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Collision avoidance using neural networks
Sugathan S, Sowmya Shree B.V, Warrier M.R,
Published in IOP Publishing
Volume: 263
Issue: 5
Now a days, accidents on roads are caused due to the negligence of drivers and pedestrians or due to unexpected obstacles that come into the vehicle's path. In this paper, a model (robot) is developed to assist drivers for a smooth travel without accidents. It reacts to the real time obstacles on the four critical sides of the vehicle and takes necessary action. The sensor used for detecting the obstacle was an IR proximity sensor. A single layer perceptron neural network is used to train and test all possible combinations of sensors result by using Matlab (offline). A microcontroller (ARM Cortex-M3 LPC1768) is used to control the vehicle through the output data which is received from Matlab via serial communication. Hence, the vehicle becomes capable of reacting to any combination of real time obstacles. © Published under licence by IOP Publishing Ltd.
About the journal
JournalData powered by TypesetIOP Conference Series: Materials Science and Engineering
PublisherData powered by TypesetIOP Publishing
Open AccessNo