发表机构
Graduate School of Science and Engineering, Saitama University; Technology Development Functional Division, Astemo, Ltd.; Academic Association (Graduate School of Science and Engineering), Saitama University（埼玉大学理工学研究科; 爱思摩有限公司技术开发事业部; 埼玉大学学术协会（理工学研究科））
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对混合ROS 2与AUTOSAR AP车载系统的跨域追踪难题，提出边界感知轨迹重建框架BA-TRACE，融合多源事件重建端到端执行图，经案例验证可揭示边界延迟，支撑可追溯性评估。
AI 中文摘要
现代车载嵌入式系统日益将基于ROS 2的自动驾驶栈与AUTOSAR Adaptive Platform（AUTOSAR AP）相结合。此类混合栈使得场景化评估难以解释，因为执行路径跨越了ROS 2与AUTOSAR AP之间的DDS-SOME/IP中间件边界。现有的模拟器和追踪工具能够执行场景或收集平台本地轨迹，但无法重建跨域数据流。本文提出了BA-TRACE，一种面向混合AUTOSAR AP与ROS 2车载嵌入式系统场景化评估的边界感知轨迹重建框架。BA-TRACE结合ROS 2轨迹事件、AUTOSAR ara::log事件、ARXML派生的结构依赖以及桥接级插桩，以重建跨越DDS-SOME/IP边界的端到端执行图。一项基于AWSIM/OpenSCENARIO的目标检测与制动场景案例研究表明，BA-TRACE能够重建预期的跨平台路径，并揭示边界特定的延迟，如点云传输开销。重建的拓扑结构用作可追溯性的证据，而非行为正确性或安全性的证明。
英文摘要
Modern vehicular embedded systems increasingly combine ROS 2-based autonomous-driving stacks with AUTOSAR Adaptive Platform (AUTOSAR AP). Such mixed stacks make scenario-based evaluation hard to interpret because execution paths cross DDS-SOME/IP middleware boundaries between ROS 2 and AUTOSAR AP. Existing simulators and tracing tools execute scenarios or collect platform-local traces but cannot reconstruct cross-domain data flows. This paper presents BA-TRACE, a boundary-aware trace reconstruction framework for scenario-based evaluation of mixed AUTOSAR AP and ROS 2 vehicular embedded systems. BA-TRACE combines ROS 2 trace events, AUTOSAR ara::log events, ARXML-derived structural dependencies, and bridge-level instrumentation to reconstruct an end-to-end execution graph across the DDS-SOME/IP boundary. A case study with an AWSIM/OpenSCENARIO-based object-detection and braking scenario shows that BA-TRACE reconstructs the expected cross-platform path and exposes boundary-specific latency such as point-cloud transfer overhead. The reconstructed topology is used as evidence of traceability, not as proof of behavioral correctness or safety.
