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

Related Articles

Trust-based Routing Security in MANETS

The advantage of Mobile Ad-hoc Networks (MANETs) is to orm a wireless network in the absence of fixed infrastructure. arly stages of routing protocols of MANETs were, incapable of handling security issues but by the in...

Architectural Based Data Aggregation Techniques in Wireless Sensor Network: A Comparative Study

Data aggregation is very crucial techniques in wireless sensor network. Because with the help of data aggregation we reduce the energy consumption by eliminating redundancy .when wireless sensor network deployed in remot...

INVESTMENT PORTFOLIO MANAGER- MOBILE APPLICATION

The application of this project is to help the user keep track of his investments and manage his portfolio anytime, anywhere. A system of this sort finds its applications in trading, keeping track of the user's/company's...

PERFORMANCE EVALUATION OF THREEPHASE INDUCTION MOTOR DRIVE FED FROM Z-SOURCE INVERTER

This paper presents a Z-source inverter which has been proposed as an alternative power conversion concept for adjustable speed AC drives. It is having both voltages buck and boost capabilities as they allow inverters to...

New Edge Detection Technique based on the Shannon Entropy in Gray Level Images

Edge detection is an important field in image processing. Edges characterize object boundaries and are therefore useful for segmentation, registration, feature extraction, and identification of objects in a scene. In thi...

Download PDF file
  • EP ID EP146294
  • DOI -
  • Views 71
  • Downloads 0

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