Professional truck drivers are an essential
part of transportation in keeping the global economy alive and commercial
products moving. In order to increase productivity and improve safety, an
increasing amount of automation is implemented in modern trucks. Transition to
automated heavy good vehicles is intended to make trucks accident-free and, on
the other hand, more comfortable to drive. This motivates the automotive
industry to bring more embedded ICT into their vehicles in the future. An
avenue towards autonomous vehicles requires robust environmental perception and
driver monitoring technologies to be introduced. This is the main motivation behind
the DESERVE project. This is the study of sensor technology trials in order to
minimize blind spots around the truck and, on the other hand, keep the driver’s
vigilance at a sufficiently high level. The outcomes are two innovative truck
demonstrations: one R & D study for bringing equipment to production in the
future and one implementation to the driver training vehicle. The earlier
experiments include both driver monitoring technology which works at a 60% - 80%
accuracy level and environment perception (stereo and thermal cameras) whose
performance rates are 70% - 100%. The results are not sufficient for autonomous
vehicles, but are a step forward, since they are in-line even if moved from the
lab to real automotive implementations.
Cite this paper
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