ScienceDaily

Preventing vehicle crashes by learning from insects
Source: American Chemical Society

Summary:
Despite only about 25% of car travel happening after dark, almost half of fatal accidents occur at night. As our vehicles become more advanced and even autonomous, the ways of detecting and avoiding these collisions must evolve too. Current systems are often complicated, resource-intensive or work poorly in the dark. But now, researchers have designed a simple, power-saving collision detector inspired by the way insects avoid bumping into one another.

Despite only about 25% of car travel happening after dark, almost half of fatal accidents occur at night. As our vehicles become more advanced and even autonomous, the ways of detecting and avoiding these collisions must evolve too. Current systems are often complicated, resource-intensive or work poorly in the dark. But now, researchers reporting in ACS Nano have designed a simple, power-saving collision detector inspired by the way insects avoid bumping into one another.

Numerous collision avoidance systems (CASs) are already included in vehicles, and they can automatically brake when an object gets too close. Some operate by analyzing an image of the space around the car, but in conditions like heavy rain or low light, the image isn't as clear. To make up for it, complicated signal processors are used to make sense of what is still visible. Another method is to incorporate either radar or LiDAR (light detection and ranging) sensors, but these are difficult to miniaturize and need a lot of power. In the end, these instruments can add unnecessary weight, energy requirements and complications, despite making the vehicle safer.

But insects, including locusts and flies, can easily avoid collisions with each other without relying on fancy software or LiDAR, even at night. Instead, they engage certain obstacle-avoiding neural circuits, which are highly efficient and could inspire a next-generation CAS. So, Saptarshi Das and colleagues wanted to create an insect-inspired collision detector adapted to sense vehicles that was effective, safe and consumed less power than its predecessors.

Read on: https://www.sciencedaily.com/releases/2023/01/230117083204.htm#