Implementation of Neural Network with a variant of Turing Machine for Traffic Flow Control

Journal Title: International Journal on Computer Science and Engineering - Year 2013, Vol 5, Issue 5

Abstract

The conventional method of operation of a typical traffic light is to distribute the time equally for all the directions.This method causes congestion when throughput of the signal increases and is also ineffective in managing traffic flow. In this paper, we have proposed a new model for managing traffic intelligently.The model is based on Turing machine with the application of neural network. The model considers current traffic status of its own signal along with the status of its adjacent signals to determine the ratio of time slot for each signal therefore, reducing traffic congestion to a greater extent and ensuring steady flow of traffic in a wide region.

Authors and Affiliations

Rashmi Sehrawat , Honey Malviya , Vanditaa Kaul

Keywords

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  • EP ID EP146294
  • DOI -
  • Views 99
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How To Cite

Rashmi Sehrawat, Honey Malviya, Vanditaa Kaul (2013). Implementation of Neural Network with a variant of Turing Machine for Traffic Flow Control. International Journal on Computer Science and Engineering, 5(5), 343-348. https://europub.co.uk/articles/-A-146294