一种更快更可靠的自动驾驶系统中件
A Faster and More Reliable Middleware for Autonomous Driving Systems
AI总结：
针对ROS 2中间件在自动驾驶中传输开销大的问题，提出共享内存传输机制SIM，降低延迟达98%，提升定位频率并缩短制动距离。
摘要：
确保高速自动驾驶车辆的安全性需要快速的闭环控制以及从感知到执行严格受限的延迟。许多开源自动驾驶系统依赖ROS 2中间件；当多个传感器和控制节点共享一个计算单元时，ROS 2及其DDS传输会带来显著的（反）序列化、复制和发现开销，从而压缩可用的时间预算。我们提出了Sensor-in-Memory（SIM），一种为自动驾驶车辆内主机间管道设计的共享内存传输机制。SIM将传感器数据保留在原生内存布局中（例如cv::Mat、PCL），使用无锁有界双缓冲区，通过覆盖旧数据来优先保证数据新鲜度，并仅需四行代码即可集成到ROS 2节点中。与传统中间件不同，SIM在ROS 2旁运行，并针对数据新鲜度和最小延迟优先于保证完整性的应用场景进行了优化。SIM提供序列号、写入端心跳和可选的校验和，以确保排序、存活性和基本完整性。在NVIDIA Jetson Orin Nano上，与FastRTPS和Zenoh等ROS 2零拷贝传输相比，SIM将数据传输延迟降低高达98%，平均延迟降低约95%，并将95%/99%分位数的尾部延迟缩减约96%。在一辆运行Autoware.Universe的生产级L4级车辆的测试中，SIM将定位频率从7.5 Hz提高到9.5 Hz。应用于所有延迟关键模块后，SIM将平均感知到决策延迟从521.91毫秒降至290.26毫秒，在干燥混凝土路面上以40英里/小时（64公里/小时）行驶时，紧急制动距离减少了13.6英尺（4.14米）。
英文摘要：
Ensuring safety in high-speed autonomous vehicles requires rapid control loops and tightly bounded delays from perception to actuation. Many open-source autonomy systems rely on ROS 2 middleware; when multiple sensor and control nodes share one compute unit, ROS 2 and its DDS transports add significant (de)serialization, copying, and discovery overheads, shrinking the available time budget. We present Sensor-in-Memory (SIM), a shared-memory transport designed for intra-host pipelines in autonomous vehicles. SIM keeps sensor data in native memory layouts (e.g., cv::Mat, PCL), uses lock-free bounded double buffers that overwrite old data to prioritize freshness, and integrates into ROS 2 nodes with four lines of code. Unlike traditional middleware, SIM operates beside ROS 2 and is optimized for applications where data freshness and minimal latency outweigh guaranteed completeness. SIM provides sequence numbers, a writer heartbeat, and optional checksums to ensure ordering, liveness, and basic integrity. On an NVIDIA Jetson Orin Nano, SIM reduces data-transport latency by up to 98% compared to ROS 2 zero-copy transports such as FastRTPS and Zenoh, lowers mean latency by about 95%, and narrows 95th/99th-percentile tail latencies by around 96%. In tests on a production-ready Level 4 vehicle running Autoware.Universe, SIM increased localization frequency from 7.5 Hz to 9.5 Hz. Applied across all latency-critical modules, SIM cut average perception-to-decision latency from 521.91 ms to 290.26 ms, reducing emergency braking distance at 40 mph (64 km/h) on dry concrete by 13.6 ft (4.14 m).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
