A GPS Based System for Minimizing Jolts to Heavy Equipment 

Operators 

R. E. Miller, N. T. Lowe 

CDC, NIOSH, Spokane Research Laboratory 

R. Thompson 

University of Pretoria, South Africa 

ABSTRACT 

When two pieces of heavy equipment interact, jolting 

and jarring can occur. During haulage truck loading for 

example, there is a chance that the operator of one or 

both pieces of the equipment will experience jolting and 

jarring. Additionally, a jolt can occur when an off 

highway equipment operator drives over a road defect 

or inadvertently strikes a berm. Aside from the 

operators, there is seldom anyone else that witnesses 

the interaction and can accurately describe the extent of 

the jolting. This makes it difficult for health and safety 

managers to address jolting and jarring. The devices 

and software described in this paper constitute a method 

for installing “black boxes” called Shox Boxes onboard 

equipment that already have a GPS system onboard. 

The resulting configuration provides an objective 

assessment of jolting and a chance to determine the 

root causes of it. The Shox Box system reviews data in 

real time, onboard the vehicles, 24 hrs a day, and sends 

pertinent information via radio to a central database. 

The data generated shows whether jolts are above or 

below a supervisor defined target value for the 

equipment and the tasks being performed. This allows 

health and safety personnel to demonstrate safe 

operation of heavy equipment and recommend 

proactive actions to maintain jolting within a reasonable 

range. 

INTRODUCTION 

Overall health and fitness plays a role in injury 

prevention for operators. Physically demanding 

professions (sports for example) require training to 

prevent injuries. Equipment operators should consult 

with their physician about exercises to strengthen 

vulnerable areas, such as the lower back. Through no 

fault of their own, however, the actions of others or 

conditions such as a defect in the haul road may 

contribute to an operator injury. Human perception can 

be erroneous and misunderstandings as to what was an 

acceptable work practice or condition may happen. 

Therefore, an objective assessment that enables health 

and safety personnel to make data driven analyses is 

needed.

The National Institute for Occupational Safety and 

Health (NIOSH) has researched jolting and jarring 

cooperatively with Phelps Dodge Morenci, Inc. via a 

Cooperative Research and Development Agreement 

(CRADA). Phelps Dodge proposed connecting 

accelerometers with the GPS dispatching systems. The 

concept was to infuse GPS data into the collecting of 

accelerometer data and to record the information 24 

hours a day. Traditionally, jolting and jarring data has 

been collected for a few hours at a time and correlations 

with injury data proved inconclusive. Understanding 

how frequently jolting occurs and what can be done 

about jolting requires 24 hour data. The product of the 

research is called the Feedback to Operator System or 

Shox Box System. The research to date has led to the 

conclusion that the best approach towards reducing 

jolting and jarring in GPS equipped surface mines would 

be to utilize the Shox Box system for a Six Sigma 

approach to the truck loading process. 

The following are some of the factors that determine 

whether or not jolting occurs and also can be affected: 

 1. Operator Awareness and Skills 

 2. Road Conditions 

3. Equipment Design and Maintenance 

 

OPERATOR AWARENESS AND SKILLS 

A central feature of the Shox Box system is its ability to 

provide objective feedback to equipment operators 

regarding performance. Currently, the main application 

is feedback concerning shovel operations. The system 

objectively determines whether a haul truck was jolted 

during loading and quantifies the amplitudes of the jolts. 

A second application is the miles per jolt ratio, which 

measures the proficiency of truck operators. Although 

these applications are in surface mining, the system 

could be adapted to other work environments. 
The main application is to determine loading jolts during 

shovel operations, but statistically speaking, jolts during 

loading are infrequent. Loading jolts were 15 and 14 

percent of the trucks’ totals, respectively, for calendar 

years 2001 and 2002. However, when they do occur it 

is helpful to have an objective measurement to refer to 

during a discussion. An aim of the cooperative research 

is to reduce jolting during loading by applying 

engineering controls to the loading process and via 

supervisor to operator feedback. 

The second application that provides objective feedback 

about performance is the miles traveled per jolt ratio. 

Equipment operators do not determine the road 

conditions or the maintenance of their equipment. 

However, they do control the location of the equipment 

within the lane, speed, and braking. Jolts at shovels do 

not count towards the jolt total. The ratio of miles per 

jolt is a qualitative measure of driver proficiency. 

Numbers greater than 1900 miles per jolt have been 

observed. When this occurs, it is an accomplishment of 

the truck operator, truck design, and road/truck 

maintenance. The lowest numbers were less than 100 

miles per jolt. Research is needed to determine how 

these numbers can be communicated to enhance truck 

operator awareness. Such work would focus on a better 

understanding of jolting factors; either related to truck 

operation (sharp application of brakes), drive-train 

induced jolts, or those purely related to the condition of 

the road (including readability from the operator’s cab). 

This careful attention to the Human Element1

 has been 

shown to result in increased safety and availability of the 

equipment2

. 

A futuristic Shox Box application could integrate road 

jolt data into a “heads up” proximity warning display. It 

has been demonstrated that road defects and prescribed 

road maintenance can be processed and displayed in 

real time3

. Utilizing this approach, the truck operator 

would see road defects on their screen before the truck 

arrives at the location of the road anomaly4

. This would 

improve readability of the road and allow the operator to 

anticipate when to slow down or drive around a road 

defect. 

 

ROAD CONDITIONS 

Four haulage trucks at the Morenci mine were 

instrumented in 2000 with the Shox Box “black boxes”. 

The boxes detect vertical jolts to the trucks’ cabs 

anytime that the engines are on5

. For calendar year 

2001, 85 percent of the jolts to the trucks occurred on 

the haulage roads and the rest at loading points 

(shovels). For calendar year 2002, 86 percent were 

haulage road jolts. Since 2000, ten more trucks have 

been instrumented with various versions of Shox Boxes. 

This data correlates with an injury report by Aldinger, 

Kenney, and Keran6

. In their study of surface coal 

haulage mine injuries, 1989-1991, these researchers 

found that rough ground was the main category for 

jolting and jarring incidents. 

Since the vast majority of jolts occur on haulage roads, 

a jolt mapping feature now shows jolts on a mine map. 

A Geographical Information System (GIS) map of the 

mine can be viewed with the locations of jolts reported 

by the trucks. However, a location that resulted in one 

jolt has the same priority as a location with many jolts. 

To prioritize road maintenance, an algorithm is needed 

that denotes clusters of jolts. This would likely be based 

on a combination of jolt severity experienced by the 

operator, expected traffic volume on the particular 

section of road, and an economic assessment of rolling 

resistance versus costs per ton hauled. Road 

maintenance models exist for haulage trucks. To apply 

them here would require a conversion between 

conventional measures of road roughness and Shox 

Box parameters. Irrespective of the Shox Box system, 

an academic understanding of the relationship between 

physical road profiles and the resultant jolting severity 

requires more experimentation. 

EQUIPMENT DESIGN AND MAINTENANCE 

The Shox Box system distinguishes between jolting on 

roads and jolts that occur during loading. Currently, it 

lacks a transducer to determine the root of the jolt. A 

jolt at a shovel could be due to dropping the load from 

too high, the shovel striking the side of the haulage bed, 

or a boulder. Instrumentation or cameras on shovels 

that determine the position of the shovel when a jolt 

occurs would be very beneficial. With this 

instrumentation and/or human observation, a Six Sigma 

DMAIC (define, measure, analyze, improve, and 

control) approach to the loading process would identify 

what conditions result in jolts. Insight into equipment 

interactions would lead eventually to process or 

equipment changes. 

Overall, the quality of equipment maintenance must 

remain high, for some of the Shox Box features to be 

applied. A jolt occurring on the haulage road could 

partly be due to an improperly tuned truck suspension. 

Preventative maintenance is a key to success. To 

delineate whether a jolt is induced by the road or a truck 

malfunction, existing truck maintenance systems may 

need to be accessed and truck parameters verified7

. 

SHOX BOX TECHNOLOGY 

For the purposes of this paper a jolt is defined as a peak 

in acceleration below 120 Hz and above 2 g (> 0.5 g 

rms). ISO 2631 style frequency weightings were not 

applied to the data stream, to reduce hardware 

complexity. Jarring for the purposes of this paper is 

defined as low amplitude, yet perceptible peaks in 

acceleration/vibration, which are less than or equal to 

0.5 g rms. 

Traditionally, measuring jolting and jarring has involved 

an accelerometer connected to a data logger. The data 
logger would operate for a few hours at a time. There 

are two downfalls of the traditional approach. First, jolts 

can occur at a rate as low as none, one, or two per day 

and second, incident locations are unknown. Typically, 

data showed mostly jarring, limited jolting, and no 

location information. Correlating the data with 

equipment activities at the time of a jolt was especially 

cumbersome. To remedy the downfalls of the traditional 

approach, personnel at Phelps Dodge recommended 

that NIOSH investigate connecting GPS data from 

haulage trucks and accelerometers5

. 

A Shox Box runs off of the vehicle’s power supply and is 

in operation whenever the vehicle is operating. It takes 

an analog signal from the accelerometer and determines 

whether the value is above or below a preset trigger 

value. If it is higher, then the Shox Box sends a signal 

to the GPS system to record the vehicle location and 

that a jolt has occurred. On the latest version of the 

Shox Box, the peak value of each jolt is also sent (via 

radio) to be logged. 

Besides the GPS hardware, the Shox Box system needs 

several main components. They are the Shox Box 

itself, an analog to digital interface which is connected 

via a radio to the central GPS database, and lastly 

software on the central server which tabulates and 

formats the results. All of the pieces except for the 

Shox Box and the reporting software were already 

available at Phelps Dodge Morenci, Inc. The reporting 

software was written as part of the software 

maintenance contract for the mine’s haul truck dispatch 

system5

. The current cost for the Shox Box alone is 

approximately $150 per vehicle. 

Shox Box System Components 

Two of the more recent advancements to the Shox Box 

system have been in the software that produces the 

data report and the third was with the electronics 

attached to the accelerometer. 

The first advancement was a subroutine for determining 

when a jolt occurs during loading. This is a fairly 

complex function that was made efficient because of the 

design of the dispatch software. 

Secondly, a subroutine was written to calculate the miles 

per jolt ratio. It divides the total distance traveled by a 

vehicle over a given time period by the number of jolts 

logged. The resulting ratio is a measure of an 

equipment operator’s efficiency in terms of smooth 

operating. This application can be implemented for 

heavy equipment without a central database. However, 

downloading data by hand from each piece of 

equipment can prove to be cumbersome. 

The most recent advancement is that the electronics 

now trigger off of the root mean square (rms) value of 

the acceleration signal and also output an analog value 

corresponding to the peak rms value of each jolt. This 

change is based on an experiment conducted at the 

Caterpillar Tucson Proving Ground in the Fall of 20003

. 

Caterpillar provided an obstacle course and a haulage 

truck for Spokane Research Laboratory to compare 

various types of haul road defects with the acceleration 

waveforms that they produce. To fully characterize and 

capture information about the test road, the 

instrumentation was set to trigger at a very low level (0.6 

g) and with a low pass filter of 200 Hz. Severe road 

defects were intentionally built into the test track and the 

test truck was run over the test track while loaded and 

unloaded at different speeds. The road defects were 

surveyed with a GPS backpack system so that jolts and 

the haul road section (road defects) could be readily 

matched. The experiment lasted approximately two and 

a half hours of operating time. There were 189 events 

recorded with a four second event window. The 

experiment showed that many road defects can be 

identified by the waveform signature which they 

produce7

. For example, a washboard area in the haul 

road can be clearly distinguished from a dip in the haul 

road. 

While washboard road defects can be significant, they 

tend to produce insignificant, high frequency peaks of 

short duration. Depending on the selection of the 

frequency value, a low pass filter may be adequate to 

solve the problem. However, a rms filter is an 

improvement over traditional methods because it will 

more often trigger the logger on jolts related to 

significant road defects. 

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

Time, sec

Acceleration, g

z - pedestal

z - seat

Waveform for Washboard Jolting 

As can be seen from the table below, a washboard road 

defect is more likely to trigger a traditional data logger 

(19), than one triggered by rms acceleration (15). The 

values 1.1 g and 0.3 g rms were chosen to illustrate the 

differences. 
Number of events 

above 1.1 g in 

amplitude 

Number of 

events above 0.3 

g rms in 

amplitude 

Washboard 

Areas 19 15 

Dips in 

Haul Road 9 15 

Humps 1 4 

Fixed 

Stones 13 14 

Table Showing Improvement by Applying R.M.S. 

For the sake of brevity and intellectual property 

considerations, specifications of the Shox Box hardware 

and accompanying software are not given here. The 

circuit diagrams for the Shox Box may eventually be 

available to companies interested in building their own. 

The authors can provide information on how to acquire 

components to implement the system. 

DISCUSSION 

A significant advantage of the Shox Box system is that it 

is setup to measure jolting and jarring 24 hours a day. 

Traditional methods of measuring jolting and jarring are 

apt to miss jolts because they can occur as infrequently 

as none, one, or two per day. 

The system currently provides objective feedback to 

equipment operators regarding their performance. 

Because of the capability to link GPS and accelerometer 

data, the system is utilized to settle disagreements as to 

whether or not a haul truck was jolted during loading and 

the jolt amplitude. When the Shox Box system is 

enhanced further to include instrumentation or cameras 

on shovels, an engineering control can be pursued. 

Whilst currently unavailable, a “Real-Time Mine Road 

Maintenance Management System” appears feasible 

according to work done with GIS maps of Shox Box 

data. Feasibility of road defect identification by 

qualitative vibration signature was confirmed, although 

development of an operational road maintenance 

system will require enhanced software3

. Once 

developed, a road maintenance system could be 

incorporated into a “heads up” proximity warning 

display. Proximity warning systems based on GPS are 

already on the way towards commercialization4

. 

CONCLUSION 

The Shox Box system was prototyped in a surface 

mining environment and shown to be durable and 

reliable. The equipment interaction and miles per jolt 

applications are two of the system’s features, which can 

be readily duplicated in any heavy equipment 

environment. Situations where heavy equipment and 

onboard GPS are being utilized together lend 

themselves to Shox Boxes. The next step in GPS 

equipped, surface mines is to utilize Shox Boxes and 

apply Six Sigma process control techniques. 

 

ACKNOWLEDGEMENTS 

The authors acknowledge the Fulbright Commission for 

the award of a Fulbright Scholarship to Dr. Thompson. 

They also acknowledge Carl Sunderman and Anna 

Wilson of the Spokane Research Laboratory for the 

design and manufacture of prototypes of the Shox Box. 

REFERENCES 

1. The Human Element, video, Caterpillar, Inc., 1999 

2. Thompson R. J. and Visser A. T., Mine Haul Road 

Maintenance Management Systems, Journal South 

African Institute of Mining and Metallurgy, June 

2003, pp. 303-312. 

3. Thompson R. J., Visser A. T., Miller R. E., and Lowe 

N. T., Development of Real-Time Mine Road 

Maintenance Management System Using Haul 

Truck and Road Vibration Signature Analysis, 

Transportation Research Record, Journal of the 

Transportation Research Board, Eighth International 

Conference on Low-Volume Roads, 2003, No. 1819, 

Volume 1, pp. 305-312. 

4. Holden T. and Ruff T., GPS-based Proximity 

Warning System for Mining and Construction 

Equipment, Proceedings of the 14th International 

Technical Meeting of the Satellite Division of the 

Institute of Navigation (ION GPS 2001), Salt Lake 

City, UT, September 11–14, 2001, pp. 517–525. 

5. Miller R. E., Boman P., Walden J., Rhoades S., and 

Gibbs R., Acceleration and GPS Data Monitor 

Truck-Haulage Jolts, Mining Engineering, SME, 

August, 2000, pp. 20-22. 

6. Aldinger J. A., Kenney J. M., and Keran C. M., 

Mobile Equipment Accidents in Surface Coal Mines, 

U. S. Bureau of Mines, Information Circular 9428, 

1995, 51 pp. 

7. Thompson R. J., Condition-triggered Mine Road 

Maintenance System, THRIP Project 2875, National 

Research Foundation, Pretoria, South Africa, 2004.