Orange-sized roadside radar sensor extends self-driving vehicle view

Researchers at Rice University have developed EyeDAR, a compact, orange-sized millimeter-wave radar sensor designed to enhance safety in autonomous vehicles (AVs) by providing reliable traffic detection where traditional cameras and lidar often fail, such as in fog, heavy rain, or low light. Unlike conventional onboard sensors, EyeDAR is mounted on infrastructure like streetlights and traffic signals, enabling it to track traffic and detect hidden hazards—such as pedestrians obscured by large vehicles—and relay this critical information directly to self-driving cars in real time. This infrastructure-based approach extends the sensing range of AVs and addresses blind spots caused by environmental conditions or physical obstacles. The key innovation behind EyeDAR is its 3D-printed Luneburg lens, inspired by the human eye, which uses over 8,000 uniquely shaped resin elements to bend radar waves toward a focal point, performing “analog computing” by physically manipulating signals rather than relying solely on digital processing. EyeDAR also integrates sensing and communication functions in a single