This low-cost orange-sized sensor could be what self-driving cars need to hit public roads

A team of engineers at Rice University has developed a tiny new sensor that could dramatically improve the safety of self-driving cars on public roads. This is a compact, low-power millimeter-wave radar sensor roughly the size of an orange. The new tech, dubbed EyeDar, is designed to work as an “extra set of eyes” by enhancing radar perception in places where a vehicle’s own sensors may struggle, such as blind spots, intersections, or poor visibility conditions.

Why existing sensors fall short

Typically, autonomous vehicles rely on a suite of sensors like cameras, LiDAR, and radar to “see” their surroundings. While cameras and LiDAR can offer detailed spatial information in optimal conditions, they have their limitations in bad weather conditions, such as rain, fog, or low light. So carmakers rely on radar for better visibility in poor weather and lighting conditions.

Though even these have limitations, as much of the signal emitted from the radar simply scatters away. Meaning, stationary obstacles or moving pedestrians that aren’t directly in the detection path can remain hidden until it’s too late. Rather than solely relying on just these sensors, EyeDAR arrives to fill these blind spots.

EyeDAR: How does it work

EyeDAR was introduced by Kun Woo Cho, a researcher leading the project in the lab of Ashutosh Sabharwal, a professor of electrical and computer engineering at Rice University. The key innovation here is how EyeDAR combines simple hardware design with efficient signal detection. Its orange-sized form factor makes it small enough to be mounted across road infrastructure, keeping deployment costs low and coverage high.

It uses millimeter-wave radar that operates reliably in all weather and lighting conditions. EyeDAR’s physical design incorporates a 3D printed Luneberg lens and a surrounding antenna array, which can naturally focus on incoming radar signals onto detection elements.

Since the design does much of the direction-finding computation in the hardware itself, it also resolves target directions hundreds of times faster than traditional radar systems. One of EyeDAR’s standout features is its ability to communicate radar information back to self-driving cars. This technology also has wider applications, like robots, drones, and wearable platforms. With its compact design and hardware-level efficiency, EyeDAR could be one of the key pieces in safely putting autonomous vehicles on public roads.