Neural Network (NN) Based Route Weight Computation for Bi-Directional Traffic Management System

Shamim Akhter, Rahatur Rahman and Ashfaqul Islam
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Shamim Akhter: Computer Science and Engineering Department, East West University, Dhaka, Bangladesh
Rahatur Rahman: Simplexhub Ltd., Dhaka, Bangladesh
Ashfaqul Islam: Computer Science and Engineering Department, East West University, Dhaka, Bangladesh

International Journal of Applied Evolutionary Computation (IJAEC), 2016, vol. 7, issue 4, 45-59

Abstract: Low-cost, flexible, easily maintainable and secure traffic management support systems are in demand. Internet-based real time bi-directional communication provides significant benefits to monitor road traffic conditions. Dynamic route computation is a vital requirement to make the traffic management system more realistic and reliable. Therefore, an integrated approach with multiple data feeds and Backpropagation (BP) Neural Network (NN) with Levenberg-Marquardt (LM) optimization is applied to predict the road weights. The results indicate that the proposed traffic system/tool with NN based dynamic weights computation is much more effective to find the optimal routes. The BP NN with LM optimization achieves 96.67% accuracy.

Date: 2016
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