The week's pick
Reseach Article
Traffic Flow Control using Neural Network
| International Journal of Applied Information Systems |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 1 - Number 2 |
| Year of Publication: 2012 |
| Authors: Anuja Nagare, Shalini Bhatia |
10.5120/ijais12-450115
|
Anuja Nagare, Shalini Bhatia . Traffic Flow Control using Neural Network. International Journal of Applied Information Systems. 1, 2 ( January 2012), 50-52. DOI=10.5120/ijais12-450115
Abstract
With rapid increase in motorization, urbanization, population growth, and changes in population density, Traffic Congestion problems have increased worldwide. Traffic Congestion causes increase in traveling time, air pollution and increase in fuel usage is also observed. Intelligent Transportation Systems (ITS) are used to avoid these problems and improve efficiency, safety and service. Traffic Flow Forecasting is an important part of ITS [1][2]. Traffic Flow Forecasting (TFF) is for Controlling Traffic and Intelligent Traffic Guidance. TFF is the study of interactions between vehicles, drivers, and infrastructure (which includes highways and traffic control devices), with the aim of understanding and developing an optimal road network with efficient movement of traffic and minimal traffic congestion problems.
References
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- Fengying Cui , “Study Of Traffic Flow Prediction Based On Bp Neural Network”, In proc. of College of Automation and Electronic Engineering Qingdao University of Science and Technology Qingdao, 2010.
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- Li Xiaobin, “RBF Neural Network Optimized by Particle Swarm Optimization for Forecasting Urban Traffic Flow” , Third International Symposium on Intelligent Technology Application, 2009, pp. 124-127
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