关于自动驾驶车辆资源受限平台持续试验的思考
Considerations about Continuous Experimentation for Resource-Constrained Platforms in Self-Driving Vehicles
摘要：
由于许多学术和工业组织的努力，自动驾驶汽车正在慢慢成为现实。由于为这些系统提供动力的软件的复杂性和开发过程的动态性，需要能够支持长期发展和维护的架构解决方案。持续实验（CE）是软件密集型基于Web的软件系统中越来越多地采用的实践，以随着时间的推移稳步改进它们。CE允许组织通过基于在其应用领域中收集的关于系统的数据来指导开发工作。尽管持续实验具有优势，但这种做法很少在网络物理系统和汽车领域中采用。其原因包括严格的安全约束和目标系统所需的计算能力。在这项工作中，概述了将连续实验用于资源受限平台（如自动驾驶车辆）的概念。
英文摘要：
Autonomous vehicles are slowly becoming reality thanks to the efforts of many academic and industrial organizations. Due to the complexity of the software powering these systems and the dynamicity of the development processes, an architectural solution capable of supporting long-term evolution and maintenance is required. Continuous Experimentation (CE) is an already increasingly adopted practice in software-intensive web-based software systems to steadily improve them over time. CE allows organizations to steer the development efforts by basing decisions on data collected about the system in its field of application. Despite the advantages of Continuous Experimentation, this practice is only rarely adopted in cyber-physical systems and in the automotive domain. Reasons for this include the strict safety constraints and the computational capabilities needed from the target systems. In this work, a concept for using Continuous Experimentation for resource-constrained platforms like a self-driving vehicle is outlined.
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。
