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Localization based intelligent traffic management system

Author

Listed:
  • Praveen Goel

    (Graphic Era University)

  • R. H. Goudar

    (Visvesvaraya Technological University (VTU))

  • Rohit Malik

    (Graphic Era University)

  • Ranjeet Singh

    (Graphic Era University)

  • Nitish Kumar Singh

    (Graphic Era University)

Abstract

Traffic management is a real challenge that is faced by almost every metropolitan city of the world. As due to the increase in number of public as well as private transportation on roads, traffic problem bound to exist. Therefore in order to sort out this problem an intelligent traffic management system is introduced in this paper, according to which we would be able to control the flow time at cross roads in an efficient way and in addition to this we are also introducing a new traffic assistance system for the drivers. Initially we had divided the city in a set of seed nodes where every seed node is installed with a server capable of maintaining the database of all the vehicles present in a particular area allotted to it. For the traffic assistance the driver will be interacting with the server through an installed hardware. This hardware is capable of localizing every vehicle with a use of sensor network containing gyroscopic sensor, altimeter and magnetic compass as the main components. This calculated location is transmitted to the server for the database updating and at the same time the hardware will be displaying the current traffic conditions by accessing the same database.

Suggested Citation

  • Praveen Goel & R. H. Goudar & Rohit Malik & Ranjeet Singh & Nitish Kumar Singh, 2017. "Localization based intelligent traffic management system," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(1), pages 90-98, January.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:1:d:10.1007_s13198-015-0407-x
    DOI: 10.1007/s13198-015-0407-x
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    Cited by:

    1. Mohamed Alawadhi & Jumah Almazrouie & Mohammed Kamil & Khalil Abdelrazek Khalil, 2020. "A systematic literature review of the factors influencing the adoption of autonomous driving," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(6), pages 1065-1082, December.

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