Enabling unit testing of already-integrated AI software systems: The case of Apollo for autonomous driving

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hdl:2117/353609
Document typeConference report
Defense date2021
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
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ProjectUP2DATE - Intelligent software-UPDATE technologies for safe and secure mixed-criticality and high performance cyber physical systems (EC-H2020-871465)
SuPerCom - Sustainable Performance for High-Performance Embedded Computing Systems (EC-H2020-772773)
SuPerCom - Sustainable Performance for High-Performance Embedded Computing Systems (EC-H2020-772773)
Abstract
The advanced AI-based software used for autonomous driving comprises multiple highly-coupled modules that are data and control dependent. Deploying those already-integrated software frameworks makes unit testing, a fundamental step in the validation process of critical software, very challenging in safety-critical systems. To tackle this issue, in this paper, we show the steps we followed to develop standalone versions of the modules in an industry-level autonomous driving framework (Apollo) by applying several modifications to its architectural design. We show how the standalone modules have the same functional behavior as their integrated counterpart modules. We exemplify the benefits of standalone modules by performing incremental analysis of the software timing requirements of each module running on a heterogeneous System on Chip (SoC). This is a mandatory step to consolidate and integrate software modules guaranteeing timing constraints (e.g. related to freedom from interference) while maximizing SoC utilization.
CitationAlcón, M. [et al.]. Enabling unit testing of already-integrated AI software systems: The case of Apollo for autonomous driving. A: Euromicro Conference on Digital System Design. "2021 24th Euromicro Conference on Digital System Design, DSD 2021: virtual conference, 1-3 September 2021: proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2021, p. 426-433. ISBN 978-1-6654-2703-6. DOI 10.1109/DSD53832.2021.00071.
ISBN978-1-6654-2703-6
Publisher versionhttps://ieeexplore.ieee.org/document/9556323
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