Insect neural networks as a visual collision detection
mechanism in automotive situations
Richard Stafford (1), Matthias S. Keil (2), Shigang Yue (1), Jorge Cuadri-Carvajo
(2), F. Claire Rind (1)
1) School of Biology, Ridley Building, University of Newcastle upon Tyne, NE1
7RU, UK.
2) Instituto de Microelectronica de Sevilla (IMSE), Centro Nacional de
Microelectronica (CNM),
Avda. Reina Mercedes, 41012, Sevilla, Spain
Abstract
The lobula giant movement detector (LGMD) of locusts is a large visual interneuron
known to respond to objects, such as predators, on a direct collision course. Previous
computer models of the neuron interfaced with camera equipped robots have
demonstrated its effectiveness at collision avoidance in simple environments. The
data presented here examines the performance of a computer realised LGMD model
to real and simulated automotive scenes from the perspective of a camera situated
inside a car. The model was challenged with videos of a range of non collision traffic
sequences as well as videos of collisions with cars. Finally the model was interfaced
with a driving simulator game on a Sony Playstation (Sony Corporation, Japan) to
assess its performance over a range of collision and non collision sequences.
Although the model can detect the majority of the collisions prior to occurrence it
falsely signals collisions when vehicles were found to pass in front of the camera from
left to right or vice versa or when the car in which the camera was situated turned
sharply. False detection of non collision stimuli is not apparent in the real LGMD of
the locust and was largely caused due to the differences in speed to size ratio between
collisions with cars and approaching avian predators.
The LGMD model was then combined with a simple model of the Elementary
Movement Detector (EMD) neurons in the fly visual system. These EMD neurons
were used to detect translating objects or rotational movement and when triggered
inhibited the response of the LGMD. Although the incorporation of the EMD neurons
slightly reduced the success rate of detecting collisions by occasionally inhibiting the
LGMD when real collisions were occurring, the number of false detections was
substantially reduced.
The study shows that the mechanisms of visual processing used by insect
neurons can be exploited for commercial purposes. However, because the commercial
uses of the neuron do not exactly match the purpose for which it evolved in the insect,
modifications to the neurons or integrating several neurons which process information
in different ways may be required for robust performance.