Artificial neural network model of traffic operations at signalized junction in Johor Bahru, Malaysia

• Main Authors: Che Puan, Othman, Roshandeh, Arash Moradkhani, Joshani, Majid
• Format: Book Section
• Published: World Scientific And Engineering Acad And Soc 2009
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/id/eprint/13185/; https://pure.utm.my/en/publications/artificial-neural-network-model-of-traffic-operations-at-signaliz

Driving behavior models are an important component of microscopic traffic simulation tools. Artificial Neural Networks (ANN) are systems that try to make use of some of the known or expected organizing principles of the human brain. Today neural networks can be trained to solve problems that are difficult for conventional computers or human beings. In this research four signalized junction in Johor Bahru have been considered and simulation of driver's behavior in terms of delay and queue length have been implemented. The neural network approach seems to be more natural and reasonable than the conventional method. The neural network is also more effective and efficient in determining appropriate traffic terms of study.