Autonomous Vehicle Engineering - May 2021 - 22
Artificial Intelligence/Machine Learning
"
We are focusing on the parts of full autonomy that can be commercialized
successfully today, leaving the parts that require further development
and validation for tomorrow.
NHTSA / ISO
University of Illinois at Urbana-Champaign
"
The purpose of the SOTIF analysis, performed using the ISO 21448 standard,
is to reduce the unknown unsafe scenarios.
Deep neural networks offer a nonlinear functional approximation with some hidden layers and unknown parameters
that link the inputs to outputs.
University of Illinois at Urbana-Champaign
AI = real-time optimization
For longer platoons, convolutional neural networks (CNN) can be used to
create a modular single-truck surrogate when the input layer is an image.
CNN is a machine-learning approach widely used in image classification,
segmentation and detection.
Based on the fault-tree analysis, systems with a
human-in-the-loop could benefit from safety mitigations, Svenson added. " Safety mitigation such
as training and operating procedures to assess the
workload of drivers in the vehicles, as well as how
and what type of information is conveyed, could be
beneficial for heavy-truck platooning systems. "
22 May 2021
Optimization of fuel consumption is critical for truck
platooning, but analysis of full-scale computational
fluid dynamics (CFD) simulations can be expensive
and time-consuming, according to Dr. Hadi Meidani,
assistant professor of civil and environmental engineering at the University of Illinois at UrbanaChampaign. Meidani shared research during a recent
Center for Connected and Automated Transportation
(CCAT) webinar that proposes an AI-based surrogate model to enable near real-time optimization of
platoon configurations.
" Platooning is really an optimization problem, "
Meidani said, noting that it is important to run multiple
simulations for various uncertainties. " To arrive at the
best platoon configuration, which essentially is determining the longitudinal spacing between trucks and
their lateral position, you need to run a CFD model
to quantify the drag force, " he explained. " They're not
easy problems to solve using finite elements, so you
typically need a full-scale high-fidelity simulation, and
that may take hours depending on how many trucks
you have and how many uncertain factors you want
to consider in your problem. "
The researchers propose using a surrogate, which
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Autonomous Vehicle Engineering - May 2021
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