Safety guarantees and regulatory approval for autonomous vehicles remain an ongoing challenge. In particular, software that is frequently adapted or contains complex, non-transparent components, such as artificial intelligence, is exceeding the limits of safety standards. This paper presents a detailed implementation of an online verification module - the Supervisor - that copes with these challenges. The presented implementation focuses on autonomous race vehicles without loss of generality. Following an identified holistic list of safety-relevant requirements for a trajectory, metrics are developed to monitor whether the trajectory can safely be executed. To evaluate safety with respect to dynamic objects in a semi-structured and highly dynamic racing environment, rule-based reachable sets are presented. As a result, the pure reachable set is further constrained by applicable regulations. Real-time capability and effectiveness are demonstrated in fault-injected scenario-based tests and on real-world run data. The implemented Supervisor will be publicly available on GitHub.

中文翻译：

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在线验证可批准自动赛车规划者的驾驶功能实施


自动驾驶汽车的安全保证和监管批准仍然是一个持续的挑战。特别是，经常修改或包含复杂、不透明组件（例如人工智能）的软件超出了安全标准的限制。本文介绍了应对这些挑战的在线验证模块（Supervisor）的详细实现。所提出的实现重点关注自动赛车，但不失一般性。根据确定的轨迹安全相关要求的整体列表，制定指标来监控轨迹是否可以安全执行。为了评估半结构化和高动态赛车环境中动态对象的安全性，提出了基于规则的可达集。因此，纯可达集进一步受到适用法规的限制。实时能力和有效性在基于故障注入场景的测试和实际运行数据中得到证明。实施的 Supervisor 将在 GitHub 上公开发布。