Assessing the Validity of Kinematically Generated Reach
Envelopes for Simulations of Vehicle Operators
Matthew P. Reed, Matthew B. Parkinson, and Amy L. Klinkenberger
University of Michigan
This paper was originally prepared for the SAE Digital Human Modeling Conference. It appears is in SAE Transactions as Technical Paper 2003-01-
2216 and was selected from 2,492 papers to receive SAE’s Colwell Merit Award for best paper in 2003.
Copyright © 2003 Society of Automotive Engineers, Inc.
Assessments of reach capability using human figure
models are commonly performed by exercising each
joint of a kinematic chain, terminating in the hand,
through the associated ranges of motion. The result is a
reach envelope determined entirely by the segment
lengths, joint degrees of freedom, and joint ranges of
motion. In this paper, the validity of this approach is
assessed by comparing the reach envelopes obtained
by this method to those obtained in a laboratory study of
men and women. Figures were created in the Jack
human modeling software to represent the kinematic
linkages of participants in the laboratory study.
Maximum reach was predicted using the software’s
kinematic reach-envelope generation methods and by
interactive manipulation. Predictions were compared to
maximum reach envelopes obtained experimentally.
The findings indicate that several changes to the normal
procedures for obtaining maximum reach envelopes for
seated tasks are needed. Accurate prediction of
maximum seated reach requires consideration of
balance and pelvis mobility, neither of which is closely
linked to joint range of motion. Sufficient ranges of
motion in the shoulder and torso are also needed to
represent postures near maximum reach.
Maximum reach capability is an important consideration
in the design of seated workstations. For most of the
history of human-factors engineering, operator reach
capability has been represented using graphical
representations of statistical models based on laboratory
measurements. In one widely cited study, Kennedy
(1964) presented the results of a study of the maximum
reach capability of U.S. Air Force pilots wearing belt
restraints on the torso. The data were presented as
planar curves positioned relative to the seating reference
point within which 95 percent of the tested subjects
could reach. SAE Recommended Practice J287
presents three-dimensional surfaces within which 95
percent of drivers are predicted to be able to reach.
These surfaces are based on a study of drivers seated in
three different vehicle mockups (Hammond and Roe,
1972). SAE J287 is widely used in the design of
passenger cars and light trucks.
During the past decade, software models of the human
body have become increasingly important for vehicle
interior design. Human modeling tools, such as
RAMSIS, Jack, and SafeWork, are used to simulate the
interaction of humans and vehicle interiors. The
software tools provide the human factors engineer with
the ability to simulate a vehicle occupant reaching to
controls or other targets by articulating the joints of a
virtual human. For many vehicle interior analyses, these
simulations, based on the kinematics and posture of a
human figure model, are used instead of statistical reach
In typical application, the range within which an occupant
can reach (reach envelope) is obtained by iterating each
joint of the upper extremity, from the sternoclavicular
joint to the wrist, through its range of motion. Analytical
methods have also been developed to calculate the
surfaces defining the reach envelope (Abdel-Malek et al.
2001). Previous studies have examined the validity of
reach simulations for pilots with fixed-length torso
restraints (e.g., Green and Hilby 1999).
However, belt restraints in modern road vehicles are
commonly equipped with emergency locking retractors
(ELR). An ELR allows the belt to spool under light
tension until the vehicle undergoes a level of
acceleration that might be associated with a crash. With
this type of belt system, the belt does not substantially
restrain the occupant’s torso during normal reaching
activities. Hence, a vehicle occupant’s reach envelope
is determined by torso mobility in addition to upper
extremity dimensions and range of motion.
In the current study, maximum reach envelopes from a
pilot study of seated reaches were used to assess the
validity of kinematically generated reach assessments in
the Jack human figure model. Because preliminary
results showed large discrepancies between the reach
envelopes obtained in Jack and those observed with the
experiment participants, this paper uses a qualitative
evaluation of terminal postures from near-maximal
reaches to recommend improvements to human-
modeling procedures for estimating seated reach
Data for maximal and submaximal seated reaches were
obtained from a study conducted at the University of
Michigan’s Human Motion Simulation (HUMOSIM)
laboratory. Details of the experimental methods are
found in Reed et al. (2003). Testing was conducted
using mockups of heavy truck, passenger car, and
industrial workspaces. Figure 1 shows a participant
completing a reach in the heavy truck mockup. A
computer-controlled target positioning apparatus was
used to place a push-button target at a wide range of
locations within the participant’s right-hand reach
envelope. The participant reached to the target, pressed
the button for two seconds, and returned to a home
position. Optical targets and electromagnetic sensors
were attached to landmarks on the participant to track
the motion using methods reported previously (Park et
al. 1999, Chaffin et al. 1999)
Figure 1. Laboratory setup, showing the optical and electromagnetic
markers used to track motions and the computer-controlled target-
The kinematic data were analyzed to compute joint
locations that produce a representation of the
participant’s body as a kinematic linkage. These data
were used in the Jack human modeling software to scale
figures to match the participants’ linkage dimensions.
The terminal postures from selected maximal reaches
were mapped onto the Jack figures to compare with
those produced by interactive manipulation.
Maximum reach envelopes were obtained from the
laboratory data by a process described in Reed et al.
(2003). The participant rated the difficulty of each of
over 200 reach trials to targets distributed throughout
and just beyond the right-hand reach envelope.
Participants rated maximal attainable reaches as 10 on a
10-point scale. Unattainable reaches were coded as 11.
Maximum reach envelopes were calculated from these
data by interpolating to find locations for which the
difficulty rating was predicted to be 10.5 and fitting
smooth functions in spherical coordinates. These
empirically derived maximum reach envelopes were
compared to those obtained by kinematic manipulation
of the Jack figures that had previously been scaled to
match the participant’s body linkages.
Figure 2 shows a Jack figure scaled to match the
measured kinematic linkage for one study participant.
Three reach envelopes are shown. The innermost
envelope was generated in Jack by tracing the right
fingertip location as the right upper extremity was
manipulated, starting at the right sternoclavicular joint.
The middle envelope was created similarly, but with the
mobility beginning at the L5/S1 joint. The outermost
envelope is the maximum reach envelope obtained in
testing with this participant. The focus of the current
analysis is on the sources of the discrepancies between
these three envelopes.
Note that to simplify the graphical presentation of the
reach envelopes, restrictions due to self-collision and
interference with the environment (for example,
restrictions on forward reach due to the steering wheel)
are not included. The analysis focuses on upward and
lateral reaches in a coronal plane, for which these
restrictions are not important.
The two kinematically generated reach envelopes are
similar for reaches up and to the right, because torso
mobility does not add much reach distance in that
direction. The effect of torso mobility is largest for
reaches to the side. Figure 3 shows a posture with the
figure reaching to the right with torso mobility down to
L5/S1 included, illustrating the additional reach distance
obtained when the torso is allowed to flex, bend, and
twist. However, this reach envelope is still substantially
smaller than the observed envelope.
Analysis of the kinematics of the study participants
showed two important differences compared to the
terminal postures in Figures 2 and 3. First, the study
participants rolled their pelves on the seat to obtain
greater reach distance. Figure 4 shows the large
increase in lateral reach distance that is obtained by
rolling the pelvis.
Figure 2. Illustration of posture on boundary of maximum
reach envelope generated using mobility starting at the
sternoclavicular joint (innermost envelope).
Figure 3. Illustration of posture on boundary of maximum
reach envelope generated using mobility from starting at the
Figure 4. Expansion of reach capability obtained by rolling the
pelvis (compare with Figure 3).
Second, the study participants showed considerably
more range of motion in the shoulder, particularly at the
sternoclavicular joint, than is provided by Jack in its
default configuration. In Figure 5, the joint limits at the
sternoclavicular joint have been relaxed to better
approximate the kinematics observed in the laboratory
study. Combining torso mobility with pelvis roll and
increased range-of-motion at the sternoclavicular joint
results in a reach capability that closely approximates
that which was observed in the laboratory, although the
change in the shoulder motion introduced some
graphical anomalies in the figure.
Figure 5. Expansion of reach capability obtained by rolling
pelvis and releasing limits at sternoclavicular joint to better
approximate the observed (outermost) reach envelope.
The analysis in this paper used the Jack human model,
but the results of this study indicate that any figure
model that relies on kinematics and joint limits to obtain
maximum seated reaches for conditions typical of civilian
road vehicles will give predictions that are likely to be
substantially in error. The shoulder-mobility problems
documented above are due in part to deficiencies in the
construction of the shoulder joints in Jack, but the
majority of the discrepancy between the observed
maximum reach capability and that predicted by the
model is associated with pelvis rotation.
The study participants used pelvis rotation to
substantially increase their reach distances. The effect
was observed for all reach directions, even for vertical
reaches. In vertical reaches, the participants tilted their
pelves to the left to elevate their right shoulders. As
illustrated above, rolling the pelvis toward a lateral reach
provided a large increase in distance. Pelvis postures at
maximum reach do not appear to be determined
primarily by joint ranges of motion (at the hips, for
example). Rather, the pelvis and torso postures are
limited by the balance requirements of the task. In this
study, participants held a steering wheel or table with
their left hands while performing the right-hand reaches.
Analyses of forces exerted at the hands and under the
seat indicate that the people use a combination of a shift
in seated position (obtained by rolling the pelvis) and
counterbalance force at the hand to maintain control of
their posture in extreme reaches (Parkinson et al. 2002).
The fact that pelvis rotation in maximal seated reaches is
constrained by balance rather than joint range of motion
means that a strictly kinematic approach to predicting
maximum reach capability is not likely to be accurate.
Instead, a model that accounts for balance-maintenance
behavior is needed. Such a model could use an
empirically derived motion prediction or could involve
static or dynamic biomechanical calculations of balance
The current analysis suggests that kinematic methods
for generating seated reach envelopes that do not
include pelvis motion are likely to be conservative; the
true maximum reach envelopes are probably larger, as
illustrated above. Reach targets within these envelopes
are very likely to be reachable by people who match the
simulated figures in size and seating position. However,
the conservative solution is inadequate when a control
must be placed beyond the (apparent) reach envelope.
Based on the current analyses, and perhaps intuitively,
the human factors analyst will know that people can in
fact reach beyond the reach envelopes typically
generated by human models. But, lacking information
about how much greater actual reach capability will be, a
quantitative analysis of the suitability of a design
requiring near-maximal reaches cannot be conducted.
Contemporary use of the J287 reach curves is instructive
in this regard. Most vehicle designers currently use the
reach curves obtained with fixed-length, highly restrictive
torso belts that effectively represent reach capability
without torso motion. Of course, they are well aware that
modern restraint systems allow substantial torso
mobility, but experience has shown that controls located
within the more-restrictive curves are generally
reachable by a large percentage of the driving population
with acceptable difficulty. In effect, curves that represent
maximum reach for a restrictive condition are used to
approximate comfortable reach for a less restrictive
condition. As with the conservative, kinematically
generated reach envelopes, this approach has generally
been effective, particularly for passenger cars.
However, the ongoing increase in the number of in-
vehicle controls, particularly in commercial vehicles, is
exposing the problems with this approach. With a large
number of controls to be placed and a limited area within
the traditional design curves (or within envelopes
generated kinematically using human models) some
controls must be placed in zones that are “unreachable”
according to the design tools that are currently used.
Once beyond the current zones, no information is
available on the relative reachability of various potential
Most users of digital human models will attempt to
overcome these limitations by kinematic manipulations
of the figure, much as those represented above.
However, lacking quantitatively valid models of postures
and motions for extreme reaches, the results may not be
useful. For example, a user of a digital human model is
unlikely to guess the correct amount of lateral pelvis
rotation when simulating a lateral reach.
Two solutions are needed. First, human figure models
used for vehicle interior design should include
functionality for accurate prediction of postures and
motions in near-maximal seated reaches, including
pelvis mobility and consideration of balance
requirements. Second, SAE J287 should be upgraded
to accurately represent the reach capabilities of drivers
in modern vehicles with current belt restraints. Because
maximum reach envelopes are not sufficient for
optimizing control layouts, an updated J287 should
include a model that predicts the difficulty of submaximal
This research was sponsored by the University of
Michigan Automotive Research Center and by the
partners of the Human Motion Simulation (HUMOSIM)
program at the University of Michigan. HUMOSIM
partners include DaimlerChrysler, Ford, General Motors,
International Truck and Engine, United States Postal
Service, U.S. Army Tank-Automotive and Armaments
Command, and Lockheed Martin.
Abdel-Malek, K, Yang, J., Brand, R., Tanbour, E.,
(2001). Towards understanding the workspace of the
upper extremities. Technical Paper 2001-01-2095.
Society of Automotive Engineers, Inc., Warrendale, PA.
Chaffin, D.B., Faraway, J., and Zhang, X. (1999).
Simulating reach motions. Technical Paper 1999-01-
1916. Society of Automotive Engineers, Inc.,
Green, R.F. and Hilby, D.L. (1999). Validation of the
Boeing CATIA human model reach algorithm. Technical
Paper 1999-01-1902. Society of Automotive Engineers,
Inc., Warrendale, PA.
Hammond and Roe (1972). SAE controls reach study.
Technical Paper 720199. Society of Automotive
Engineers, Inc., Warrendale, PA.
Kennedy, K. W. (1964). Reach capability of the USAF
population. Phase I-the outer boundaries of grasping-
reach envelopes for the shirt-sleeved, seated operator.
Report No. AMRL-TDR-64-59. Air Force Systems
Command, Aerospace Medical Research Laboratory,
Wright-Patterson AFB, Ohio.
Parkinson, M.B., Chaffin, D.B., and Reed, M.P. (2002).
Maintaining Balance in Seated Reaches.
. Rehabilitation Engineering and
Assistive Technology Society of North America,
Reed, M.P., Parkinson, M.B., and Chaffin, D.B. (2003).
A new approach to modeling driver reach. Technical
Paper 2003-01-0587. Society of Automotive Engineers,
Inc., Warrendale, PA.
Park, W., Woolley, C., Foulke, J., Chaffin, D.B.,
Raschke, U., Zhang, X. (1999). Integration of magnetic
and optical motion tracking devices for capturing human
motion data. Technical Paper 1999-01-1911. Society of
Automotive Engineers, Inc., Warrendale, PA.