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Revisiting Clear Floor Area Requirements for Wheeled Mobility
Device Users in Public Transportation
Aravind Bharathy
Inclusive Mobility Research Laboratory, Center for Ergonomics
School of Information
University of Michigan,
1205 Beal Ave, Ann Arbor, MI 48109-2117
Tel: 734-764-9965; Fax: 734-764-3451; Email: aravindb@umich.edu
Clive D’Souza, Corresponding Author
Inclusive Mobility Research Laboratory, Center for Ergonomics
Department of Industrial and Operations Engineering
University of Michigan,
1205 Beal Ave, Ann Arbor, MI 48109-2117
Tel: 734-763-0542; Fax: 734-764-3451; Email: crdsouza@umich.edu
Word count: 5993 words text + (3 tables + 3 figures) x 250 words (each) = 7493 words
TRR Paper number: 18-02377
Submission Date: March 13, 2018
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ABSTRACT
Current accessibility standards in the U.S. prescribe minimum dimensions for ‘clear floor area’
to accommodate wheeled mobility device (WhMD) users on transportation vehicles. Prior
research on the anthropometry of WhMD users (n = 500) indicates that these dimensions are too
small to accommodate the size of many occupied WhMDs, especially power chairs and scooters.
This paper describes a development project designed to update the evidence for these
technical criteria and communicate them to the vehicle designers and accessibility standards
developers in a manner that would facilitate making good decisions. An interactive web-based
design tool was developed for determining the dimensions of clear floor area to achieve a user-
specified level of physical accommodation based on occupied device length and width
measurements taken on 500 WhMD users. The web-based design tool is now available to
practitioners who seek to accommodate a wider range of WhMD users than the minimum
standards required by regulations.
The design tool is also intended as a visual evidence base for regulatory activity and
universal design practice with higher ambitions. The advent of driverless automated vehicles will
increase the importance of accessibility and usability to accommodate the diversity of riders with
disabilities. Clear floor space to enable independent ingress, interior circulation and egress
among WhMD users will be a foremost concern. The transportation industry, standards
developers, disability advocates, mobility device manufacturers and prescribers need to
understand the limitations of current accessibility standards and work to address these limitations
through updated vehicle design standards and policies.
Keywords: accessibility, wheeled mobility devices, anthropometry, low-floor bus,
accommodation model
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INTRODUCTION
Increases in life span, improved medical care, and increasing availability of assistive
technologies that promote independence have resulted in a growing need for accessible public
transportation that provides efficient and safe services for those with disabilities, including users
of wheeled mobility devices (WhMDs). The U.S. population of non-institutionalized (i.e., not in
nursing homes, hospitals) WhMD users is currently at 3.4 million (1) and continues to grow at an
annual rate of 5% (2). However, over 40% of WhMD users living in areas served by public
transit experience significant environmental and design barriers when using public transit
services (3). WhMD users present a unique set of challenges for physical accessibility in public
transportation because of concerns over large spatial requirements for floor area and
maneuvering (4, 5).
Currently, accessibility standards and codes are used throughout the U.S. and in other
countries to implement laws that mandate accessibility to transportation (e.g., buses, vans, trains,
etc.) and buildings (e.g., public restrooms, bus stops, transit facilities, etc.). The Americans with
Disabilities Act Accessibility Guidelines (ADAAG) for Transportation Vehicles (6) is the key
document used for the design of accessible facilities and transportation systems. A primary
feature of the ADAAG is the specification of a 'clear floor area' for wheelchairs, a space 760 mm
(30 in.) wide by 1220 mm (48 in.) in length. The 'clear floor area' is used to determine the size
of the area planned for wheelchair securement, the width of doorways and minimum interior
clearances for maneuvering a WhMD, and the space needed to accommodate people in WhMDs
in bus shelters, bus stop pads and in terminals - hence, a critical component for ensuring physical
accessibility.
The technical criteria in these standards are based on body sizes and functional abilities
(i.e., anthropometry) of adults and sometimes children with disabilities. To understand the spatial
implications of contemporary wheeled mobility technology and user populations, the second
author (CD) collaborated with researchers at the IDeA Center at the University at Buffalo to
develop an extensive anthropometry database of WhMDs in the U.S. with the intention of
improving accessibility to buildings, facilities, and public transportation vehicles (7, 8). A key
finding from an early analysis on the anthropometry of 369 WhMD users indicated that the
minimum clear floor area dimensions for transit buses are too small to accommodate the size of
many occupied WhMDs, especially power chairs and scooters (9). Key reasons for this
disaccommodation are worth revisiting. Foremost was the realization that research conducted in
the 1970's was the basis for the current criteria for accommodating WhMD users (10). Since that
time, the sizes and characteristics of WhMDs and their users have changed considerably. By the
late 1990's, anecdotal evidence was emerging that the standards were no longer adequate.
Today, the range of WhMDs available is much more diverse. The size, weight and
maneuvering characteristics of WhMDs vary considerably between device type (e.g., manual
wheelchairs, powered wheelchairs and electric scooters), make, and model (7-9, 11). Both
manual and powered wheelchairs offer some customizability to fit user needs in postural support,
comfort, and ease of use (e.g., leg rests and footrests, tilt and recline) which also impacts space
requirements. The growing availability and use of scooters and power chairs are expected to
further change the mobility device user demographics in the coming years (2). Power chairs have
allowed people with more severe disabilities to become mobile in the community. The choice of
drive configuration (i.e., front, mid, and rear-wheel-drive) and powered seating options influence
maneuverability of powered wheelchairs (12). People are larger due to the obesity epidemic
resulting in a growth in bariatric wheelchairs.
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Increasing use of scooters among the growing older adult population has put greater
emphasis on scooter access in public transit systems. Scooters typically have a larger turning
radius and are less maneuverable than wheelchairs because their configuration and chassis length
need to accommodate the drive controls (e.g., tiller) and foot placement (12-14). These devices
tend to be designed and prescribed for outdoor use. They are intended to assist individuals with
limited ambulation and good trunk control and sufficient upper extremity function to control the
steering tiller, but who also lack the upper extremity stamina or range of motion necessary to use
a manual wheelchair. These problems are not unique to the U.S. Research studies from the U.K.
suggest similar concerns regarding increased WhMD sizes and challenges to accommodation on
public transit vehicles (7, 15, 16).
Over time, the emphasis of our research effort evolved to creating data-driven graphical
design tools to provide an evidence base to evaluate existing accessibility standards and to
support designers and standards developers who seek to accommodate a wider range of WhMD
users than the minimum standards required by regulations (17, 18). Facilitating this outcome was
the production of statistical analyses and visualizations with results in a graphical format (e.g.,
the percentage of WhMD users that could fit, turn, reach, see, in specific conditions). In
particular, multivariate accommodation models were very effective for communication and
standards development activities by providing a sophisticated way to visualize the impact of
revisions to accessibility standards as "what if" analyses (17, 18). This shift was informed by
lessons learned from our engagement with the design and accessibility standards community (18)
that:
Research results are best presented to decision makers in a form that is familiar to them,
in this case, two-dimensional illustrations that resemble or can be overlaid with
illustrations used in the existing standard, and,
Graphic presentations that illustrate the impact of alternative decisions, like interactive
accommodation models, can greatly facilitate the adoption of findings.
Study Objectives
The objectives of this study were to:
1. Develop a data-driven algorithm for determining the dimensions of clear floor area to
achieve a user-specified level of physical accommodation based on occupied device
length and width measurements taken on 500 WhMD users,
2. Implement the algorithm as a web-based accommodation model with a graphical and
interactive user interface to support standards development, regulatory action, and design,
3. Evaluate existing clear floor area requirements prescribed in the ADAAG using the
developed accommodation model and where necessary generate recommendations for
improving the minimum clear floor area requirements.
Implications of these findings are discussed.
METHODS
The analysis described in this study used anthropometry measurements previously taken on 500
adults in the U.S. who relied solely on WhMDs for mobility (8). WhMD users were recruited
through many sources, including a local independent living center, a United Cerebral Palsy
Association, a geriatric day care center, and local hospitals, including Veterans Affairs Medical
Centers in Buffalo and Pittsburgh. In addition, advertisements were posted in local newspapers
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and flyers placed in local organizations and stores. The university’s institutional review board
approved the study and all participants provided written informed consent.
The research team made a deliberate attempt to recruit a diverse group of users, rather
than just individuals who possessed a specific set of physical capabilities so that the results
obtained could be extended to the broader WhMD user population in the US. The measurement
protocol included the collection of demographic information, mobility device specifications,
structural anthropometric measurements and functional anthropometric information from each
participant (8).
A three-dimensional digitizing technique was developed to collect detailed data on static
anthropometric variables (19, 20). A set of over 130 standardized three-dimensional data points
for each person and device were collected that could describe the three-dimensional volume of
the occupant and device, while occupants held a comfortable or typical seated posture. Three-
dimensional coordinates of the landmarks were then used to derive estimates of widths, heights,
and depths of mobility device characteristics and body dimensions relevant to built environment
design. The current study used three computed dimensions:
1. Occupied length: computed as the horizontal distance from the extreme rear-most and
forward-most point of the combined occupant or mobility device.
2. Occupied width: computed as the horizontal distance between the extreme lateral right-
most and left-most points on the body or mobility device with the participant seated in a
comfortable, relaxed posture.
3. Occupied floor area: defined as the estimated rectangular floor space required for each
occupant-mobility device in the study sample and computed as a product of the occupied
length and occupied width.
WEB DATABASE AND USER INTERFACE
This development project advances our anthropometry research by implementing a new web-
based framework to support multivariate analysis of specific aspects of WhMD user interaction
with the built environment (e.g., clearance, approach, reach capability, line of sight, and turning
space requirements). This framework consists of an interconnected, hierarchical set of modules
(using open source scripting languages PHP and JavaScript) to query the underlying
anthropometry of wheeled mobility database implemented in MySQL and to perform
multivariate anthropometry analyses. A visual interface was developed using D3.js, which is a
JavaScript library for producing dynamic, interactive data visualizations in web browsers by
combining SVG for graphics, HTML5 for content, CSS (Cascading Style Sheets) for aesthetics,
PHP for data retrieval, and Javascript for data manipulation.
Displaying Clear Floor Area
The visual interface allows users to retrieve and display information on occupied width and
occupied length as individual datapoints on a two-dimensional scatter-plot (Figure 1). A scatter-
plot is very useful for depicting the association between two variables, i.e., occupied length and
width in our case. Data can be displayed for all 500 WhMD users in the study sample or
stratified by a defined sub-group (e.g., type of WhMD, sex, age range, etc.).
To provide context to designers and standards developers, a plan view of a WhMD user
and ADAAG minimum requirement for clear floor area (6) is superimposed on the display
(Figure 1). Datapoints enclosed by the ADAAG required minimum clear floor area (Quadrant 1)
represent individuals accommodated, while datapoints outside represent individuals excluded
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either due to inadequate clear floor length (Quadrant 2), width (Quadrant 3), or both length and
width (Quadrant 4).
Accommodation Model for Clear Floor Area
An accommodation model was developed for determining the minimum dimensions of clear
floor area to achieve a user-specified level of physical accommodation based on occupied device
length and width measurements taken on 500 WhMD users. In the interactive web-based display
two modes for conducting “what if” analyses are implemented. First, end-users can drag the
boundary of the clear floor area (dotted lines in Figure 1) to increase/decrease the clear floor area
with the interface display updating in near-realtime to communicate the proportion of the sample
accommodated (i.e., number of datapoints in Quadrant 1 divided by the total number of datpoints
for that group of users). Alternately, the end-user can specify on a slider-bar the percentile of
users to be accommodated and the boundary of the clear floor area on the 2-D display updates in
near-realtime to depict the corresponding minimum required clear floor area length and width.
The latter percentile analyses occupied floor area provides a more useful starting point
for determining suitable dimensions for ‘clear floor area’. In contrast to our previous report (9),
this study presents a more refined method for computing the minimum required clear floor area
length and width to accommodate the desired percentile of WhMD users. The need for this stems
from the fact that the Pearson’s correlation coefficients between occupied width and occupied
length were weak, i.e., 0.21 for manual chairs, 0.30 for power chairs, and 0.50 for scooters,
suggesting that neither occupied width or occupied length can necessarily be used to reliably
predict the other. It also implies that the specific combination of clear floor area length and width
to accommodate the desired percentile is not trivial.
Procedure for Calculating Minimum Clear Floor Space Requirements by Percentile
Summarized below is the procedure developed for calculating by WhMD type the minimum
clear floor area length and width to accommodate a user-specified percentile accommodated
(Figure 2):
1. For a given percentile of accommodation, say 5%, the WhMD users in the study sample
whose corresponding occupied length and occupied width accommodate 5% ± 2% of
users in the sample are identified. We opted for a tolerance range of ± 2% due to the
relatively small sample sizes, particularly for scooter users. This step produces multiple
possible lengths and widths for a given value of percentile accommodation.
2. Next, we determine the specific combination of length and width that would produce the
smallest clear floor area from these identified points. This is done by fitting or
approximating a quadratic curve to the identified data points (i.e., a yellow curve at 5% in
figure 2). Any point on this curve would accommodate 5% of users; some combinations
with large occupied widths, some with large occupied lengths, while others in-between.
A quadratic curve was chosen due to low mean squared error values compared to a linear
fit and other higher-order polynomial fit. The equation for a quadratic curve takes the
following general form,
(1)
3. The clear floor area, A, obtained by any point on the curve can be represented as,
(2)
where
x = occupied length
y = occupied width.
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Substituting for ‘y’ from Eq. (1),
(3)
The point (xmin, ymin) on this quadratic curve that would yield the smallest clear floor area
can be obtained by computing the solution to the first derivative, namely,
= 0 (4)
(5)
4. The solution to this equation is:
(6)
Substituting for x in Eq. (1), we obtain:
(7)
5. Steps 1 to 4 are repeated for all percentiles from 5% to 95% in increments of 1%. Figure
2 shows the corresponding quadratic curves in increments of 5%.
6. Next, a quadratic curve is fit through all the pairs of minimum occupied length and
occupied width obtained from each percentile value. Again, a quadratic curve is chosen
due to low mean squared error. Each point on this curve provides a clear floor area with a
corresponding length and width, and this area will be close to the minimum for a given
accommodation value. This is depicted in Figure 2 by a solid-black curve passing through
the different percentile-based combinations of points (xmin, ymin). The curve shows the
trajectory by which the occupied length and width should change to increase/decrease
accommodation. Clearly, this trajectory is non-linear, i.e., occupied length and width do
not change proportionately. Separate trajectories were produced for each type of WhMD.
DATA ANALYSIS
Three types of analyses were performed stratified by the type of WhMD:
1. Descriptive analyses to evaluate the distributional characteristics of occupied length,
width, and area. The mean, standard deviation, range, 5th and 95th percentile values for
occupied length, width, and area were calculated using SPSS Statistics v23.0 (21).
2. Occupied lengths and widths in the sample were compared to the ADAAG minimum
requirement for clear floor area to determine the proportion of the sample accommodated
and disaccommodated.
3. Using the graphical accommodation model described in the previous section, the
minimum required clear floor area lengths and widths for commonly used percentiles
accommodated were computed and summarized in a graphical and tabular format for use
by accessibility designers and standards developers.
RESULTS
Sample Demographics
The study sample consisted of 264 (52.8%) men and 236 (47.2%) women. Among men, 147
(55.7%) used a manual wheelchair, 100 (37.9%) used power chairs, and 17 (6.4%) used scooters.
Among women, 130 (55.1%) used a manual chair, 89 (33.7%) used a power chair, and 17 (7.2%)
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used a scooter. The mean (standard deviation) age of the sample was 56.4 (18.8) year with a
range of 18 to 100 years.
Regarding self-reported medical conditions that led to dependence on mobility devices,
CNS disorders (e.g. multiple sclerosis, cerebral palsy, etc.) were the most frequently occurring
(34%), followed by spinal cord injuries (26%), orthopedic injuries/deformities (13%) and
cerebral vascular diseases such as stroke (10%). Instances of medical conditions such as
amputations (3%), traumatic brain injuries (2%), or respiratory and cardiovascular diseases (2%),
were less frequent, with the remaining cases listed under ‘Other’ (10%).
Univariate analysis of occupied width, occupied length and occupied floor area
Descriptive statistics for occupied width, occupied length, and occupied floor area stratified by
mobility device type are tabulated (Table 1).
Comparisons with the ADAAG Minimum Clear Floor Space Requirement
Table 2 provides the frequency count and percentages in parentheses (percentages are computed
based on the corresponding mobility device category) for cases in each of the four quadrants
depicted in Figure 1. Only 59.4% of combined mobility device users in the sample were
accommodated in the ADAAG minimum clear floor space requirement (Quadrant 1).
Comparisons of occupied length and occupied width of WhMD users in the study sample with
the ADAAG prescribed minimum clear floor length (1220 mm) and minimum clear floor width
(760 mm) showed that a larger percentage of users exceeded on occupied length (Quadrant 2) as
compared to occupied width (Quadrant 3) or both, occupied length and width (Quadrant 4).
Percentile-based Accommodation Model for Clear Floor Area Length and Width
Figure 3 shows the quadratic fit for the data points at which least area for a given percentile was
observed. The coefficient of determination (r2) or the fit of the quadratic curve was determined to
be 0.86 for all mobility devices combined, 0.89 for manual chairs and 0.80 for power chairs.
Scooters had a very low r2 value due to insufficient data points that result from the small number
of scooter users in the sample. Table 3 gives the same values by device type.
DISCUSSION
Contemporary wheeled mobility technology can support greater independence, better utilization
of public transportation and increased social participation of individuals with disabilities into
mainstream society (e.g., employment, shopping/doctor visits, recreational travel). However, the
full potential of this technology cannot be realized unless device size and shape, and the size of
occupants are accommodated by transportation systems to insure access to safe, comfortable and
timely travel.
Implications for Accessibility Design Standards and Policies
Standards serve as the foundation for the evidence-based design of the built environment because
architects, engineers, product designers, and other design professionals rely on experts in
accessibility, safety, and public health to translate knowledge into guidelines for practice. Like
product development, standards development is a long-term, expensive, and time-consuming
activity. It requires the creation of supporting evidence and translation of that evidence into
realistic standards.
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The findings of this research provide a guide to policy-makers and accessibility
standards developers for evaluating and revising current transportation accessibility standards.
The results suggest that the current standards are not adequate to accommodate a large
proportion of contemporary WhMD users. Three design strategies could address this finding in
practice. The standards for minimum clear floor area could be increased. This would have
limited, if any, implications for new construction in the built environment but could have major
implications for the design of some vehicle types, especially low floor buses where the space
between wheel wells is very limited. The use of a four-passenger longitudinal flip-up seat in
place of a three-passenger longitudinal flip-up seat in one wheelchair securement area would
provide enough space for larger scooters and wheelchairs, reducing overall seating capacity by
only one person. Finally, the location of boarding ramps at entries in the middle of low floor
vehicles instead of front door access could increase the maneuvering space available by avoiding
the need for passage between wheel wells. This last strategy would require using a curbside fare
collection or an alternate method that does not require face to face driver interaction or
supervision. It also may have, at present, a limited application to boarding from raised platforms
because in most low floor buses, the kneeling feature, which enables a lower ramp slope, is only
installed on the front of the bus. These strategies above are not mutually exclusive. Together,
they provide policymakers with some options that could lead to a reasonable solution with
minimum cost and operational impact. The alternative is to enact operating policies that restrict
access on mass transport vehicles to devices that have footprints that fall within specified limits,
but such policies based on size could be considered discriminatory and require drivers to make
difficult judgments in the field.
Implications for Accessible Design of Transportation Vehicles
Small increases to the minimum securement area to better accommodate contemporary
WhMDs on occupied length and width also lead to reduced entry and positioning times and
difficulty, depending on the specific bus design without affecting seating capacity (22, 23).
However, a space increase in existing public transit environments may be prevented by
technological constraints.
The results presented here also help to identify design goals for future transportation and
wheeled mobility technology. For example, the data provide a goal for the design of new
suspension systems for low floor buses that could increase the available space between wheel-
wells, for new securement systems that might allow additional available room in the securement
area or alternative vehicle interior layouts that offer better access and circulation spaces. Also
important are innovations in mobility device design that improve device maneuverability making
them more adaptable to constrained environments such as on buses, or technologies that increase
the comfort and postural support for the occupant while possibly reducing the occupied floor
area. Designing the interior of buses and other transit vehicles for accessibility is a multi-
dimensional design problem. Multiple adjacent design features in addition to the size of the
securement area such as its location in relation to the front or rear-doorway, forward vs. rear-
facing orientation) and seat layout and orientation (transverse vs. longitudinal) influence an
individual WhMD users’ ability to enter, situate in and exit the securement area in an efficient
manner. In some instances, it can require simultaneous consideration for additional variables
such as shoulder widths and heights, knee and toe clearance widths and heights and functional
reach capability to name a few. Future research activities will explore the development of
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multivariate analyses tools that can factor in additional variables besides width and length of the
occupant and device. Additionally, in laboratory experiments using a full-scale mock-up of a
bus with reconfigurable interiors we demonstrated quantifiable relationships between occupied
device dimensions and actual performance in dynamic activities such as boarding, interior
circulation and disembarking (22, 23, 24).
The aging of the population, rising social expectations of accessible mobility options, and
the increased cost of vehicle ownership will lead increased utilization and demand for inclusive,
reliable transportation systems. The advent of automated vehicles will present opportunities for
reducing mobility barriers for individuals with disabilities. But little attention is being given to
the design of these vehicles to serve the disability community. The lack of drivers will also
introduce new problems. On the one hand, the design of automated vehicles will necessitate a
higher standard of usability to ensure independent use without driver assistance. On the other
hand, such vehicles will have more space due to the removal of obsolete components such as
driver stations and fare machines. The new mobility industry and technology developers have yet
to embrace the need and value of designing these vehicles to be accessible and inclusive.
Standards developers, disability advocates, mobility device manufacturers and prescribers need
to understand the limitations of current accessibility standards and work to address these
limitations through updated vehicle design standards and policies. As demonstrated in the case
example of clear floor area, human factors and ergonomics research can improve our knowledge
of how best to accommodate the diverse population of passengers.
Methodological Limitations
The proportion of wheelchair users mentioned above might not represent the same proportion
expected in adult U.S. population of wheelchair users. For example, the adult U.S. population of
WhMD users comprises an estimated 84% manual chair users, 8% power chair users, and about
8% scooter users in (2, 3). The current study sample had a much larger proportion of power
wheelchair users and more severe physical limitations compared to the U.S. population.
However, power chair users were intentionally oversampled to obtain a better understanding of
the functional abilities of this user group, which typically has more severe physical limitations
and is hence more sensitive to design restrictions.
Measurements in this study were taken with participants seated in a comfortable posture
that they could maintain for the duration of the measurement process, typically lasting 15-20
minutes. Participants often chose to rest their arms on the armrest and/or extend the footrests and
legrests to support the lower extremities. This data does not take into account the ability of some
individuals to move their limbs inboard of their devices, swing legrests and footrests out of the
way, or adjust back-packs and bags which may extend beyond the boundaries of their devices. It
is also worth noting, however, that traveling on public transportation is an activity that requires
remaining relatively stationary for extended periods of time. While these measurement
conditions and postures may tend to overestimate the occupied width and occupied length
dimensions for very short time durations, they do reflect postures that WhMD users consider
comfortable for times that are commensurate with the vast majority of transit trips. Further, the
samples were drawn largely from cold weather cities which may introduce some bias toward
larger and more durable equipment, but data was collected all year round in an attempt to
minimize any bias in recruitment associated with the seasons.
The analyses presented in this paper are based on the assumptions of a rectangular area
required for static positioning of a WhMD. The findings suggest that the current minimum
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requirements of a 760 mm (30 in.) wide by 1220 mm (48 in.) length of ‘clear floor area’ are
clearly inadequate for a sizeable proportion of WhMD users measured in this study, especially
those with the most serious disabilities, namely, power chair users. Wheeled mobility
anthropometry dimensions from this study have also been compared with existing accessibility
standards and anthropometry research findings from other countries such as Australia, Canada,
and U.K. (7). These international comparisons also suggest a trend toward an increase in
occupied floor area among mobility devices, and the inability of accessibility standards to reflect
the space requirements of WhMD users in the built environment. One approach to increasing the
level of accommodation would be to provide a larger clear floor area than the existing
standards. The findings described here are intended to provide guidance for modifying
standards, particularly in applications where the amount of space available in some vehicles is
very limited. A large number of individuals in the study were excluded by the minimum clear
floor area requirements due to larger occupied lengths (Quadrant 2 in Figure 1), suggesting that
the greatest improvements in accommodation could be first achieved by increasing the length
dimension of the ‘clear floor area’. It is worth noting that based on our research findings and
other considerations from stakeholders, the ICC/ANSI A117.1 Committee, which publishes a
voluntary building standard for accessibility has revised its minimum requirements for clear floor
area length in all new construction, increasing it from 1220 mm (48 in.) to 1320 mm (52 in.) (18,
25). Also, space requirements for maneuvering into and out of these spaces inside vehicle were
not considered in the current analysis and might suggest the need for additional clearances (22).
CONCLUSION
This report describes a data-driven graphical and interactive accommodation model that can be
used by architects and designers to visualize and understand the impact of physical design
features on accommodation levels. The accommodation model presented here shows the
importance of linking occupied width and length of WhMDs when establishing suitable
dimensions for minimum ‘clear floor area’ in accessibility standards, including those used in the
transportation sector. The findings from the analysis of clear floor area need to be the subject of
considerable dialogue in the transportation community to determine what level of
accommodation is realistic and practical with regard to contemporary vehicle
technology. Involving WhMD manufacturers, mobility device vendors, rehabilitation engineers
and therapists, and representatives from transit agencies and organizations serving individuals
with disabilities in this dialogue is also very critical to arriving at acceptable and easily
implementable solutions. For now, given prevailing standards provisions, rehabilitation
engineers and therapists prescribing wheelchairs need to consider the transportation needs of
clients and the occupied device size relative to the space available for wheelchair circulation and
securement areas on contemporary public transportation vehicles.
The report also demonstrates the utility of the assembled anthropometry database in
helping standards developers and designers improve accessibility, independent mobility, and
safety for travelers using WhMDs on buses, other public transportation vehicles and potentially
future autonomous driverless vehicles. The web-based implementation provides the accessible
design and standards community worldwide with the capability to query our anthropometry
database and perform multivariate analyses without requiring users to have programming or
statistical expertise. Usability testing of the website and implementation of other such
multivariate accommodation models is ongoing. The accommodation model can be accessed via
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the website for the University of Michigan’s Inclusive Mobility Research Laboratory at
http://dsouzalab.engin.umich.edu/research/anthro/index.php.
ACKNOWLEDGMENTS
The contents of this manuscript were developed under a grant from the National Institute on
Disability, Independent Living, and Rehabilitation Research (NIDILRR) through the
Rehabilitation Engineering Research Center on Universal Design at Buffalo (RERC-UD; Grant #
90RE5022-01-00). Research underlying the anthropometry database on WhMD users presented
in this paper was supported under a grant from NIDILRR through the RERC-UD (Grant #
H133E990005) and from the U.S. Access Board (contract # TDP-02-C-0033). NIDILRR is a
Center within the Administration for Community Living (ACL), Department of Health and
Human Services (HHS). The contents of this manuscript do not necessarily represent the policy
of NIDILRR, ACL, HHS, U.S. Access Board, and you should not assume endorsement by the
Federal Government.
The authors thank the principal investigators of the RERC-UD and the Anthropometry of
Wheeled Mobility project, Drs. Edward Steinfeld, Victor Paquet, and James Lenker at the IDeA
Center, University at Buffalo for anticipating the need and initiating this important research
effort more than a decade ago.
AUTHOR CONTRIBUTION STATEMENT
The authors confirm contribution to the paper as follows: study conception and design: CD;
analysis and interpretation of results: CD, AB; draft manuscript preparation: AB, CD. All authors
reviewed the results and approved the final version of the manuscript.
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Bharathy, D’Souza 15
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LIST OF TABLES
TABLE 1 Summary Statistics For Occupied Width (mm), Occupied Length (mm) And
Occupied Area (m2) Statrified By Type Of Wheeled Mobility Device
TABLE 2 Percentage Of Wheeled Mobilty Device Users in the Study Sample (n = 500)
With Lengths And Widths That Are Accommodated (Quadrant 1) Or Excluded
(Quadrants 2, 3, 4) Compared to the ADAAG Required Minimum Clear Floor Area Of
Size 760 mm X 1220 mm
TABLE 3 Percentile Accommodated and the Corresponding Estimated Minimum Clear
Floor Area Length and Width Stratified by Mobility Device Type
LIST OF FIGURES
FIGURE 1 Scatter-plot of occupied length vs. occupied width, overlaid with the ADAAG
Sec. 305.5 requirement for minimum ‘clear floor area’ of size 760 mm x 1220 mm (30 in. x
48 in.).
FIGURE 2 Quadratic fit for least areas by percentile for manual wheelchair users,
overlaid with the ADAAG Sec. 305.5 requirement for minimum ‘clear floor area’ of size
760 mm x 1220 mm.
FIGURE 3 Accommodation model for Clear Floor Area by Type of Wheeled Mobility
Device. Close-up view on the right.
Bharathy, D’Souza 16
Pre-print version – internal use only
TABLE 1 Summary Statistics For Occupied Width (mm), Occupied Length (mm) And
Occupied Area (m2) Statrified By Type Of Wheeled Mobility Device
Manual chairs (n = 277)
Dimension
Mean
SD
Min
Max
Percentile
5th
50th
95th
Occupied Width (mm)
685.0
61.4
508.0
992.0
595.7
677.3
786.4
Occupied Length (mm)
1150.5
129.8
743.0
1625.0
934.7
1154.8
1362.0
Occupied Area (m2)
0.79
0.125
0.44
1.25
0.60
0.78
1.00
Power chairs (n = 189)
Dimension
Mean
SD
Min
Max
Percentile
5th
50th
95th
Occupied Width (mm)
706.7
72.4
574.0
1008.0
606.9
695.3
827.5
Occupied Length (mm)
1196.3
133.7
831.0
1709.0
977.0
1183.4
1414.5
Occupied Area (m2)
0.85
0.145
0.50
1.27
0.63
0.84
1.11
Scooters (n = 34)
Dimension
Mean
SD
Min
Max
Percentile
5th
50th
95th
Occupied Width (mm)
650.0
89.6
488.0
857.0
526.7
617.3
829.3
Occupied Length (mm)
1208.5
110.0
1025.0
1439.0
1039.3
1202.8
1433.1
Occupied Area (m2)
0.79
0.158
0.50
1.17
0.55
0.77
1.12
Bharathy, D’Souza 17
Pre-print version – internal use only
TABLE 2 Percentage Of Wheeled Mobilty Device Users in the Study Sample (n = 500)
With Lengths And Widths That Are Accommodated (Quadrant 1) Or Excluded
(Quadrants 2, 3, 4) Compared to the ADAAG Required Minimum Clear Floor Area Of
Size 760 mm X 1220 mm
Mobility
Device
Type
Quadrant
Total
Q1
(Included)
L<1220 &
W<760
Q2
(Exceed length)
L>=1220 &
W<760
Q3
(Exceed width)
L<1220 &
W>=760
Q4 (Exceed
length & width)
L>=1220 &
W>=760
Manual
185 (66.8%)
65 (23.5%)
15 (5.4%)
12 (4.3%)
277 (100%)
Power
94 (49.7%)
55 (29.1%)
16 (8.5%)
24 (12.7%)
189 (100%)
Scooter
18 (52.9%)
12 (35.3%)
1 (2.9%)
3 (8.8%)
34 (100%)
Combined
297 (59.4%)
132 (26.4%)
32 (6.4%)
39 (7.8%)
500 (100%)
Bharathy, D’Souza 18
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TABLE 3 Percentile Accommodated and the Corresponding Estimated Minimum Clear
Floor Area Length and Width Stratified by Mobility Device Type
Dimension
Percentile Accommodated for Users of Manual Wheelchairs (n = 277)
5%
15%
25%
35%
45%
55%
65%
75%
85%
95%
Length(mm)
1008
1111
1163
1195
1230
1255
1295
1319
1352
1449
Width (mm)
658
660
670
679
692
702
721
734
754
828
Area (m2)
0.66
0.73
0.78
0.81
0.85
0.88
0.93
0.97
1.02
1.20
Dimension
Percentile Accommodated for Users of Power Chairs (n = 189)
5%
15%
25%
35%
45%
55%
65%
75%
85%
95%
Length (mm)
1076
1168
1204
1244
1267
1320
1338
1355 *
1372
1508 *
Width (mm)
616
652
669
689
702
732
744
755 *
766
870 *
Area (m2)
0.66
0.76
0.80
0.86
0.89
0.97
0.99
1.02
1.05
1.31
Dimension
Percentile Accommodated for Users of Scooters (n = 34)
5%
15%
25%
35%
45%
55%
65%
75%
85%
95%
Length (mm)
1148
1161
1246
1252
1253
1291
1310
1327 *
1343
1360 *
Width (mm)
549
548
609
617
619
687
729
785 *
817
860 *
Area (m2)
0.63
0.64
0.76
0.77
0.77
0.89
0.95
1.04
1.10
1.17
* Indicates values that were interpolated (if in between) or extrapolated (if at the end) from the best-fit quadratic
curve due to few observations at those percentiles.
Bharathy, D’Souza 19
Pre-print version – internal use only
FIGURE 1 Scatter-plot of occupied length vs. occupied width, overlaid with the ADAAG
Sec. 305.5 requirement for minimum ‘clear floor area’ of size 760 mm x 1220 mm (30 in. x
48 in.).
Bharathy, D’Souza 20
Pre-print version – internal use only
FIGURE 2 Quadratic fit for least areas by percentile for manual wheelchair users,
overlaid with the ADAAG Sec. 305.5 requirement for minimum ‘clear floor area’ of size
760 mm x 1220 mm.
Bharathy, D’Souza 21
Pre-print version – internal use only
FIGURE 3 Accommodation model for Clear Floor Area by Type of Wheeled Mobility
Device. Close-up view on the right.
