Challenges in Architecting Fully Automated Driving; with an Emphasis on Heavy Commercial Vehicles
Naveen Mohan, Martin T\"orngren, Viacheslav Izosimov, Viktor Kaznov,, Per Roos, Johan Svahn, Joakim Gustavsson, Damir Nesic

TL;DR
This paper analyzes architectural options for fully automated heavy commercial vehicles, emphasizing integration challenges with legacy systems, safety, and verification, and introduces a classification of these architectural cases.
Contribution
It classifies architectural cases for autonomous heavy commercial vehicles and analyzes their implications on safety, dependability, and integration with legacy platforms.
Findings
Full reuse of vehicle platforms increases complexity and safety challenges.
Allowing platform modifications enables better fault handling but raises development costs.
Design and verification of ADI pose significant challenges related to safety standards.
Abstract
Fully automated vehicles will require new functionalities for perception, navigation and decision making -- an Autonomous Driving Intelligence (ADI). We consider architectural cases for such functionalities and investigate how they integrate with legacy platforms. The cases range from a robot replacing the driver -- with entire reuse of existing vehicle platforms, to a clean-slate design. Focusing on Heavy Commercial Vehicles (HCVs), we assess these cases from the perspectives of business, safety, dependability, verification, and realization. The original contributions of this paper are the classification of the architectural cases themselves and the analysis that follows. The analysis reveals that although full reuse of vehicle platforms is appealing, it will require explicitly dealing with the accidental complexity of the legacy platforms, including adding corresponding diagnostics…
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