Self-driving cars typically use radar or LiDAR technology to avoid collisions with other vehicles. Scientists have now created a much simpler, insect-inspired system that could serve the same purpose more efficiently – namely at night.
While radar, LiDAR, and computer vision systems are all reasonably effective at preventing autonomous cars from colliding with things, the actual modules themselves can only be miniaturized to a certain extent. They also require a significant amount of power and generally only add to the complexity of the vehicle.
Looking for a smaller, simpler, and more energy-efficient alternative, Assoc. Prof. Saptarshi Das and colleagues looked into the world of insects. More specifically, they studied the neural circuits that keep insects like grasshoppers from colliding with objects while in flight — and being caught by predators.
The resulting optoelectronic sensor contains eight light-sensitive “memtransistors” made of a layer of molybdenum disulfide and arranged in a circuit. It is only 40 square microns and consumes a few hundred picojoules of energy. According to the university, this is 10,000 times less than conventional collision avoidance sensors.
Used at night, the device measures the relative distance of cars by simply measuring changes in the intensity of their headlights – the brighter the lights, the closer the car. When tested in real driving scenarios, the sensor was able to predict two-vehicle crashes two to three seconds before they happened. While that may not seem like much, it would likely be enough time for an autonomous driving system (or the driver himself) to take corrective action.
And while the technology is unlikely to replace existing systems, the scientists state: “We strongly believe that the proposed collision detectors can complement existing sensors needed to ensure the safety of autonomous vehicles.”
The research is detailed in an article recently published in the journal ACS Nano.
Source: American Chemical Society
