As many companies work to put autonomous vehicles (self-driving cars) on roads, scientists are working to find ways to increase the safety of these vehicles not just for the passengers they carry but also for those in the environment, such as cyclists and pedestrians. A team of researchers has come up with a concept involving installing radar sensors on roadsides to augment the onboard sensors in autonomous vehicles.
Dubbed EyeDAR, these low-power radar sensors are small (approximately orange-sized) and are designed to provide extra input to onboard sensors so that the technology inside self-driving cars can function a lot better than it would if it only depended on data collected by the sensors on and inside the vehicles themselves.
The EyeDAR sensors can be placed at strategic locations like intersections and streetlights. Such sensors would collect data that would ordinarily be outside the scope of sensors on AVs, such as a cyclist who approaches a junction from an unusual angle or a pedestrian who steps into the road from the side of a large vehicle.
In these examples, the sensors on an AV can easily miss this emergent object/person and an accident can occur. With the EyeDAR sensors, however, the onboard sensors would receive input about the environment and the vehicle would take the necessary action, such as stopping to let the pedestrian through.
These new sensors were introduced during the HotMobile 2026 workshop that was held in Atlanta on February 25-26. Kun Woo Cho, a Rice University researcher, led the team that developed these radar sensors. She explained that her team wanted to find a solution to the challenges that automotive sensors like lidar and camera systems face, such as limited effectiveness during poor visibility conditions.
When it is raining, there is fog, or lighting is poor, onboard lidar and camera systems struggle to collect input from the environment of an AV. The roadside radar system would help since it works optimally in all conditions, including poor-visibility situations.
The researchers explain that their sensors don’t just collect input but also process it and share it in ways that communicate to other systems, such as onboard lidar sensors. The radar sensor design is inspired by the human eye, which has a lens to collect input and a retina to process that input.
These “extra eyes” could be of great help in making autonomous vehicles a lot safer. They could also serve in other applications, such as drones, robots and wearable devices. It would be interesting to hear what firms like Alphabet Inc. (NASDAQ: GOOGL) (NASDAQ: GOOG) with interests in the autonomous vehicle segment have to say about the benefits of installing EyeDAR on road infrastructure.
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