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Design and Implementation of an Intelligent Traffic Management System: A Neural Approach
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Author(s): Shamim Akhter (East West University (EWU), Bangladesh), Sakhawat Hosain Sumit (Socian Ltd., Bangladesh)and Md. Rahatur Rahman (Simplexhub Ltd., Bangladesh)
Copyright: 2019
Pages: 22
Source title:
Exploring Critical Approaches of Evolutionary Computation
Source Author(s)/Editor(s): Muhammad Sarfraz (Kuwait University, Kuwait)
DOI: 10.4018/978-1-5225-5832-3.ch004
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Abstract
Intelligence traffic management system (ITMS) provides effective and efficient solutions toward the road traffic management and decision-making problems, and thus helps to reduce fuel consumption and emission of greenhouse gases. Software-based real-time bi-directional TMS with a neural network was proposed and implemented. The proposed TMS solves a decision problem, dynamic road weights calculation, using different environmental, road and vehicle related decision attributes. In addition, the development of the real-time operational models as well as their solving challenges has increased in a rapid manner. Therefore, the authors integrate the design and development of a neural-based complete real-time operational ITMS, with the combination of software modules including traffic monitoring, road weight updating, forecasting, and optimum route planning decision. Collecting, extracting the insights and inherit meaning, and modeling the tremendous amount of continuous data is a challenging task. A discussion is also included with the future improvements on ITMS.
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