Systems, Man & Cybernetics - July 2016 - 9

(a)

(b)

(c)

(d)

Figure 2. the UmS is the ultimate HmI. Complete immersion is possible through the use of (a)-(b) integrated

haptic vehicle controls, (c) a high-resolution display, and (d) a complete 36-camera motion capture and
tracking system.

compensator-based MCAs, and
a dv a nced evolut ion a r y a lgo The provided washout
r it h m s -ba sed MCA s, such a s
MCAs based on the cuckoo algofilters by IISRI's
rithm, genetic algorithm, and parresearchers eliminate
ticle swarm optimization (e.g.,
Introducing a Framework
simulator sickness
[1]-[5]). Their recent findings,
IISRI proposed a framework for
which a re the most accurate
researching, developing, and testand maximize motion
mathematical model of human
ing novel MCAs on UMS based on
fidelity through
sen sat ion s, i nclud i ng hu ma n
the research team's past promising
threshold, are taken into account
works in the field of motion simuefficient use of the
in the provided algorithms for
lation, artificial intelligence, and
platform workspace
m i n i m izi ng hu ma n sensat ion
robotics. A number of advanced
within limitations.
errors between real and simulatcomputational-intelligence-based
ed driving tasks. By exploiting the
MCAs have been developed and
advantages of advanced computaimplemented to remedy critical
tional-intelligence-based MCAs, a
drawbacks and disadvantages of
new framework for motion cueing is formulated to greatmotion-based driving simulators (e.g., suboptimal tunly improve the physical limits of the restitution platforms
ing process, inefficient usage of platform workspace,
and enhance motion simulator fidelity.
lack of considering multiple human sensation-related
During a UMS driving scenario, several physiological
factors and sensation shape tracking, unrealistic
signals, including electrocardiogram (heart frequency),
motions, and simulator sickness) and to provide users
electrodermal activity (skin resistance, potential, and
with the most realistic driving experience in a virtual
temperature), and 32/64 channel EEG signals can be
vehicle. The advanced computational-intelligence-based
recorded using sensors or electrodes placed on the drivMCAs provided by IISRI's researchers include a range
er's hand, chest, and head to assess his motion sickness
of innovative adaptive fuzzy-based MCAs, optimal
realistically emulate the driving
experience of a range of land, air,
sea, and outer space vehicles without eliciting simulator sickness.

Ju ly 2016

IEEE SyStEmS, man, & CybErnEtICS magazInE

9



Table of Contents for the Digital Edition of Systems, Man & Cybernetics - July 2016

Systems, Man & Cybernetics - July 2016 - Cover1
Systems, Man & Cybernetics - July 2016 - Cover2
Systems, Man & Cybernetics - July 2016 - 1
Systems, Man & Cybernetics - July 2016 - 2
Systems, Man & Cybernetics - July 2016 - 3
Systems, Man & Cybernetics - July 2016 - 4
Systems, Man & Cybernetics - July 2016 - 5
Systems, Man & Cybernetics - July 2016 - 6
Systems, Man & Cybernetics - July 2016 - 7
Systems, Man & Cybernetics - July 2016 - 8
Systems, Man & Cybernetics - July 2016 - 9
Systems, Man & Cybernetics - July 2016 - 10
Systems, Man & Cybernetics - July 2016 - 11
Systems, Man & Cybernetics - July 2016 - 12
Systems, Man & Cybernetics - July 2016 - 13
Systems, Man & Cybernetics - July 2016 - 14
Systems, Man & Cybernetics - July 2016 - 15
Systems, Man & Cybernetics - July 2016 - 16
Systems, Man & Cybernetics - July 2016 - 17
Systems, Man & Cybernetics - July 2016 - 18
Systems, Man & Cybernetics - July 2016 - 19
Systems, Man & Cybernetics - July 2016 - 20
Systems, Man & Cybernetics - July 2016 - 21
Systems, Man & Cybernetics - July 2016 - 22
Systems, Man & Cybernetics - July 2016 - 23
Systems, Man & Cybernetics - July 2016 - 24
Systems, Man & Cybernetics - July 2016 - Cover3
Systems, Man & Cybernetics - July 2016 - Cover4
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