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Toward an Automated Scenario-Based X-in-the-Loop Testing Framework for Connected and Automated Vehicles
Journal Article
12-05-04-0030
ISSN: 2574-0741, e-ISSN: 2574-075X
Sector:
Citation:
Kyriakopoulos, I., Jaworski, P., and Edwards, T., "Toward an Automated Scenario-Based X-in-the-Loop Testing Framework for Connected and Automated Vehicles," SAE Intl. J CAV 5(4):381-391, 2022, https://doi.org/10.4271/12-05-04-0030.
Language:
English
Abstract:
Emerging technologies for connected and automated vehicles (CAVs) are rapidly
advancing, and there is an incremental adoption of partial automation systems in
existing vehicles. Nevertheless, there are still significant barriers before
fully or highly automated vehicles can enter mass production and appear on
public roads. These are not only associated with the need to ensure their safe
and efficient operation but also with cost and delivery time constraints. A key
challenge lies in the testing and validation (T&V) requirements of CAVs,
which are expected to be significantly higher than those of traditional and
partially automated vehicles. Promising methodologies that can be used toward
this goal are scenario-based (SBT) and X-in-the-Loop (XiL) testing. At the same
time, complex techniques such as co-simulation and mixed-reality simulation
could also provide significant benefits. Nevertheless, the benefits of
individual solutions are likely to be significantly smaller, if considered in
isolation without any supporting test automation methods. This article attempts
to combine existing knowledge and state of the art to explore the development of
a framework for automating the T&V needs of CAVs. To this end, the
integration of the VeriCAV framework for automating SBT with the Digital CAV
Proving Ground Feasibility Study (DigiCAV) XiL mixed-reality CAV development and
evaluation platform has been explored. The goal of the new framework is to
enable an iterative and incremental approach across all stages of CAV
development through the combination of optimal scenario generation and a
comprehensive XiL scenario execution environment. This article presents an
overview of the new framework as well as preliminary proof of concept
results.
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