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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Shamim Akhter & Rahatur Rahman & Ashfaqul Islam, 2016. "Neural Network (NN) Based Route Weight Computation for Bi-Directional Traffic Management System," International Journal of Applied Evolutionary Computation (IJAEC), IGI Global, vol. 7(4), pages 45-59, October.
    • Handle: RePEc:igg:jaec00:v:7:y:2016:i:4:p:45-59
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