构建全自动驾驶的挑战;重点是重型商用车
Challenges in Architecting Fully Automated Driving; with an Emphasis on Heavy Commercial Vehicles
摘要：
全自动驾驶汽车将需要新的感知、导航和决策功能--自动驾驶智能（ADI）。我们考虑这些功能的架构案例，并研究它们如何与传统平台集成。这些案例包括从机器人取代驾驶员--完全重复使用现有的车辆平台，到全新的设计。以重型商用车（HCV）为重点，我们从业务、安全性、可靠性、验证和实现的角度对这些案例进行评估。本文的原创贡献是对建筑案例本身的分类和随后的分析。分析表明，尽管车辆平台的完全重用很有吸引力，但它需要明确处理遗留平台的意外复杂性，包括在ADI中添加相应的诊断和错误处理。平台目前的自动防故障设计也将限制可用性。允许对平台进行更改，将使设计和故障操作行为更加优化，但需要更高的初始开发成本，并特别强调分区和控制，以限制安全要求的影响。在所有情况下，ADI的设计和验证都将带来巨大的挑战，并与包括安全标准在内的监管框架的演变有关。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
