EMP: edge-assisted multi-vehicle perception
EMP: edge-assisted multi-vehicle perception
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DOI：
10.1145/3447993.3483242
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发表时间：
2021-10
期刊：
影响因子：
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通讯作者：
Xumiao Zhang;Anlan Zhang;Jiachen Sun;Xiao Zhu;Y. Guo;Feng Qian;Z. Mao
中科院分区：
文献类型：
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作者：
Xumiao Zhang;Anlan Zhang;Jiachen Sun;Xiao Zhu;Y. Guo;Feng Qian;Z. Mao
连接和自动驾驶汽车（CAVS）严重依赖3D传感器，例如激光雷达，雷达和立体声摄像机。但是，来自单个车辆的3D传感器遭受了两个基本局限性的限制：易受阻塞和遥远物体细节的漏洞。为了克服这两个局限性，在本文中，我们设计，实施和评估EMP，这是一种新型的边缘辅助多车感知系统。在EMP中，多个附近的骑士与边缘服务器共享其原始传感器数据，然后将CAVS的个人视图合并，形成更完整的视图，并具有更高的分辨率。合并的视图可以大大提高参与骑士的感知质量。我们的核心方法论贡献是通过一系列新颖的算法使传感器数据共享可扩展，适应性和资源有效的无线链接，然后将其集成到成熟的合作感应管道中。广泛的评估表明，EMP可以在24 fps下实现实时处理，平均端到端的潜伏期为93毫秒。与传统的车辆到车辆（V2V）共享方法相比，EMP将端到端的潜伏期降低了49％至65％。我们的案例研究表明，与单个车辆的感知相比，由EMP提供动力的合作感应可以检测到诸如盲点等危害，例如盲点斑点，例如0.5至1.1秒。
Connected and Autonomous Vehicles (CAVs) heavily rely on 3D sensors such as LiDARs, radars, and stereo cameras. However, 3D sensors from a single vehicle suffer from two fundamental limitations: vulnerability to occlusion and loss of details on far-away objects. To overcome both limitations, in this paper, we design, implement, and evaluate EMP, a novel edge-assisted multi-vehicle perception system for CAVs. In EMP, multiple nearby CAVs share their raw sensor data with an edge server which then merges CAVs' individual views to form a more complete view with a higher resolution. The merged view can drastically enhance the perception quality of the participating CAVs. Our core methodological contribution is to make the sensor data sharing scalable, adaptive, and resource-efficient over oftentimes highly fluctuating wireless links through a series of novel algorithms, which are then integrated into a full-fledged cooperative sensing pipeline. Extensive evaluations demonstrate that EMP can achieve real-time processing at 24 FPS and end-to-end latency of 93 ms on average. EMP reduces the end-to-end latency by 49% to 65% compared to the traditional vehicle-to-vehicle (V2V) sharing approach without edge support. Our case studies show that cooperative sensing powered by EMP can detect hazards such as blind spots faster by 0.5 to 1.1 seconds, compared to a single vehicle's perception.