjects participated in one or less daily activity outside the home, and 73%
of all subjects made 2 or less activity trips per day.
67% of subjects reported that they were
denied some activities because of visual problems affecting independent travel.
They reported they would make 31% more
trips if they could travel independently.
After experiencing the additional environmental
cues of direction and identity that could be delivered through the use of RIAS,
subjects were able to more fully understand that they could gain more access to
urban opportunities.
They reported they would make 107% more
trips if RIAS was installed in their environment.
There was a reported 46% increase in the
number of new types of activities that subjects would participate in if RIAS was
installed.
None of the subjects originally thought
they did not have access to work because of their lack of independent travel.
However, after using RIAS, an additional 41% said they would make work
trips.
Subjects reported trip frequencies for
work trips would increase 100% if they could use RIAS.
Participation in educational activities
was desired, after using RIAS, by an additional 15 people over the current level
of 8, a 188% increase in the demand for education.
Estimated trip frequencies increased 165%
for education activities if RIAS was available.
Marston & Golledge (1998b) and Marston, et al. (1997) have suggested that
one cause of the dismal unemployment level for the severely vision-impaired, 70%,
(Kirchner et al., 1999) is the difficulties of independent travel. That
includes not just the daily job commute, but, perhaps more importantly, the ability
to execute a successful job search strategy when jobs are located in various and
scattered urban locations. As non-drivers, the available jobs or educational
opportunities for people who are blind that are located in familiar areas must
be much less than the aggregate available to the sighted public. That 41%
more people thought they would participate in work and 188% more thought they
would attend education facilities adds empirical evidence to their argument.
The data in this section about trip behavior indicate that blind people feel they
face barriers that limit activities and opportunities because of the lack of environmental
cues that restrict independent travel. They often are restricted to local
and familiar areas, and many appear to limit their trips and activities to needed
functions with a smaller participation in more discretionary activities.
Both the number of trips and the types of activities are restricted.
When the environment is made more accessible though the use of additional cues,
blind subjects perceived their lives as having many more types of activities and
a much higher participation rate in those activities. RIAS appears to reduce
the perceived limitation of independent travel by providing a much higher level
of accessibility to blind users.