ADVANCES IN PROXIMITY DETECTION TECHNOLOGIES FOR SURFACE MINING EQUIPMENT 

Todd M. Ruff, P.E. 

Electrical Engineer 

National Institute for Occupational Safety and Health 

INTRODUCTION 

The lack of visibility near earthmoving equipment 

resulted in six fatalities in U.S. surface mining 

operations during 2003. These accidents were the 

result of either a piece of equipment striking another 

vehicle or worker, or the equipment traveling over the 

edge of an embankment. Figure 1 is an example of a 

recent accident that resulted in serious injuries to one 

worker and fatal injuries to two others when a van 

parked in front of a haul truck. Two fatalities occurred 

in separate incidents when front-end loaders struck 

workers. Another two workers were killed when their 

equipment backed over the edge of a highwall or 

dump point [1]. There is clearly a need to provide 

better information to equipment operators regarding 

their surroundings. 

 

Figure 1. Accident involving collision between offhighway dump truck and van. 

Researchers at the National Institute for 

Occupational Safety and Health (NIOSH), Spokane 

Research Laboratory, are working to reduce these 

accidents by developing systems that sense obstacles 

and changes in terrain near the equipment and provide 

this information to the operator. Many off-the-shelf 

proximity warning systems that were developed for 

automobiles, light trucks, and recreational vehicles 

were evaluated on off-highway dump trucks [2]. 

Many limitations were found with existing systems, 

including frequent false alarms, limited detection 

range, a lack of specific information on an obstacle 

(e.g., location, identity), difficulties in finding suitable 

mounting locations, and an inability to withstand the 

environment. These limitations have necessitated the 

development of new systems designed specifically for 

large, off-highway, earthmoving equipment. New offthe-shelf systems available for mining equipment 

include radar and tag-based detection systems. 

Prototype systems now being developed include a 

proximity warning system based on the Global 

Positioning System (GPS) and a computer-assisted 

stereovision system. Development of these new 

systems was accomplished by working with 

manufacturers to modify existing systems to meet the 

needs of surface mining and through cooperative 

research with organizations to develop completely new 

solutions. 

 A typical proximity warning system consists of a 

sensor or antenna mounted on the equipment that 

detects the presence of obstacles and an alarm 

interface in the cab of the equipment. Some systems, 

as described in more detail below, also require that 

other vehicles and personnel on the ground be outfitted 

with electronic tags that transmit an “I’m here” signal 

back to the system (e.g., radio signal detection systems 

or GPS). Many types of proximity warning systems 

are on the market, but they are not all discussed in this 

paper. 

APPROACH 

 In past work, engineers at NIOSH evaluated several 

off-the-shelf proximity warning technologies in order 

to verify their effectiveness on off-highway dump 

trucks [2]. Dump trucks were chosen because of the 

number and severity of accidents involving this type of 

equipment and because extensive blind areas around 

these trucks are typical. This experience allowed 

engineers to limit the number of systems chosen for 

long-term tests at mine sites to those systems showing 
the best potential for success. Even so, field tests 

quickly revealed shortcomings, and work with 

manufacturers was initiated to modify the systems. At 

the same time, new technologies were investigated to 

meet the specific requirements of surface mining 

equipment and mine environments. 

Initial tests were conducted using a 50-ton-capacity, 

off-highway dump truck. It was critical to test each 

system on an actual piece of equipment because of the 

variability seen in performance depending on where 

the system was mounted on the truck and the actual 

environment. These short tests were used to analyze 

how well each system detected a person and a 

passenger vehicle (pickup), which are commonly 

involved in accidents. The tests involved temporarily 

mounting the proximity warning system on the rear of 

the truck near the top of the axle, then backing slowly 

toward a stationary person or a pickup. The detection 

zone was recorded for each test object and analyzed to 

determine if the zone was adequate to help avoid a 

collision. The frequency of false alarms was also 

observed by backing the truck up in a clear, flat area. 

For detailed information on test procedures, see SAE 

standard J1741 entitled “Discriminating Backup 

Alarm System Standard,” and the NIOSH procedures 

in reference [2]. 

After the initial tests were completed, researchers 

chose the most promising systems for tests at a mine 

site. A cooperative agreement with Phelps Dodge 

Morenci, Inc., Morenci, AZ, was established that 

allowed NIOSH and system manufacturers to test 

systems on Caterpillar model 793 and 797 dump 

trucks used in mine production. On some trucks, 

evaluation forms were given to the truck drivers at the 

end of each shift, and they were asked to provide 

feedback on how the system was operating and if it 

was helpful. Researchers also collected performance 

data during direct observations, driver interviews, and 

by recording video footage of the blind area. 

RESULTS 

Preview Radar System 

 The Preview heavy-duty radar system1

 is 

manufactured by Preco Electronics, Boise, ID, and 

marketed for heavy equipment. The system uses 

pulsed radar to sense the presence of and determine 

 

1 Mention of specific products and manufacturers does not imply 

endorsement by the National Institute for Occupational Safety and Health.

the distance to an object in the radar beam. An alarm 

interface is mounted in the cab of the truck and has 

both audible and visual warnings. A series of LEDs 

light up in succession, and the warning tone changes 

frequency to indicate distance to an object. 

NIOSH tested the first generation of the Preview 

radar system on a Caterpillar 793B (260-ton-capacity) 

dump truck at Phelps Dodge Morenci, Inc. The 

maximum range of the system for detecting a standing 

person was 8.5 m (28 ft), but a person could not be 

detected near the rear tires because of the narrow radar 

beam pattern (dashed line in figure 2). It is important 

that the entire width of the truck be covered near the 

tires. For this reason, NIOSH researchers requested 

that the radar system be modified to provide a wider 

beam. Instead, Preco introduced a new networked 

version of the system that allows two antennas to be 

used for each alarm interface. This dual-antenna 

system is also programmable to customize the 

detection zone shape and distance for a particular 

piece of equipment. 

Figure 2. Comparison of detection zones for singleand dual-antenna Preview radar system. 

Figure 3 shows the new radar system mounted on 

the back of a Caterpillar 793B. Two antennas were 

mounted approximately 1.8 m (6 ft) apart on special 

brackets attached to the rear axle area. Caterpillar 
does not recommend welding objects directly onto the 

axle housing, so the brackets were attached using 

existing bolts. To achieve detection near the tires, the 

radar beams for each antenna were crossed slightly (an 

inward angle of approximately 20o

). A single alarm 

interface, which accepts information from both 

antennas, was mounted in the cab. The solid line in 

figure 2 shows the resulting detection zone for a 

person and indicates that detection near the tires 

improved. The detection zone for a vehicle was 

similar. 

Figure 3. Preview radar system with two antennas. 

Several methods were employed to evaluate this 

system while the truck was in use. (1) Comment 

forms that provided information on false alarms, 

system effectiveness, and other general observations 

were available for drivers to fill out at the end of each 

shift; (2) informal discussions with drivers provided 

researchers with more-detailed information; and (3) a 

VCR recorded video from a camera on the rear of the 

truck along with radar system alarms so that objects 

seen in the video footage could be correlated with 

alarm information. 

Tests of this radar system are in progress, but results 

so far have indicated the following: 

• The radar system was effective in detecting people 

and smaller vehicles behind the truck; 

• Occasional false alarms did occur, but not 

frequently enough to cause the system to be ignored. 

However, even infrequent false alarms made it evident 

that some method is needed to verify that no person or 

object was really in danger of being hit; 

• Nuisance alarms (alarms from objects that the driver 

was already aware of) did occur. Again, some method 

of verifying the cause of the alarm is needed. 

• After about 6 months of continuous use, one radar 

antenna failed due to vibration and had to be replaced. 

Based on these findings, it is recommended that 

radar or other sensing systems be used in combination 

with camera systems. The camera should provide a 

view of the area that the radar is monitoring so that 

radar alarms can be verified without the driver leaving 

the cab. At the same time, radar compliments cameras 

by providing an important alarming function that 

prompts the driver to check the video monitor so that 

the possibility of a collision does not go unnoticed. 

Electronic Tag-Based Systems 

 NIOSH has conducted short-term tests of systems 

that sense electronic tags worn by workers or mounted 

on other vehicles. These systems require a device on 

the truck that senses and communicates with the tags 

and an alarm interface in the cab. These systems 

operate in a very similar manner to radio-frequency 

identification (RFID) systems that are popular in 

security systems and asset tracking. 

 Two systems available for mining equipment have 

been tested so far: the Buddy System (Nautilus 

International, Burnaby, B.C., Canada) and the 

CAS/CAM system (Advanced Mining Technology 

[AMT], Chittaway Bay, NSW, Australia). Both 

systems were tested at NIOSH on a 50-ton-capacity 

off-highway dump truck. (The Nautilus system was 

also tested at Phelps Dodge Morenci on a 260-toncapacity truck, but NIOSH researchers were not 

present, and test results are available only from 

Nautilus.) 

 The Buddy System uses a loop antenna mounted on 

the truck to transmit a low-frequency electromagnetic 

signal that surrounds the entire truck. Electronic tags 

worn on the belt of workers or mounted on smaller 

vehicles sense this signal’s strength and send an alarm 

to the driver if the tag comes within a certain distance 

of the truck. An alarm can also be generated at the tag 

itself. Figure 4 shows the detection zone for a person 

wearing a tag. The area around an entire truck can be 

monitored with just one loop antenna, and the radius 

of the detection zone can be changed according to 

different equipment sizes and speeds. Multiple 

antennas can be used to monitor the front and back 

more equally and provide location information for a 

detected tag. 

The CAS/CAM system uses a higher-frequency 

signal and requires one transceiver mounted on the 

front of the truck and one on the back for complete 

coverage. At the time of the tests, no tag was 
available for personnel (due to tag size), so a pickup 

truck was outfitted with a tag. The results of the 

detection tests are shown in figure 5. The tag was 

detected out to 17.4 m (57 ft), and the width of the 

detection area was adequate to sense the pickup 

immediately next to the rear tires or front bumper. 

Figure 4. Detection zone for Nautilus Buddy system 

and person wearing tag. 

Figure 5. Detection zone for the CAS/CAM system 

with tag mounted on pickup truck. 

One advantage of electronic tag-based systems is the 

very low occurrence of false alarms. Only objects or 

personnel outfitted with tags can be detected. A driver 

can be very certain an alarm is cause for caution. A 

disadvantage is that the cost of these systems is higher 

when compared to radar because of the number of tags 

required and the additional communications systems 

needed. The use of tags also raises maintenance 

issues, but the increased functionality of such systems 

may help offset the added cost. The alarm interface 

for these systems does not provide an exact location 

for the person or object causing the alarm, so cameras 

may again be helpful. In fact, the manufacturers of 

both systems recommend the use of cameras on the 

truck as part of their respective overall systems. 

GPS-Based Proximity Warning System 

Many surface mines have GPS systems on their 

equipment for tracking, dispatch, and positioning. 

NIOSH researchers proposed that these systems be 

taken one step further to provide the safety function of 

proximity warning. This idea was based on the fact 

that the location of much of the equipment in a mine 

site is already known via on-board GPS. All that is 

needed is to get this information to the drivers of the 

equipment. Cooperative research was initiated 

between NIOSH and Trimble to develop a system 

based on the available GPS technology used in mines. 

The system was to provide proximity warning 

information to drivers for stationary objects (e.g., 

dump points, buildings, utility poles) and moving 

objects (e.g., other dump trucks, smaller vehicles). 

 The concept for GPS-based proximity warning 

sensors for mining equipment entails the use of 

differential GPS receivers and radios on all equipment 

having reduced visibility, all smaller vehicles on a 

mine site, and eventually all workers on foot. The 

location of all moving equipment and personnel must 

be determined and updated in real time, and this 

information must be transmitted to all nearby 

equipment so that the operators are aware of other 

vehicles or workers nearby. In addition, the location 

of stationary structures needs to be stored in a database 

of potential obstacles. An alarm interface in the cab is 

required to provide a visual and audible warning when 

another vehicle, worker, or stationary obstacle is 

within a preset danger zone around the equipment. 

 Development of a GPS-based proximity warning 

system by NIOSH and Trimble began in 2000. 

Prototypes were tested in an outdoor laboratory setting 
on passenger vehicles. Development continued over 

the next 2 years, resulting in a mine-ready system that 

was demonstrated at the Phelps Dodge Morenci 

copper mining operation in April of 2002 [3]. 

The mine-ready system consisted of the following 

Trimble components mounted on each piece of mobile 

equipment: a GPS antenna; a Windows CE-based 

computer with LCD display to run the proximity 

warning software; an eight-channel, single-frequency, 

differential GPS receiver (integrated into the computer 

enclosure); and a SiteNet 900-MHz Internet Protocol 

(IP) radio for peer-to-peer communication between 

equipment (see figure 6). All these components were 

designed for use on heavy equipment. Each system 

uses GPS to determine the equipment’s location. 

Differential correction information from a base station 

is used to correct the location. The corrected location 

is then transmitted once per second via the IP radio to 

all other mining equipment and smaller vehicles in the 

area. The locations of other vehicles are also received 

by the IP radio and shown on the computer’s display if 

they are within a specified range. The location of 

stationary obstacles, such as dump points, power lines, 

and mine buildings, does not have to be transmitted; 

instead, their coordinates can be entered into the 

system’s database so that they automatically show up 

on the vehicle’s display screen. 

 Figure 6. GPS system components. 

Tests of the system were conducted at Phelps Dodge 

Morenci. System components were installed on a 

Caterpillar 797 360-ton-capacity haul truck, a 

Caterpillar rubber-tired dozer, and two service trucks 

(pickups). A base station was also installed on a 

nearby hill to provide differential correction 

information. The computer in the cab of each vehicle 

(figure 7) contained a screen for the equipment 

operator that displayed his/her equipment in the center, 

the detection zone radius, the warning zone radius, 

system status, and icons representing other vehicles or 

stationary obstacles in the area. Audible alarms were 

generated whenever another vehicle or stationary 

obstacle was detected in either zone. Also, the color 

of another vehicle’s icon changed from green (outside 

both zones), to yellow (inside detection zone), to red 

(inside warning zone) as it approached the center of 

the screen. 

Figure 7. Driver interface for GPS-based proximity 

warning system. 

Each system successfully tracked three other mobile 

vehicles and six stationary obstacles. Expected 

accuracy of the position of a vehicle or obstacle shown 

on the system display was 2 to 5 m (6 to 16 ft) using 

the computer’s internal receiver with differential 

correction. Accuracy depended on many factors, 

including satellite position (positional dilution of 

precision [PDOP]), multipath interference, the status 

of “selective availability” (SA), and the type of GPS 

receiver used, to name a few. Observed accuracy was 

2 to 3 m (6 to 10 ft) during the tests. Greater position 

accuracies could be obtained using higher-quality GPS 

receivers.

For a mine-wide, GPS-based, proximity warning 

system to be effective, all vehicles, mining equipment, 

and workers on a mine property would need to be 

outfitted with a system. Functionality and cost of each 

system could vary with each type of vehicle. For 

instance, service trucks and contractor vehicles could 

be outfitted with a simple system that would not 

require the current computer and display set-up. Such 

a system could use an off-the-shelf GPS antenna and 

receiver, a low-cost processor, and an IP radio all 

packaged in a single enclosure that attached quickly to 
the vehicle’s roof. A simple audible warning would be 

generated in the cab of the vehicle when another 

vehicle or piece of equipment was nearby. 

The reduced visibility associated with larger mining 

equipment would require a more expensive and more 

functional system. A graphics display would be 

needed to allow the operator to locate and identify 

nearby obstacles. The system could stand alone like 

the mine-ready system described here, or it could be 

integrated into existing dispatch and control systems. 

One obvious element missing from these tests is a 

system to protect a worker on foot. This would 

require a personal system that included miniature GPS 

equipment, a small processor, and IP radio equipment. 

The system would need to fit on the worker’s belt or a 

vest pocket. With the exception of SiteNet radios, 

hardware for a personal system is available. 

The preliminary tests at a surface mine showed that 

a GPS-based proximity warning system has the 

potential to significantly reduce accidents involving 

collisions or driving over an edge at surface mining 

operations. Future work will involve larger-scale and 

longer-term tests to prove this technology adequately. 

Also, several improvements need to be made to the 

proximity warning algorithms, such as the integration 

of dead-reckoning methods and the ability to use 

pseudolite (ground-based GPS transmitter) signals 

when needed. The ability to protect workers on the 

ground will be the final element needed to complete 

this system. 

Computer-Assisted Stereo Vision 

As tests of the radar system showed, it would be 

beneficial to combine sensor technologies with 

cameras so that an alarm could prompt a driver to 

check the camera view. A new technology under 

development could integrate cameras and alarming 

into one system by using a computer to process video 

data from stereo cameras. Researchers at the Colorado 

School of Mines (CSM), Golden, CO, have developed 

a stereo imaging system as part of an automated ore 

loading system. Application of this system to the 

proximity warning problem in surface mines is being 

studied through a cooperative effort with NIOSH [4]. 

Figure 8 shows the principle behind calculating the 

distance to an object using stereo imaging. If an 

object is viewed by both cameras and camera 

parameters are known, then the distance to the object 

can be calculated from the disparity between the 

projected position of the object on the image planes. 

Note the difference between u1 and u2 in the figure. 

The distance to an object is calculated as─

( ) z fd

u u =

2 1 −

where z = distance to the object, 

 f = distance from lens to imaging plane, 

 d = distance between lenses, 

u1 = projected position of object on image 

plane 1, 

 and u2 = projected position of object on image 

plane 2. 

Figure 8. Geometry of stereo imaging and distance 

calculation. 

The prototype system being developed consists of a 

stereo camera head attached to a laptop computer via a 

Firewire (IEEE 1394) interface. A pair of images is 

captured from each camera and stored on the 

computer. To find a feature within the images that is 

common to an image pair, intensity-based correlation 

is used. This requires pixel regions to be compared in 

both images along epipolar lines. When an intensity 

match is found for a particular region, then the 

disparity between the two regions can be calculated 

and converted to a distance. A statistical approach is 

used to calculate the distance to the ground plane. An 

object that stands above the ground plane by some 

preset distance would cause an alarm. For a more 

detailed description of the algorithm, see [6]. 

Figure 9 shows an image captured during a test at a 

quarry. The stereo cameras were mounted on the rear 

of an off-highway dump truck. The light-colored 

(green) boxes represent areas identified on the ground. 
The darker (red) boxes represent items that stood out 

from the ground and would cause an alarm. The 

pickup truck, people, and car in the background were 

correctly identified as objects that would cause an 

alarm. Other tests were conducted to see if the system 

would correctly detect a person or berm in the path of 

the truck. The results of these tests were promising. 

With the system described here, calculations on 

image pairs were done after video footage had been 

collected. Future work will involve modifications to 

the software for image capture, distance calculation, 

and alarming, with updates to be run one or two times 

per second. Other issues still need to be studied, such 

as the effects of camera vibration, lighting conditions, 

and hardware limitations. 

Figure 9. Captured image from one stereo camera 

with ground and alarm areas identified.

SUMMARY 

 Devices are available to help eliminate blind spots 

and associated accidents involving off-highway 

mining equipment. Camera systems and, more 

recently, radar and electronic tag-based systems 

designed specifically for heavy equipment are on the 

market. Successful implementation of these systems 

can be achieved if their advantages and shortcomings 

are realized and anticipated. Radar is effective in 

detecting people and small vehicles, but it is 

susceptible to false and nuisance alarms, thereby 

requiring a supplemental method, such as cameras, to 

verify the cause and exact location of the nearby 

object. Tag-based systems, while more expensive than 

radar, have the advantage of producing very few false 

alarms and may be configured for tag-in/tag-out 

functionality. Cameras can benefit from the addition 

of either of these sensor systems so that an equipment 

operator is prompted to check the video monitor 

before and during equipment movement. 

Novel approaches have also been taken to solve this 

problem, such as the use of GPS and a wireless 

network to transmit a vehicle’s location to all other 

vehicles in the area. This system is in the 

development stage, but shows promise for mines that 

already have a GPS infrastructure in place. Finally, a 

new system under development at the Colorado 

School of Mines uses computerized image processing 

and stereo cameras to detect the presence of workers, 

vehicles, or other obstacles. At the same time, the 

system provides a camera view of the equipment’s 

blind area to the operator. 

An ideal proximity warning system would provide 

detection of obstacles and workers anywhere near the 

mining equipment and provide the operator with 

information on the exact location, number of 

detections, and type of obstacle detected. False alarms 

with this system would be rare, and small rocks, ruts, 

or foliage in the roadway would not cause an alarm. 

The system’s detection zone would adjust in size and 

shape according to vehicle’s size and speed. And 

finally, the system would be robust enough to handle 

the vibration and shocks typical of mining equipment 

and the extreme environmental conditions found on 

mine sites. NIOSH researchers will continue to work 

toward these goals and promote the use of effective 

technologies in order to decrease collisions involving 

mining equipment. 

ACKNOWLEDGMENTS 

The author would like to thank Thomas Holden and 

his project team at Trimble for their work in the 

development of the GPS-based proximity warning 

system; Jim Hanson of Phelps Dodge Morenci and 

Nathan Lowe of NIOSH for their contributions in the 

planning and implementation of tests for the GPSbased system; and John Steele, Chris Debrunner, and 

Mark Whitehorn of the Colorado School of Mines for 

their efforts in modifying the stereo vision system for 

surface mines. 

REFERENCES 

[1] Mine Safety and Health Administration [2003]. 

Fatal alert bulletins, fatalgrams, and fatal 
investigation reports. Data files, available at 

http://www.msha.gov/fatals/fab.htm. 

[2] Ruff T. [2000]. Test results of collision warning 

systems for surface mining dump trucks. NIOSH 

Report of Investigations 9652, DHHS Publication 

No. 2000-120. 

[3] Ruff T., Holden T. [2003]. Preventing collisions 

involving surface mining equipment – A GPSbased approach. Journal of Safety Research 34: 

175-181. 

[4] Steele J., Debrunner C., Whitehorn M. [2003]. 

Stereo images for object detection in surface mine 

safety applications. Colorado School of Mines, 

Western Mining Resource Center Tech Report 

TR20030109.