arXiv:2606.07067cs.RO2026-06中稿 · 2026 IEEE 29th Int…

为远程自动驾驶服务设计安全评估新标准,确保响应延迟下的行车安全。

Extending Responsibility-Sensitive Safety for the Assessment of Offloaded Autonomous Driving Services

论文配图:Extending Responsibility-Sensitive Safety for the Assessment of Offloaded Autonomous Driving Services
图 1 · 摘自论文原文
  • 扩展责任敏感安全模型,显式考虑本地与远程服务的响应时间差异。
  • 只有在端到端延迟下仍满足安全条件时才允许远程执行,否则自动回退。
  • 引入预热备用机制,实现更快速安全的远程到本地切换,适合高安全性场景。

自动驾驶系统对安全性要求极高。尽管功能卸载能显著提升计算效率并降低能耗,但将其应用于安全关键功能时带来新挑战:由于车-万物无线通信导致的响应时间增加和波动,直接影响车辆反应时间,进而威胁安全保证。本文通过扩展责任敏感安全(RSS)定义,明确纳入本地与远程服务组合的不同响应时间。基于此,提出将RSS安全约束融入功能卸载决策与回退机制中——仅当当前交通状况在对应端到端延迟下仍安全时,才允许远程执行;若不满足,则系统触发受控回退至本地运行。此外,提出增强型回退策略,包含远程服务的预热备用阶段,实现更快、更安全的远程至本地切换。该方法已集成至我们的自动驾驶栈,并在仿真与真实世界中验证。实验结果表明,相比现有先进卸载与安全框架,本方法在保障分布式计算优势的同时显著提升安全性。

原文摘要 · Abstract (English)

Safety is a fundamental requirement in the development of autonomous driving (AD) systems. While function offloading has demonstrated significant benefits in terms of computational efficiency and energy consumption, its application to safety-critical AD functionality introduces new challenges. In particular, offloaded service compositions incur increased and variable response times due to wireless vehicle-to-everything (V2X) communication, which directly affects the vehicle's reaction time and thus its safety guarantees. In this paper, we address this challenge by extending the definitions of Responsibility-Sensitive Safety (RSS) to explicitly account for different response times of local and offloaded AD service compositions. Based on this extension, we propose an integration into function offloading, using the RSS safety constraints for offloading decision-making and fallback mechanisms. Offloaded service compositions are only permitted if the current traffic situation remains safe under the corresponding end-to-end response time. If this condition is violated, the system performs a controlled fallback to local execution. Furthermore, we introduce an enhanced fallback strategy that includes a warm-standby phase for offloaded services, enabling faster and safer transitions from offloaded to local services. The proposed approach is integrated into our AD stack and evaluated in both simulation and the real world. Experimental results demonstrate that the proposed method improves safety compared to state-of-the-art function offloading and safety frameworks, while preserving the benefits of distributed computation when safety conditions allow.

自动驾驶安全评估功能卸载实时性

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