Page 38 - TTG-Taiwan Transportation Equipment Guide (TTG)-2021-09 Edition

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Feature Topic
the necessary technology to detect sounds and
make on-time driving adjustments. The team ended
up developing a system that would detect alarm
sounds from emergency service vehicles, and
adjust the vehicle accordingly depending on the
direction where the sound was originating from.
The system is fed with sound frequency data to
learn the difference between emergency service
alarms or other sounds, wind noise reduction
technology, employing gpuRIR to set up sound
origin range and angle, allowing the system to
collect more sample data on sounds like vehicle
horns, braking noise and more.
Cheng Wen-huang, a Distinguished Professor
at the NYCU Institute of Electronics, told CENS
during an interview at the Taipei AMPA show while
exhibiting the Ministry of Science and Technology,
that they had considered the lack of solutions to
address sound detection quite strange and had
sought to resolve it. Initial development focused
on a single sound-origin detection method, and
now the team is focusing on multi-origin detection.
Based on preliminary indoor testing, the solution
could accurately pinpoint, detect, and distinguish
sounds from different directions and origin points.
The other is a deep-learning platform that
focuses on detecting road puddles and road
defects, such as potholes or bumps, developed by
Feng Chia University. The research team on this
project also worked closely with industry companies
to develop the system.
At the next-door pavilion, mobility Taiwan
Automotive Research Consortium (mTARC), an
entity under the Economic Ministry Department
of Industrial Technology, showcased EV and
self-driving vehicle technologies developed by
domestic companies and research institutions.
Among those technologies is the “Integrating
Simulation and Reality for Autonomous Driving
Function Verification,” developed by the Automotive
Research and Testing Center (ARTC).
The simulator sets up virtual scenarios and
simulates sensor model placements, powered by
PreScan, while the algorithms navigates through
the system. Other platforms include vehicle
dynamic models, driver control interfaces, real-time
simulating with I/O interface for communication with
real hardware, and six degrees of freedom motion.
ARTC has developed the simulator to work with
companies or R&D teams in each stage of the self-
driving vehicle development to verify technologies
on the car. This is because more and more
manufacturers are attempting to develop ADAS and
ADS, though lack a comprehensive environment
to verify the control algorithms. The simulator can
assist system suppliers to troubleshoot and improve
existing algorithms. Overall, development cycles
and costs could be reduced.