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 – at night, that is.
While radar, LiDAR and computer vision systems are all reasonably effective at keeping autonomous cars from crashing into things, the actual modules themselves can only be miniaturized to a certain extent. They also require a considerable amount of power, plus they just generally add to the complexity of the vehicle.
Seeking a smaller, simpler and more energy-efficient alternative, Pennsylvania State University's Assoc. Prof. Saptarshi Das and colleagues looked to the insect world. More specifically, they studied the neural circuits that keep insects such as locusts from colliding with objects – and from getting caught by predators – while in flight.
The resulting optoelectronic sensor incorporates eight photosensitive "memtransistors" which are made out of a layer of molybdenum disulfide, and laid out in the form of a circuit. It measures just 40 square micrometers, and uses a few hundred picojoules of energy. According to the university, this is tens of thousands times less than the amount required by conventional collision-avoidance sensors.
Used at night, the device gauges the relative distance of cars simply by measuring changes in the intensity of their headlights – the brighter the lights, the closer the car. When tested in real-life driving scenarios, the sensor was able to predict two-vehicle accidents two to three seconds before they happened. While that might not seem like much, it would likely be enough time for an autonomous driving system (or the driver themselves) to take corrective action.
And although the technology probably won't replace existing systems, the scientists do state, "We strongly believe that the proposed collision detectors can augment existing sensors necessary for ensuring autonomous vehicular safety."
The research is described in a paper that was recently published in the journal ACS Nano.
Source: American Chemical Society
