Insects show drivers the way to avoid collisions

March 2007

Despite flying in large swarms, locusts are very efficient at avoid colliding with each other. They achieve this thanks to a highly developed visual response to an object approaching on a direct collision course. Supported by a Future and Emerging Technology Grant from the European Union, Dr. Claire Rind and her colleagues at Newcastle have been working on this collision avoidance pathway in the brain of the locust in order to adapt it for use as a collision avoidance system in cars. This adaptation involves changing the responses of the real neurons (the lobula giant movement detector - LGMD) into a computer model that uses the same visual information to make a decision about a collision. In this paper they used an algorithm to tune the model to the speeds of image motion it would be exposed to in a car. In addition they integrated it with a model of another neural system that exists in the fly visual system which is able to detect the direction of movement insect (elementary movement detector neurons) in order to separate colliding and non-colliding, translating, stimuli. By combining the information from a LGMD neuron with four directionally sensitive neurons they were able to produce a robust collision detection system for a wide range of automotive test situations. They have gone on to use this tuned model as the basis of a computer chip that was integrated into a Volvo XC90 car. Furthermore, for the ingenious use of different colliding images taken from the film ‘Star Wars’ Dr. Rind and her colleague, Dr. Peter Simmons, were awarded the 2005 Ig Nobel Prize for peace from Harvard University.  

A bio-inspired visual collision detection mechanism for cars: Combining insect inspired neurons to create a robust system. Stafford R, Santer RD, Rind FC (2007) Biosystems 87: 164-171 (PubMed abstract:

published on: 1st April 2007