Challenges in Architecting Fully Automated Driving; with an Emphasis on Heavy Commercial Vehicles
This addresses the problem of designing safe and efficient automated driving systems for heavy commercial vehicles, but it is incremental as it builds on existing architectural analysis without introducing new methods.
The paper tackles the challenge of integrating Autonomous Driving Intelligence (ADI) into Heavy Commercial Vehicles by analyzing architectural cases from full reuse of legacy platforms to clean-slate designs, finding that full reuse requires handling legacy complexity and limits availability, while platform changes enable optimization but increase costs.
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 and error handling to the ADI. The current fail-safe design of the platform will also tend to limit availability. Allowing changes to the platforms, will enable more optimized designs and fault-operational behaviour, but will require initial higher development cost and specific emphasis on partitioning and control to limit the influences of safety requirements. For all cases, the design and verification of the ADI will pose a grand challenge and relate to the evolution of the regulatory framework including safety standards.