A Survey on Dynamic Toll Charge

Authors

  • Prof. Mounica B  Department of Information Science and Engineering, New Horizon College of Engineering, Bengaluru, Karnataka, India
  • Merlin Mathew  Department of Information Science and Engineering, New Horizon College of Engineering, Bengaluru, Karnataka, India
  • Aishwarya Balakrishnan  Department of Information Science and Engineering, New Horizon College of Engineering, Bengaluru, Karnataka, India
  • Bikky Kumar Goit  Department of Information Science and Engineering, New Horizon College of Engineering, Bengaluru, Karnataka, India

DOI:

https://doi.org//10.32628/CSEIT1952326

Keywords:

Big data eco-system, Intelligent transportation system, NoSQL Database, feature extraction and feature selection.

Abstract

With continuing economic growth, the demand of traffic rises continuously, especially in modern cities like Bangalore. However, the space available in cities is strictly limited. In order to cope with the challenge of serving a rising traffic demand on these limited capacities, traffic management becomes mandatory. One aspect is managing the traffic by charging dynamic toll depends on conditions like occupancy of cab services, previous data. The focus of this project is a dynamic toll pricing scheme that alleviates congestion and maintains an optimized traffic density during peak hour traffic.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2019-04-30

Issue

Volume 5, Issue 2, March-April-2019

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Prof. Mounica B, Merlin Mathew, Aishwarya Balakrishnan, Bikky Kumar Goit, " A Survey on Dynamic Toll Charge, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.1255-1260, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT1952326