SAFETY ANALYSIS OF SURFACE HAULAGE ACCIDENTS

Robert F. Randolph, Research Psychologist

C. M. K. Boldt, Civil Engineer

U.S. Department of Energy, Pittsburgh and Spokane Research Centers 

ABSTRACT

Research on improving haulage truck

safety, started by the U.S. Bureau of Mines, is

being continued by its successors. This paper

reports the orientation of the renewed research

efforts, beginning with an update on accident

data analysis, the role of multiple causes in

these accidents, and the search for practical

methods for addressing the most important

causes. Fatal haulage accidents most often

involve loss of control or collisions caused by a

variety of factors. Lost-time injuries most

often involve sprains or strains to the back or

multiple body areas, which can often be

attributed to rough roads and the shocks of

loading and unloading. Research to reduce

these accidents includes improved warning

systems, shock isolation for drivers,

encouraging seatbelt usage, and general

improvements to system and task design.

INTRODUCTION

Although surface mining has always

experienced lower accident rates than

underground mining, and these rates have been

generally improving, recent increases,

particularly in the number of powered haulage

accidents, have caused concern in the mining

industry. As the most common type of

machinery involved in surface accidents,

haulage trucks have become the primary target

for improving safety performance. This paper

discusses the ongoing efforts by the successors

to the U.S. Bureau of Mines (USBM) to

analyze and solve haulage truck safety issues.

Ideally, accidents would not happen. 

Operating procedures would eliminate all

possible hazards, and these procedures would

always be followed. Equipment would be

perfectly designed, flawlessly maintained, and

never operated outside of design parameters. 

The worksite would be constant and

predictable, introducing no hazards of its own. 

Unfortunately, this is an unattainable ideal --

the realities of people, machinery, and the

mining worksite are constantly pushing one or

more of these conditions outside of the ideal. 

Understanding and controlling the causal

factors in haulage accidents is essential to

reducing their probability of occurring.

Accident Causes and Solutions

Most accident research now recognizes the

role of multiple causes in accidents, including a

significant human performance component. In

the most detailed study of accident causes in
mining, Sanders and Shaw (1988) studied

underground mining accidents through an

expert-panel investigative procedure. Their

research showed that 88% of accidents had at

least two major causes. This study also showed

that “perceptual-cognitive-motor” errors

(related to the more common term, “human

error”) were a causal factor in 93% of the

accidents. While the effort and expense

entailed in this type of analysis have so far

precluded its use in surface mining, the general

principles should be applicable. That is,

attempting to identify a single cause for every

accident is usually an oversimplification. Also,

human performance and limitations will often

come into play, even if other factors (poor

design, dangerous conditions, etc.) essentially

“forced” an error.

In surface haulage, human performance

becomes a critical issue because of the unusual

demands the vehicles place on their human

operators:

C Roadways and work areas change

frequently.

C The sheer mass of the trucks sometimes

requires control inputs (e.g., braking)

far in advance of the desired action.

C In large operations, the drive into and

out of the pit is long and tedious.

C Rough roads and loading impacts can

subject the driver to dangerous shocks

and vibration.

C Visibility is sharply curtailed by the

bulk of the vehicle.

Because of these demands, solutions to haulage

truck safety problems must consider the human

factors aspects of the task, even when

engineering solutions seem most appropriate. 

The specific problems that need to be solved

can be determined by studying the accidents

involving haulage trucks.

ANALYTICAL APPROACHES

Accident data analysis is an indispensable

tool for understanding the causes of accidents. 

Systematic analysis of large numbers of

accidents can reveal patterns and

commonalities that might be not be evident

when looking at a single incident. The analysis

can be based on industry-wide databases of

accidents, in-depth analysis of official written

accident reports, or data collected especially for

the analysis. Each of these approaches has

characteristic strengths and weaknesses.

Industry-wide Databases

The most widely used source of U.S.

mining accident information is the Mine Safety

and Health Administration (MSHA) database

collected from the quarterly 7000-1 and 7000-2

forms. In addition to reports published by the

agency, the raw data is available from their

Internet Web site (http://www.msha.gov). This

data is essentially a census of injuries in the

U.S. mining industry, although it is conceivable

that some accidents are not reported. The

current study reports updated statistics from the

MSHA database, bolstered by cost estimates

from the USBM-developed Accident Cost

Indicator model (ACIM) described in more

detail below.

Textual Analysis of Official Reports

In addition to the coded information about

accidents, there is sometimes a written

description available. For instance, accidents

reported to MSHA on the 7000-1 form also

have a brief description provided by the mining

operation. Fatalities have a more detailed

textual record in the form of an official accident

investigation report. This textual information,

because it is free of the constraints of the

coding system, can incorporate details about the

accident that might be missed otherwise. The

fatality reports are particularly informative,

containing details about the work procedures,

equipment, victims, and even diagrams of the

accident site. Unfortunately, this approach is

not without its limitations. It is very timeconsuming to convert the textual descriptions

into a form useful for tabulating and comparing
Equip. operation

46%

Ingress-egress

26%

Maintenance

22%

Other

6%

Jarring

38%

Loss of control

27%

Passive strain

6%

Collision

9%

All others

21%

Rough ground

45%

Loading shock

34%

Dumping shock

15%

All others

6%

Too close to edge

36%

Runaway

27%

All others

36%

Figure 1. Surface coal haulage truck accident categories in successively higher detail. Based on analysis of written

accident descriptions for 1989-91 (Aldinger, Kenney, and Keran, 1995).

large numbers of accidents. Key information

can be omitted unless the report writer is

following a specified format. This process also

requires subjective judgements that may be

difficult to duplicate or validate.

This analytical approach was successfully

applied to surface equipment accidents by

Aldinger and Keran (1994) in an overview of

the entire mining industry, and by Aldinger,

Kenney, and Keran (1995) in a more detailed

study of the coal segment of the industry. They

employed a panel to categorize accidents based

on the written narratives in the MSHA

database. By using the narratives, they were

free to develop categories of accidents that

were more descriptive than the traditional

categories. In their study of surface coal

mining, Equipment Operation was the most

common category of accident for haulage

trucks (46.3%) followed by Ingress-egress

(25.8%) and Maintenance (22.1%). Within the

Equipment Operation accidents, the most

common types were Jarring (37.7%) and Loss

of Control (26.8%). The main Jarring

categories were Rough Ground (44.5%),

Loading Shock (33.5%), and Dumping Shock

(15.5%). Loss of Control categories included

Too Close to Edge (36.4%) and Runaway

(27.3%). Figure 1 shows how these categories

and subcategories are related.

Seatbelt usage is another area where the

textual information reveals new accident

details. While only 163 of the 2,720 accident

reports studied by Aldinger and Keran (1994)

reported whether or not seatbelts were worn,

these cases at least suggest some trends. For

instance, none of the fatalities in their study

involved a victim wearing a seatbelt. Also,

injuries tended to be less severe (involving less

time off of work) when seatbelts were worn.

Special-purpose Data Collection

The most expensive, but potentially most

rewarding, method of analyzing accident causes

is to perform an independent scientific study. 

Sanders and Shaw (1988) used this method to

investigate causal factors in underground

mining. They conducted independent

investigations of 338 accidents at 20 mines. 

The investigations resulted in detailed

descriptions of each accident, including

interviews with employees and a study of the

worksite and equipment. The methodology was

based on a systems theory of accidents -- that
1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

0

10

20

30

40

50

60

70

80

90

Fatalities

Haulage Trucks

All Others

1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

0

2,000

4,000

6,000

8,000

10,000

12,000

Lost-time injuries

Haulage Trucks

All Others

Figure 2. Surface fatalities and lost-time injuries, 1986-

95.

is, accidents result from a system of interrelated

factors in workplaces, machinery, people, and

social structures. 

Although this process yielded

unprecedented detail about the accidents it

studied, it does have some limitations. The 20

mines studied may not be representative of the

industry as a whole, especially since the sample

consisted mostly of medium-to-large

underground coal mines. This type of study

also tends to be quite expensive, costing

hundreds or thousands of dollars per

investigated accident.

Each of these studies has some merits. 

The strengths of one approach can be used to

complement the weaknesses of others and add

missing pieces to the overall puzzle of true

accident causes. 

ACCIDENT ANALYSIS

The accident trends and breakdowns

reported here cover accidents in the MSHA

database under the category “Ore haulage

trucks, off highway and underground.” 

Accidents classified as occurring underground

or to officeworkers were eliminated so that the

reported data would reflect surface operations

only. The reported data include independent

contractors, and, unless otherwise noted, cover

the years 1986 through 1995. The 1995 data

are currently considered “preliminary” by

MSHA.

1986-95 Trends

Surface mining fatalities, including

haulage truck fatalities, have been generally

declining since 1986. However, although the

industry attained a historic low of 54 fatalities

in 1994, there was a sharp upswing to 70

fatalities in the preliminary 1995 data. A

significant component of this upswing was the

rise in haulage truck fatalities from 10 to 17. 

This increase has been a source of concern in

the mining community. It would be even more

troubling if there were a similar rise in injuries. 

Fortunately, lost-time haulage truck injuries

declined from 579 in 1994 to 460 in 1995,

mirroring an overall surface accident reduction

from 9,040 to 7,883 (figure 2). The overall

trend since 1989 has been a consistent drop in

the number of lost time injuries, with the

exception of a slight rise in 1994. The

increases prior to 1990 can be attributed to

changes and clarifications in reporting

practices, rather than an actual rise in accidents

(Randolph, 1992; Weaver and Llewellyn,

1986).

Estimated Cost

The Accident Cost Indicator Model

(ACIM) (DiCanio and Nakata, 1976) was used

to estimate the total cost of haulage truck

accidents during 1994, the most recent year for

which data are available. The ACIM provides

cost estimates based on publicly available data

on wages, workers’ compensation, medical

payments, investigation costs, and other direct

and indirect costs. Although it has some

limitations, including the omission of data on
1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

0

100

200

300

400

500

600

700

Lost-time injuries

4%

5% 9%

7% 13%

12% 11%

12%

13%

13%

Legend

Operator

Contractor

1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

0

5

10

15

20

25

Fatalities

20%

22%

46% 18%

24%

42%

38%

67%

40%

18%

Legend

Operator

Contractor

Figure 3. Contractor and operator haulage truck

fatalities and lost-time injuries, 1986-95.

1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

Fatalities per 200,000 employee-hours

1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Lost-time injuries

per 200,000 employee-hours

Operators

Contractors

Operators

Contractors

Figure 4. Contractor and operator haulage truck fatality

and lost-time injury rates, 1986-95.

independent contractors, it provides a useful

guideline on the magnitude of costs suffered by

individuals, industry, and society. According

to the ACIM, the six haulage truck fatalities in

1994 cost an estimated $2.58 million while the

519 lost-time injuries cost $3.27 million. The

total estimated cost for haulage truck fatalities

and lost-time injuries in 1994 was more than

$5.8 million.

Independent Contractors

The use of independent contractors in the

mining workforce is rising. They account for

18% to 67% of the haulage truck fatalities each

year (figure 3) and from 4% to 13% of the losttime injuries. The haulage truck accident

fatality rate for contractors has been

consistently higher than the rate for mine

operator employees, although their lost-time

rate has been similar (figure 4). Making

conclusions about these accident rate

differences is hampered by a lack of

information about how many hours are worked

by truck drivers. We only know the hours

reported by general work location, not by task,

job title, equipment operated, or any other more

specific characteristics of exposure.

Accident Categories

A more detailed picture of haulage truck

accidents emerges by looking at the MSHA

categories into which they fall (figure 5).

Nature of injury. The “nature of injury”

reported for haulage truck fatalities was

predominantly “multiple injuries” (64 fatalities)

or “crushing” (34) (Figure 5, top left). The

nature of lost-time injuries was somewhat

different (figure 5, top right). Sprains and

strains were the largest category (2,437

injuries), consistent with Aldinger, Kenney, and

Keran’s reports of jarring as the main accident

type.

Body part injured. Haulage truck fatalities

tend to be catastrophic, involving serious

damage to multiple body parts (figure 5, center

left). Lost-time injuries (figure 5, center right)
0 10 20 30 40 50 60 70

Fatalities

Multiple injuries

Crushing

Fracture, chip

Asphyxia, drowning, etc.

Burn or scald

Amputation or enucleation

Concussion

Electric shock

Heart attack

Other

0 500 1000150020002500

Lost-time Injuries

Sprain, strains

Multiple injuries

Contusion, bruise

Fracture, chip

Unclassified, not determined

Cut, laceration, puncture

Other injury, NEC

Burn or scald (heat)

Dislocation

Dust in eyes

Other/unknown

0 350 700 1050 1400

Lost-time Injuries

Back

Multiple parts

Knee

Finger(s)

Ankle

Neck

Shoulder(s)

Hips

Chest

Trunk, multiple

Other/unknown

0 10 20 30 40 50 60 70 80 90

Fatalities

Multiple parts

Head, NEC

Body systems

Chest

Skull

Trunk, multiple

Brain

Head, multiple

Neck

Lower leg

0 500 1000150020002500

Lost-time Injuries

Operating haulage truck

Get on or off equip.

Machine maint./repair

Handling material

Escaping a hazard

Hand tools

Idle

Inspect equipment

Walking/running

Operating LHD

Other/unknown

0 10 20 30 40 50 60 70

Fatalities

Operating haulage truck

Machine maint./repair

Walking/running

Get on or off equip.

Escaping a hazard

Handling material

Hand tools

Observe operations

Operating utility truck

Couple/uncouple car

Other/unknown

Nature of Injury

Body Part Injured

Activity

Figure 5. Haulage truck fatality and lost-time injury categories: Nature of injury, body part injured, and victim’s activity,

1986-95.

most often involve the back (1,511) or multiple

parts (959), which is again consistent with the

jarring scenario.

Victim’s activity. The most common

activity recorded for victims of fatal haulage

truck accidents was operating the truck (61)

followed by maintenance (12), walking or

running (9) and getting on or off the machine
1-10 11-20 21-50 51-100 Over 100

Mine Size (number of employees)

0

1

2

3

4

5

Lost-time injuries

per 200,000 employee-hours

3.75

4.12 4.13

3.59

2.55

0.24 0.31 0.43 0.46 0.30

Legend

Overall

Haulage trucks

1-10 11-20 21-50 51-100 Over 100

Mine Size (number of employees)

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

Fatalities per 200,000 employee-hours

.0357

.0297

.0136

.0349

.0162

.0032

.0083

.0015

.0058

.0081

Legend

Overall

Haulage trucks

Figure 6. Fatality and lost-time injury rates for different

surface mine sizes, 1993-95.

(6) (figure 5, bottom left). Operating the truck

was also the largest lost-time category (2,447

injuries) followed by “get on or off equipment”

(1,489), maintenance (547), and handling

supplies or material (331) (figure 5, bottom

right). These categories are roughly consistent

with the findings of Aldinger, Kenney, and

Keran (1995) despite differences in methods

and data.

Mine Size

Small mines differ from large mines in

important ways, including different geology,

fewer resources, and the special problems

confronted by all small businesses. A common

perception in the mining community is that

small mines, at least partially because of the

factors listed above, are less safe than larger

operations. Recent analyses of accident rates at

different sizes of underground coal mining

operations (Peters and Fotta, 1994) showed that

small mines had a higher fatality rate than large

mines. However, there was no consistent

pattern of higher nonfatal injury rates at smaller

mines. Less has been reported about the

relationship between mine size and safety at

surface mines.

This analysis differs from the preceding

breakdowns of surface truck accidents in

several key ways. Because it examines the

characteristics of mining operations as a

possible factor in haulage safety, the analysis

had to be restricted to surface mines only,

excluding the surface operations of

underground mines as well as preparation

plants and mills. It also excludes independent

contractors because the hours worked by these

employees are reported by the contract

company and cannot be attributed to any

particular size of mining operation. This

analysis used data from just a 3-year period to

minimize the problems of a constantly

changing population of mining operations. The

accidents were broken down into five minesize groupings: 1-10 employees, 11-20, 21-50,

51-100, and over 100. There are very many

small surface mining operations -- the median

mine size is just four employees.

Figure 6 shows the normalized rates (per

200,000 employee-hours) for surface mine

fatalities and lost time injuries. The graphs

show both the overall rates as well as the rates

for haulage trucks alone. The rates are not

clearly higher for the smallest mines. The

overall fatality rate for 1-10 employee mines

(0.0357) was almost the same as that for 51-

100 employee mines (0.0349). For haulage

trucks only, the rate for 11-20 employee mines

(0.0083) was the highest by a very small margin

over the over-100 employee mines (0.0081). 

The numbers of fatalities upon which these

rates are based were very small, ranging from

just one haulage truck death for 21-50

employee mines during 1993-95 to eight

fatalities at mines with over 100 employees. 

Because lost-time injuries occur in much higher

numbers, they can be more useful than fatalities

for identifying stable overall trends.
The lost-time rates shown in figure 6

reveal that the highest rates are for the middlesized mines. The 11-20 employee and 21-50

employee mines have the highest overall rates

of 4.12 and 4.13. The peak for haulage truck

lost-time injuries is also in the mid-range, but

farther along the mine size continuum at 51-

100 employees (rate: 0.46). Again, there is no

clear trend toward higher rates as mine size

decreases.

CONTINUING RESEARCH

In 1995, the USBM laid out new initiatives

for improving surface haulage safety based on a

history of research (May and Aldinger, 1995). 

Although the USBM was abolished by

Congress in 1996, the health and safety

research functions in Pittsburgh, Pennsylvania

and Spokane, Washington were continued. 

The surface mining hazard reduction project,

formerly conducted out of the USBM's

Minneapolis, Minnesota center, is continuing in

Spokane. The project, "Hazard Reduction for

Surface Mining", is continuing to build on past

accomplishments while re-focusing future

goals to meet the needs of the newly formed

health and safety research centers. The

objective for the project is to reduce accidents

and injuries associated with coal and

metal/nonmetal surface mining. Several

strategies are being investigated, including

improved operating practices, hazard

recognition, and safety and warning devices.

Equipment manufacturers are working to

incorporate alarms, improve vision, and

improve ergonomics on large equipment. 

Other approaches involve the development of

remote-controlled or autonomous vehicles for

specific extremely hazardous or repetitive,

simple tasks. Improvements in sensing

technology such as GPS, radar, laser, and

infrared offer an opportunity to introduce these

technological improvements as an aid to

vehicle operation and/or control. 

Currently the efforts for the Hazard

Reduction for Surface Mining project are

aimed at:

C Safety Analyses. This will review

MSHA accident data to determine root

causes of recorded accidents. For

example, slips and falls from powered

equipment are a major cause of injuries. 

But in evaluating the accident

narratives, nearly half the slips and falls

are affiliated with jumping from a

vehicle or conveyor. Of those jumping,

over half were from vehicles which had

lost power or brakes. This analysis will

help identify operating practices that

should be modified or avoided to

improve safety.

C Early Warning. Existing and

developing sensing technology will be

reviewed to determine what systems

might be easily incorporated onto

existing equipment or into current

operations to provide warning to

operators and others in the immediate

proximity. Currently, engine

performance (rpm, oil pressure) and

machine operating conditions (speed,

tilt, load) will be reviewed as possible

parameters that could be used or

recorded to define machine operating

safety. In addition, geotechnical

sensing devices, laser surveying, slope

monitoring, proximity warning and

optical sensing devices will be

investigated to determine the potential

of short- and long-term applications that

might be used to improve equipment

operating safety.

C Operator Safety. Methods to minimize

injury to operators during accidents will

be investigated. Previous research on

vibration testing done by TCRC will be

continued to define and isolate elements

that could lessen shock loads to the

operator. Methods to promote seatbelt

use will also be investigated.
C Human Factors. Work will continue to

be coordinated with the Human Factors

section at PRC to develop effective

training and ergonomic support designs

for small- to medium-sized coal and

metal/nonmetal surface mining

operations. In addition, this task will

involve investigations of the

psychological and physiological factors

of reducing operator-induced accidents.

CONCLUSIONS

There is sufficient evidence from a variety

of studies, including the data presented here, to

identify several key problem areas in surface

haulage truck usage. These include:

C Driver fatalities involving loss of

vehicle control. These accidents can be

addressed though a combination of

solutions, including haulage roads with

less-steep grades, better signs, and

longer sight lines. Also, driver

visibility can be improved through

mirrors, video cameras, and cab design. 

Drivers can be educated about keeping

their equipment within controllable

limits. Finally, seatbelt usage should be

promoted for those times when loss of

control cannot be averted.

C Strains and sprains from rough roads,

and the shocks of loading or unloading.

Road maintenance can smooth out

washboarding and other types of

bumps. Loading and unloading

techniques, such as lining the truck bed

with small material before loading large

boulders, can reduce shocks. Also,

suspensions can be used to dampen the

transmitted shocks.

C Strains and sprains resulting from a

slip or fall while mounting or

dismounting the truck. Improved

railings, non-skid surfaces, and damageresistant ladders are some of the ways

of helping drivers to mount and

dismount their vehicles safely.

Despite the range of data presented here,

there are still many unanswered questions to

pursue:

C How often are seatbelts used, and how

can usage be increased?

C How many truck drivers are in the

mining workforce, and how many of

them are contractors? Do any of these

groups have a disproportionate number

of accidents?

C What range of truck sizes are in use. 

Are some types of accidents more likely

for different-sized trucks?

C What haulage safety problems will be

solved by automation? What new

hazards will be created?

C How can the existing information on

improving haulage safety be

communicated more effectively?

These issues, and others that will emerge from

more detailed analysis planned during the next

year, will guide the development of tools and

strategies for improving haulage truck safety. 

REFERENCES

Aldinger, J.A., and C.M. Keran. 1994 “A

Review of Accidents During Surface Mine

Mobile Equipment Operations” Paper in

Proceedings of 25th Annual Institute on Mining

Health, Safety and Research, pp. 99-108.

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

1995 “Mobile Equipment Accidents in Surface

Coal Mines” USBM IC 9428, 51 pp.

DiCanio, D. G., and A. H. Nakata. 1976

“Accident Cost Indicator Model to Estimate

Costs to Industry and Society From

Work-Related Injuries and Deaths in

Underground Coal Mining, Volume I. 

Development and Application of Cost Model”

(contract JO255031, FMC Corp.). BuMines

OFR 39(1)-77, NTIS PB 264 438. 202 pp.

May, J.P., and J.A. Aldinger. 1995 “Overview

of Bureau Research Directed Towards Surface
Powered Haulage Safety” Paper in Proceedings

of 26th Annual Institute on Mining Health,

Safety and Research, pp. 121-131.

Peters, R.H., and B. Fotta. 1994 "Statistical

Profile of Accidents at Small Underground

Coal Mines" Paper in Improving Safety and

Small Underground Mines, Proceedings: 

Bureau of Mines Technology Transfer

Seminar, Compiled by R. H. Peters. USBM SP

18-94, pp. 5-14.

Randolph, R.F. 1992 “Human Factors of High

Technology Mining” Paper in Proceedings of

the Symposium on New Technology in Mine

Health and Safety at the Annual Meeting of the

Society of Mining, Metallurgy, and

Exploration, Inc., Phoenix, AZ, pp. 287-295.

Sanders, M.S., and B.E. Shaw. 1988 

"Research to Determine the Contribution of

System Factors in the Occurrence of

Underground Injury Accidents” (contract

JO348042, Essex, Corp.). USBM OFR 26-89,

NTIS PB 89-219638/AS, 165 pp.

Weaver, R. J., and R.G. Llewellyn, 1986

“Report on 30 CFR Part 50" MSHA PC-7014,

49 pp.