论文标题
REIT:智能运输系统的反射表面
REITS: Reflective Surface for Intelligent Transportation Systems
论文作者
论文摘要
预计在可预见的将来,自动驾驶汽车将主导运输行业。安全是自动驾驶系统早期部署的主要挑战之一。为了确保安全,自动驾驶车辆必须准确,稳健,及时地感知和检测人类,其他车辆和道路基础设施。但是,自动驾驶汽车使用的现有传感技术可能不是绝对可靠的。在本文中,我们设计了REIT,该系统是提高自动驾驶汽车的基于RF的传感模块可靠性的系统。我们对现有基于RF的传感系统的可能失败进行理论分析。基于分析,REIT采用了多个Antenna设计,该设计使建设性的盲梁形成能够在入射方向返回增强的雷达信号。 REIT还可以通过在建设性的光束形成状态和破坏性的光束形成状态之间切换现有雷达系统感官识别信息。初步结果表明,REIT将自动驾驶汽车雷达的检测距离提高了3.63。
Autonomous vehicles are predicted to dominate the transportation industry in the foreseeable future. Safety is one of the major challenges to the early deployment of self-driving systems. To ensure safety, self-driving vehicles must sense and detect humans, other vehicles, and road infrastructure accurately, robustly, and timely. However, existing sensing techniques used by self-driving vehicles may not be absolutely reliable. In this paper, we design REITS, a system to improve the reliability of RF-based sensing modules for autonomous vehicles. We conduct theoretical analysis on possible failures of existing RF-based sensing systems. Based on the analysis, REITS adopts a multi-antenna design, which enables constructive blind beamforming to return an enhanced radar signal in the incident direction. REITS can also let the existing radar system sense identification information by switching between constructive beamforming state and destructive beamforming state. Preliminary results show that REITS improves the detection distance of a self-driving car radar by a factor of 3.63.