This document discusses the application of historical mobility testing conducted by the U.S. Army Engineer Research and Development Center over 50+ years to sensor-based robotic systems. It summarizes the Center's extensive experience conducting experimental field testing of military vehicles to develop predictive models of vehicle-terrain interactions. These capabilities could immediately apply historical knowledge to developing, refining, and implementing future robotic systems by utilizing current testing capabilities with sensor-based drivers or terrain data from sensors. Translating sensor data into engineering terms would also allow assessing robotic performance for deployment and ensuring maximum performance.

1. APPLICATION OF HISTORICAL MOBILITY TESTING TO
SENSOR-BASED ROBOTIC PERFORMANCE
William E. Willoughby, Randolph A. Jones, George L. Mason, Sally A. Shoop, James H. Lever
U.S. Army Engineer Research and Development Center, CEERD-GM-M, 3909 Halls Ferry Road,
Vicksburg, MS, USA 39180-6199
ABSTRACT
The USA Engineer Research and Development Center (ERDC) has conducted on-/off-road experimental field testing
with full-sized and scale-model military vehicles for more than fifty years. Some 4000 acres of local terrain are
available for tailored field evaluations or verification/validation of future robotic designs in a variety of climatic
regimes. Field testing and data collection procedures, as well as techniques for quantifying terrain in engineering terms,
have been developed and refined into algorithms and models for predicting vehicle-terrain interactions and resulting
forces or speeds of military-sized vehicles. Based on recent experiments with Matilda, Talon, and Pacbot, these
predictive capabilities appear to be relevant to most robotic systems currently in development. Utilization of current
testing capabilities with sensor-based vehicle drivers, or use of the procedures for terrain quantification from sensor
data, would immediately apply some fifty years of historical knowledge to the development, refinement, and
implementation of future robotic systems. Additionally, translation of sensor-collected terrain data into engineering
terms would allow assessment of robotic performance for a priori deployment of the actual system and ensure maximum
system performance in the theater of operation.
Keywords: mobility testing, mobility history, vehicle modeling, vehicle terrain interaction, terrain characterization,
sensor development
1. INTRODUCTION
The US Army Engineer Research and Development
Center (ERDC) has conducted on-/off-road
mobility/trafficability research including experimental field
testing with full-sized and scale-model military vehicles for
more than fifty years. The Mobility/Trafficability Section was
created in the mid-1940’s from the Soils Division of the U S
Army Corps of Engineers’ (USACE) Waterways Experiment
Station (WES) in Vicksburg, Mississippi, to address military
vehicle shortcomings apparent to combat engineers in World
War II operations. Initially, actual field testing of vehicles in a
variety of soil conditions was the focus of the group, and
results were encouraging. However, mobility planners soon
realized special facilities were required for laboratory
parametric testing of scale-model vehicles, so in 1957 some
24,000 square feet of unique laboratory facilities were added
(shown in Figure 1.) that defined the state of the art in
mobility testing at that time. The main operational area Figure 1. SMALL-SCALE TEST FACILITY. The
enclosed the principal testing apparatus: a cantilevered facility consistsed of a remotely controlled
structure supporting a carriage to which scaled vehicle dynamometer carriage (shown) that rides on overhead
running gear could be attached. Beneath the carriage, a line of rails and could accommodate wheels up to 32 in. in
metal cars filled with processed soil formed a test lane through diameter and tracks up to 4+ ft in overall length.

2. which the models traveled. Apparatuses for measuring soil strength, stress and strain factors, wheel or track torque, and
other instrumented mobility data adjoined the edifice. The main building also contained a stationary soil processing
plant, a mobile soil processor, additional soil
cars, and a track system for moving the cars
into/out of position. Pressure cells placed at
specific positions and angles in the soil cars
provided important data on soil reactions to
traffic of the models attached to the carriage.
Results were very encouraging, and a
larger facility (shown in Figure 2) was added
to allow full-scale testing of vehicles in large
concrete soil bins that were 5-ft-deep by 20-
ft-wide and nearly 200-ft-long. A variety of
soil data collection devices, such as the hand-
held cone penetrometer developed at WES,
the bevameter developed by the Land
Locomotion Laboratory at the Detroit
Arsenal, and the torque shear vane
successfully used by British trafficability
engineers, were fully mechanized and
instrumented for data collection. Comparisons
of laboratory tests with actual field test data
concluded that wheel or track models of one-
fourth to one-third the size of those on actual
military vehicles could be effectively Figure 2. LARGE-SCALE TEST FACILITY. Equipment contained
evaluated and data extrapolated for design of in this laboratory permited the simultaneous testing of single wheels up
full-sized vehicles. The large-scale facility to 72 in.' in diameter, single tracks up to 48 in. long, and full-size
actually allowed validation of the scaled data vehicles.
from the vehicle models.
The WES assumed another area of field research in 1954, when the USACE Office of the Chief of Engineers
(OCE) charged the Trafficability Section with the task of developing a methodology for predicting trafficability in
snow-covered terrain. In the summer of 1954 WES began field investigations on the Greenland Icecap, which continued
in 1955 and 1957. These test programs established criteria for trafficability projections in artic conditions and
recommended the adoption of the cone penetrometer as the most practical instrument for field tests. However, the
relatively firm artic snow of Greenland produced few vehicle immobilizations, and the data indicated testing was
required in softer snows of subartic areas and during springtime thaws. Accordingly, testing was initiated in Colorado in
1954, Canada and Michigan in 1955, and Colorado in 1958. Results of this testing indicated that artic snows generally
supported wheeled vehicles, but subartic and thaw-conditions produced “NOGO’ conditions for all conventional
wheeled military vehicles used in the experiments. Further, these tests determined that the first vehicle pass in subartic
snow was the most difficult.
The success of the snow program led the USACE to embark on a consolidated research program regarding the
effects of winter conditions on military operations. The USACE had previously been responsible for two research
organizations involved in cold regions research: the Snow, Ice and Permafrost Research Establishment (SIPRE) at
Wilmette, Illinois, and the Artic Construction and Frost Effects Laboratory (ACFCL) in Boston, Massachusetts.
Several winter engineering cooperative programs with Dartmouth College led Dartmouth to offer leased land near the
college in Hanover, New Hampshire, to USACE, and in June 1960 the SIPRE, ACFCL, and Dartmouth chartered the
Cold Regions Research and Engineering Laboratory (CRREL) as the Corps’ laboratory responsible for cold regions
research which continues today.
In 1960, OCE provided more impetus to the encouraging mobility research area by assigning a long-term
program to WES to determine the effects of the dimensions of pneumatic tires on the performance of military vehicles.

3. The primary objective of the program was to determine the behavior of various soil types when subjected to traffic by a
number of tires with various sizes, proportions, and inflation pressures. Hopefully, testing would lead to development of
procedures for selecting proper tire sizes and inflations for specified soil conditions. Almost concurrently, hostilities in
Southeast Asia were drawing interest from the US military, and in early 1962, the US Army Materiel Command (AMC)
requested that WES become the managing agency for the Mobility Environmental Research Study (MERS). The MERS
program required an extensive study of the environment of Thailand, especially as it pertained to the design and
employment of materiel and materiel systems. Thailand was an ally of the United States, and operations in that country
could be conducted unimpeded and with the support of a friendly government. Project planners noted that military
environments in Thailand were very similar to those of Vietnam so that analogous comparisons could be made that
would assist military operations later.
As the US became more involved in Southeast Asia, the MERS program gained significant momentum, and
other agencies including the Land Locomotion Laboratory, Army Transportation Board, and the Advanced Research
Projects Agency joined in the study. Some 2400 sampling sites were carefully characterized using soil sampling, terrain
surveys, hydrographic mapping, vegetation analysis, aerial photography, and extensive field experiments with
conventional and experimental vehicles yielded a wealth of correlated data over an extended time period. Additionally,
engineering tests and procedures were developed and refined to allow characterization of terrain sites for mobility
analysis, and concurrent experiments were
conducted stateside and in tropical areas to
verify correlations of vehicle performance and
terrain characterization. Additionally, field
experiments began stateside to develop
vehicles for operations in the marshy areas of
very low trafficability, or in riverine
environments. The WES and other agencies
began evaluations of experimental amphibious
vehicles such as the Marsh Screw Amphibian,
Riverine Utility Craft, XM759 Logistical
Carrier, and others specifically under
development to operate in Southeast Asian
terrains.
Stateside there was also interest in
sending astronauts to the moon. The WES soil
laboratories were engaged by contractors for
the National Aeronautics and Space
Administration (NASA) to use the laboratory
test facilities with various sands and other
materials to simulate lunar soils in order to Figure 3. LUNAR ROVER VEHICLE (LRV) WHEEL.. This is one
develop wheels for a lunar roving vehicle. The of three wheels tested for NASA for the moon landings and is the
Boeing-GM wheel, shown in Figure 3, was design selected for the landings. The mesh portion is made of woven
eventually selected based on its superior piano wire and the chevrons are of titanium. The inner ribs are merely
woven wire-design and in 1971 the Lunar to protect the outer portion of the wheel from hitting the axle of the
Rover Vehicle successfully landed on the wheel in case of a sever jolt.
moon and operated with a WES-validated
wheel design.
2. MOBILITY MODEL DEVELOPMENT
By 1970 researchers had reached the conclusion that knowledge derived from previous WES studies, as well as
experimental and theoretical developments from other mobility research programs at other Army agencies, could be
used to make limited predictions of vehicle performance in other areas of the world. Based on the premise that those

4. essential factors necessary to evaluate vehicle performance in a given environment could be quantified, a cross-country
prediction model was structured whose three primary elements of vehicle, terrain, and driver could be logically
structured to take advantage of all the WES-derived vehicle/terrain interactions measured previously. The program
needed a proponent, and in 1971 The Army Materiel Command (AMC) stepped forward and requested that the three
Army laboratories engaged at that time in mobility research (WES, the US Army Tank-Automotive Command
(TACOM), and CRREL) cooperate to achieve a common goal. Thus, the groundwork was laid for development of a
first-generation computerized ground mobility model [1] to be known as the AMC-71 Mobility Model, or simply AMC-
71.
The physics-based, sum-of-forces model recognized the three primary elements in the mobility equation; the
vehicle, the terrain, and the driver. It was noted that each required independent analysis and quantification, but that
inter-relationships were required in order to predict vehicle performance by summing tractive and resistive forces
required in a given terrain. Data bases for the most common military vehicles were developed, including specifications
of geometric and mechanical characteristics that could be easily computerized. Terrain modules consisted of relatively
small, homogeneous “patches” characterized by some thirteen measurements reflecting soil type and strength, slope,
surface roughness, obstacle geometries, and vegetation [2] derived from previous studies, especially the MERS research
in Southeast Asia. Linear features that crossed the terrain, such as streams or walls, were characterized as to width,
depth, velocity, type, strength and material properties, and other elements. All of the terrain features were then
combined on detailed terrain ‘maps’ to present an overall mathematical interpretation of any area. Driver information
such as reaction time, acceleration-limited ride and shock performance, braking, and visibility were also incorporated. A
methodology was developed to depict vehicle performance for specific travel paths and for general cross-country
movement. Thus, if areas anywhere in the world could be characterized using available data, vehicle performance could
be accurately predicted. If the direction of movement over the terrain was known, then a more accurate traverse or trail
speed could be made that incorporated vehicle direction and interaction with each successive terrain unit encountered
through typical accelerations or decelerations that occurred as the terrains were challenged.
Following development, a three-year validation program was initiated to refine the model’s relationships for a
military jeep, a 2-1/2-ton truck, an M113 personnel carrier, and M48/M60 tanks [3]. Test sites included Fort Sill,
Oklahoma; Eglin AFB, Florida; Yuma Proving Ground, Arizona; Houghton, Michigan; and Fort Knox, Kentucky.
Results indicated that the initial model was about seventy percent accurate, and shortcomings were in quantification of
terrain surface roughness, obstacle override, and vegetation influences, and it was noted that driver performance
obviously exerted a tremendous influence on vehicle performance. This first-generation model also was successfully
used in ‘Project Wheels’ which resulted in identification of equivalent capabilities among the Army’s vehicle systems,
and the subsequent elimination of several duplicate systems. This program demonstrated the power of this new
technology and resulted in significant cost savings due to the vehicle systems eliminated with no reduction in
performance capability.
By 1975 more refined quantification of terrain areas and improved vehicle-terrain interaction relationships led to
the second-generation product designated Army Mobility Model-74, or AMC -74 [4]. This version described each aerial
unit through twenty-two mathematically–independent terrain factors rather than the previous thirteen. Ten classification
factors for linear features and an additional nine for roads further enhanced the model. Whereas AMC-71 assumed all
running gears of a vehicle were powered, geometrically identical, and equally loaded, AMC-74 could simulate vehicles
and vehicle combinations having various configurations of powered, braked, and towed wheels and tracks with various
loads. This version also contained equations that allowed simulations of travel across slippery soils, muskeg, and snow
in addition to the fine- and coarse-grained soils covered by AMC-71. Additionally, AMC-74 provided more detailed
and accurate quantification of driver behavior, one of the shortcomings of the earlier model.
It had been recognized by the North Atlantic Treaty Organization (NATO) as early as 1976 that a need existed
for a ‘standard’ mobility model for member countries to use for comparing overall vehicle performances in terms of
mobility, armor protection, and fire power. In 1977, the model was offered as the solution for mobility comparisons
with recommendations for improvements in certain submodels. After a period of research and revision by the member
countries, the improved model soon found acceptance abroad. In 1978, NATO adopted AMC-74 and its subsequent
refinements for use by member countries as an ‘initial reference’ model for comparing current vehicles among member
countries, and also as a tool for planning and designing new vehicles. By 1979, the now internationally-sanctioned

5. mobility model became known as the NATO Reference Mobility Model, or NRMM [5]. Research and developments
have continued and by 1992, the second version, NRMM II [6], was adopted and refinements continue to this day.
3. USE OF NRMM FOR VEHICLE PROCUREMENT AND COMPARISON
During the late 1970’s and early 1980’s, the US embarked on development and acquisition of a new fleet of
vehicles to replace the aging jeeps, trucks, armored personnel carriers, and tanks of the 50’s and 60’s. Although NRMM
was not directly tailored for ‘building’ a vehicle per se, the USA Training and Doctrine Command (TRADOC) and
USA TACOM soon found that NRMM could be used to specify requirements for expected vehicle performances for
new vehicles or upgrades of existing vehicles. Three representative terrain scenarios developed previously to showcase
NRMM (central Germany, arid areas of the Middle East, and areas of interest in Korea) soon gained acceptance for
evaluation of expected performances in these and analogous areas of the world. Studies began by TRADOC to derive
attributes for future vehicles using these terrains, and TACOM used NRMM mobility specifications and testing
procedures to derive required vehicle
performances within the contracts for
procurement. Figure 4 shows a Palletized
Loading System during Product Qualification
Testing performed by ERDC. Most of the US
vehicles still in use today were procured
through this process. Additionally, terrain
statistics from the study areas (percent slope
occurrences, obstacle descriptions, vegetation
stem sizes and spacings, soil strengths during
the various seasons, etc) could be used based
on their occurrences within the terrain to
specify operational scenarios for vehicles in
these terrains [7]. Likewise, a reverse-
engineering process has been used to derive
required vehicle attributes for operations in
specific areas, generally leading to trade-off Figure 4. PALLETIZED LOADING SYSTEM. Tested in 1989 at
analyses of performance versus cost. ERDC for Production Qualification Testing. The PLS is undergoing
Utilization of NRMM in this process over drawbar pull testing on a clay soil.
some 25 years led to the US possessing the
finest fleet of military vehicles in the world today.
4. APPLICATION OF NRMM TO ROBOTICS AND SENSORS
Currently, cooperative research at the ERDC and TACOM is focused on extension of NRMM to include smaller
or mini-robotic vehicles while understanding that NRMM was developed for vehicles of 500-600 lbs and larger
(generally vehicles that could be operated by a man onboard). Whereas the physics-based logic is appropriate for
smaller (and larger) vehicles, some of the model’s internal empirical relations may be extended to enhance model
accuracy. For example, the effects on very small vehicle performance of small vegetation (trees less than 2-3 inches in
diameter, tall grass, etc) or small obstacles (stones instead of boulders, stumps, small ditches or walls, etc) is not fully
quantified. Preliminary research indicates additional terrain classes may be required in order to make accurate
predictions or reverse-engineer robotic requirements, unless most future robotic vehicles will be expected to avoid all
potential immobilizing terrain elements, which does not appear logical. Obviously, inexpensive, disposable or tele-
operated robots for use in mine detection or other dangerous tasks may not require extended analysis prior to use.
However, if we assume that some 40 percent of the Future Combat System (FCS) vehicles will be robotic or
autonomous, it would seem logical that the technology base that has been responsible for mobility research for some 50
years would be consulted regarding an engineering approach to vehicle development rather than leaving such
development solely to a winning contractor who has little historical background in the field. In this respect,

6. modifications made to NRMM will only enhance future vehicle designs and should bolster a research area dedicated to
maximizing robotic and autonomous vehicle performances.
In the pursuit of this goal, the ERDC has been developing a new physics-based terrain mechanics model that can
be used in multibody dynamic environments. The terrain mechanics model builds off the historical information used in
NRMM but creates a more accurate and robust mobility prediction engine as shown in Figure 5. The heart of this
model is the Vehicle Terrain Interaction (VTI) that can be used for onboard maneuver decision logic. The terrain
mechanics model was developed for the real-
time simulation environment and primarily
for implementation into a multibody
dynamics engine that drives motion-based
platforms that can also link into the Semi-
Automated Force (SAF) simulations such as
the OneSAF Objective System. The fidelity
of the VTI is such that it can also serve as the
mobility engine for onboard maneuver
decision logic. When the VTI is coupled with
the onboard vehicle controller, it offers the
realism of mobility performance predictions
that can assist in maneuver decision logic for
path selection. This will enhance the ability
to select the best path from the “GO” path
corridor. The VTI is designed to evaluate the
mobility potential at the wheel or tire
interface by describing the traction potential
of each terrain node under the traction Figure 5. HIGH FIDELITY VEHICLE TERRAIN INTERACTION
element. This level of traction analysis is MODEL. HMMWV crossing a gap. The simulation shows traction
critical for obstacle negotiation, gap crossing, and pressure distrubitions under the wheels and the rear of the vehicle
or border-line “NOGO” situations. in contact with the terrain.
Historically, the principal weakness in the various physics-based vehicle performance modeling systems has
been an inability to map terrain of sufficient area for practical military applications at the fidelity required to accurately
assess vehicle movement at reasonable cost. The area of greatest research interest for such applications is development
of procedures to evaluate and collect terrain data in areas of interest via remote and/or onboard sensors while the vehicle
is in an operational context. The costs associated with development of terrain data sets of the quality and fidelity needed
for accurate vehicle predictions by NRMM in 1970’s dollars were on the order of $100,000-150,000 for development
and validation of a 1:50000 quadrangle map sheet (about 20 km X 20 km) for use in tactical operations. Those costs are
obviously substantially higher today, and the addition of characteristics to predict very small vehicle performances
would increase this cost. There appears to be little interest among vehicle developers or the military in providing the
funds required to produce such data sets, and perhaps some underlying political pressure not to “map’ specific areas of
the world in order not to single out potential areas of operation by US forces or unduly rile suspect countries. However,
the model’s utility is based on supplying it with engineering physical properties of the terrain in order to obtain
meaningful predictions. Thus, the suggestion to research the area of processing static and onboard sensor information
along the route traveled by a scout vehicle in order to develop relatively accurate assessments of the terrains being
challenged and the logic required to negotiate the mission in the area.
Based on the many years of expertise garnered from mobility research on a myriad of conventional and
unconventional vehicles, the ERDC has expertise in the production of ‘typical’ high-fidelity terrain information,
especially that sensitive to mobility and maneuver, which would be useful for overall system performance evaluation.
Although much more basic and applied research is still required to create actual ‘mapped’ areas from sensor data
anywhere in the world while ‘traveling’ in the terrain, the logic required to accomplish this task is currently a proposed
area of ERDC research starting in 2007. Statistical extrapolation of ‘measured path’ tractive and resistive data to
surrounding terrains obviously will require more research in order to develop a capability to ‘map’ operational areas
with sufficient accuracy to take advantage of the available vehicle models. However, the potential of a capability for

7. defining a mission, identifying the characteristics of the operational environment, identifying sensitive environmental
effects that will affect vehicle movement, and then developing the methodology to quantify the sensitive parameters via
onboard or remote sensing techniques seems well worth the research effort!
How would we expect all of this to work in a sensor environment? The sensor technology could be used as a
substitute for human ‘sensors’ for remotely controlled or autonomous vehicle operation. In this manner, sensed data
could be translated into soil physical properties (type, strength, moisture condition, etc.) via remote means, or ‘look-
ahead’ schemes could be developed to assess terrain impediments before the vehicle encountered them, or sensed data
could provide ‘near-area’ awareness to provide levels of autonomous capabilities (terrain information or location, other
vehicle positions, relevant mission characteristics, etc). The sensor technology also could be used to enhance or
supplement the human capabilities for legacy vehicle tasks, such as providing enhanced wide-area assessment of actual
or impending terrain conditions, enemy locations or other information for tactical operations, or related scout or
reconnaissance missions. Based on the lengthy experience described earlier, the ERDC’s contribution would center on
increasing the fidelity and decreasing the resources required in obtaining the various information necessary to assess the
physical impediments to vehicle movement relative to the mission. The ERDC would also offer a specialty in
quantifying vehicle system missions, identifying sensitive parameters associated with operational areas and mission
requirements, and quantifying the impact of the fidelity of sensitive vehicle movement parameters on mission success.
One mission concept that could be advanced if onboard sensor technology could be used for terrain
characterization is the concept of “collect, use, and disseminate”. The process of planning missions is based on using
the best available terrain information to determine the best “GO” corridor for the mission and adjust the mission
onboard as it unfolds. For autonomous operations, the mission adjustment is based on maneuver logic using real-time
information from onboard sensors either stand-off or tactile. The accuracy of the mission adjustment is based on the
amount of terrain information available and the onboard maneuver logic. More terrain information allows for higher
fidelity onboard terrain mechanic models, which in turn will assist the maneuver decision logic in making a more
accurate assessment of the “GO” path selection. Once the best path is chosen from all possible “GO” paths, the local
terrain information can be disseminated and used for developing mobility data layers that can update maneuver support
information. The biggest problem in this scenario is quantifying the performance pay-off. We know that more terrain
information will result in better maneuver decisions but by how much is yet to be determined. It may only be a 10
percent improvement over current abilities, but that 10 percent may be the difference in a successful mission versus a
mission failure.
5. SUMMARY
With a background of more than fifty years in mobility engineering research, the ERDC offers a unique and valuable
resource for accurately evaluating and predicting the performances of actual or concept vehicles in various strategic
areas of the world. Possibilities currently being developed for accessing and collecting important terrain information via
onboard or tactile sensors in concert with scout or reconnaissance robots should indicate that the ERDC’s past
experience in terrain and vehicle quantification, whether by on-the-ground surveys or sensor–collected data, should
make it a valuable member of any maneuver support vehicle- or sensor-development team, whether government or
industry.
6. REFERENCES
[1] Rula, A. A. and Nuttall, C. J. Jr. 1971 (May), “An Analysis of Ground Mobility Models (ANAMOB)”, Technical
Report M-71-4, US Army Engineer Waterways Experiment Station, Vicksburg, MS
[2] Shamburger, J.H., Grabau, W.E., et.al Vol. I-Vol. VIII 1967-1968, Mobility Environmental Research Study, “A
Quantitative Method for Describing Terrain for Ground Mobility”, US Army Engineer Waterways Experiment Station,
Vicksburg, MS

8. [3] Schreiner, B.G. and Willoughby, W. E. 1976 (Mar), “Validation of the AMC-71 Mobility Model”, Technical
Report M-76-5, US Army Engineer Waterways Experiment Station, Vicksburg, MS
[4] Jurkat, M. P., Nuttall, C. J., Jr., and Haley, P. W., 1975 (May), “The AMC’74 Mobility Model”, Technical Report
11921 (LL-149), US Army Tank Automotive Command, Warren, MI
[5] Haley, P. W., Jurkat, M. P., and Brady, P. M., Jr. 1979 (Oct), “NATO Reference Mobility Model, Edition I, Users
Guide”, Volume I, Operational Modules and Volume II, Obstacle Module, Technical Report 12503, US Army Tank-
Automotive Research and Development Command, Warren, MI
[6] Ahlvin, R. B. and Haley, P. W. 1992 (Dec), “NATO Reference Mobility Model , Edition II, NRMM II User’s
Guide”, Technical Report GL-92-19, US Army Corps of Engineers Geotechnical Laboratory, Vicksburg, MS
[7] Willoughby, W. E., Jones, R. A., et.al (in publication), “US Army Wheeled Versus Tracked Vehicle Mobility
Performance Test Program”, Vol I-IV, US Army Engineer Waterways Experiment Station, Vicksburg, MS
7. ACKNOWLEDGMENT
The tests described and the resulting data presented herein, unless otherwise noted, were obtained from research under
the Terrain Mechanics Modeling research program of the US Army Corps of Engineers by the Engineer Research
Development Center, Geotechnical and Structures Laboratory. Permission was granted by the Director, Geotechnical
and Structures Laboratory to publish this information.