aiqbench analysis
This research extends Responsibility-Sensitive Safety (RSS) frameworks to explicitly account for variable latency introduced by offloading autonomous driving functions to edge or cloud resources. By integrating these extended safety constraints into offloading decision logic, the system ensures that distributed computation is only utilized when end-to-end response times maintain safe reaction margins, automatically falling back to local execution if thresholds are breached. The approach validates that safety guarantees are preserved while still leveraging the computational efficiency and energy savings of offloaded architectures.
Extending Responsibility-Sensitive Safety for the Assessment of Offloaded Autonomous Driving Services
arXiv:2606.07067v1 Announce Type: new Abstract: 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.
Abstract: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.
Robotics (cs.RO)
arXiv:2606.07067 [cs.RO]
(or arXiv:2606.07067v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2606.07067 arXiv-issued DOI via DataCite (pending registration)
Full text under the publisher's open licence · 238 words