梳理自动驾驶安全开发中快速迭代的挑战与对策
The DevSafeOps Dilemma: A Systematic Literature Review on Rapidity in Safe Autonomous Driving Development and Operation
- 系统综述现有文献，分析DevOps在自动驾驶中的应用
- 发现安全验证、持续监控等仍是关键难题
- 适合关注AI安全开发流程的研究者和工程师
自动驾驶系统开发因系统复杂性及安全性要求而极具挑战。广泛采用的DevOps模式有望支持AI技术的持续进步，并快速响应事故，实现持续开发、部署与监控。本文通过系统性文献综述，识别、分析并综合了与自动驾驶开发中使用DevOps相关的一系列现有研究。结果提供了一个关于将DevOps应用于安全相关AI功能时所面临挑战与解决方案的结构化概述。研究指出，要实现自动驾驶系统的安全DevOps，仍存在多个待解决的关键问题。
原文摘要 · Abstract (English)
Developing autonomous driving (AD) systems is challenging due to the complexity of the systems and the need to assure their safe and reliable operation. The widely adopted approach of DevOps seems promising to support the continuous technological progress in AI and the demand for fast reaction to incidents, which necessitate continuous development, deployment, and monitoring. We present a systematic literature review meant to identify, analyse, and synthesise a broad range of existing literature related to usage of DevOps in autonomous driving development. Our results provide a structured overview of challenges and solutions, arising from applying DevOps to safety-related AI-enabled functions. Our results indicate that there are still several open topics to be addressed to enable safe DevOps for the development of safe AD.
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