PRODUCTS & SERVICES
STONERIDGE-ORLACO
55
Detecting people and objects
AUTONOMOUS VEHICLES WILL PLAY A MAJOR ROLE IN THE CONSTRUCTION
SITE OF THE FUTURE – AND ADVANCED CAMERA SYSTEMS WILL BE ESSENTIAL
TO THEIR SAFE FUNCTIONING
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iVTInternational.com November 2019
Most accidents at construction sites or mines are
caused by not having an adequate view of the
surrounding area. Construction machinery can be
extremely large, so in many cases operators do not have
a complete field of vision around the vehicle. Factor in
excessive time pressure or a tired operator and the risk
of accidents only increases. Using a camera monitor
system that can detect objects and people can eliminate
this risk. A camera makes the operator’s job easier,
increases the field of view and prevents both accidents
and damage to machinery.
From automation to autonomy
Stoneridge-Orlaco, one of the market leaders in the field
of camera and monitoring systems for commercial and
industrial vehicles, believes that the role of vision solutions
is shifting, from accessories to essential safety components
for vehicles and machinery. This development is aimed not
only at increasing productivity but also at enhancing
safety. Automation has led to reduced production costs
across multiple sectors in recent decades and is now
considered indispensable. Despite these advances, people
remain an important yet essentially fallible element —
some 90% of accidents are the result of human error.
Self-driving vehicles can help prevent accidents, and
therefore injury and damage. After many years focused
on achieving automation the industry is moving towards
the advent of autonomous vehicles. Autonomous
construction vehicles are more productive than
machinery operated by people. Dump trucks or
excavators can be operated 24x7 with the end result
that construction projects are completed quicker. Such
vehicles increase safety and reduce costs as operators
are no longer required.
Camera key role
Cameras are essential to the development of
autonomous vehicles, and advances in artificial
intelligence mean that they are constantly improving. If
the right parameters and algorithms are applied,
cameras are able to recognize patterns and initiate
actions accordingly. As a result, it is possible for a vehicle
to brake, excavate and dump its load fully independently.
While radars and sensors can detect obstacles, smart
cameras are able to verify and classify those obstacles,
even in the case of moving objects such as people.
Cameras on and around the vehicle monitor the area
constantly in order to detect people in the vicinity.
Cameras are able to “see” depth by comparing successive
frames and can then use algorithms to detect people
and construction materials. With intelligent features
such as these, cameras are now much more than just
passive recording devices — they are proactive
detection systems. A camera is therefore an
indispensable part of a future in which operators can
access images and data remotely and will no longer be
needed on construction sites. However, as cameras are
optical systems that can struggle in dark or rainy
conditions, a camera on its own is not enough. Fully
autonomous vehicles also depend on various other
technologies such as sensors, 5G and wi-fi, GPS,
lidar and radar.
Packed with sensors
An autonomous vehicle requires a whole host of sensors
to ensure that the entire area around the vehicle can be
captured. GPS pinpoints the location, 5G and Wi-Fi allow
vehicles to communicate with each other, lidar and radar
detect objects, and cameras map the surrounding area.
With all these intelligent technologies at work, vehicles
are able to respond much more quickly in an emergency
than people, independently taking action within
milliseconds to prevent accidents. Autonomous
excavators and dump trucks fitted with this smart
equipment can therefore enhance safety and increase
productivity on major infrastructure projects and large
mining operations. iVT
Author: Thieme Wels, Stoneridge-Orlaco
Cameras on a vehicle
can monitor the area
for movement
/pivt
/iVTInternational.com
