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ITSMEI: An intelligent transport system for monitoring traffic and event information

Author

Listed:
  • Matheus S Quessada
  • Rickson S Pereira
  • William Revejes
  • Bruno Sartori
  • Euclydes N Gottsfritz
  • Douglas D Lieira
  • Marco AC da Silva
  • Geraldo P Rocha Filho
  • Rodolfo I Meneguette

Abstract

The disorderly growth of urban centers can lead to serious socioeconomic disadvantages, such as health problems, due to long-term exposure to toxic gases and also monetary losses due to time stopped in congestion. Thus, there is a need for systems that help in the management and control of the flow of vehicles on the roads, seeking to reduce the damage resulting from a faulty transportation system and also avoiding the use of an inefficient system of information dissemination of urban roads. In this scenario, innovative systems are being developed to analyze the conjunction of road conditions to supervise and provide routes as needed for drivers to provide greater comfort and safety to vehicle traffic on urban roads. Thus, in this work, we propose the development of a system to monitor vehicle traffic, informing about events that are taking place on the roads in real time. The system can recommend new routes to drivers or allow drivers to take action based on information received from a particular road. As well as, the system uses driver location information for traffic monitoring, which will later be available for any devices, either a mobile device (smartphone) or a desktop. For the evaluation of the proposed system, a user case was developed for the Catanduva city in which we performed a test with the proposed system and was possible to verify a reduction in vehicle stopping time by 42% and a shorter travel time of 50% with an average speed of 33 km/h.

Suggested Citation

  • Matheus S Quessada & Rickson S Pereira & William Revejes & Bruno Sartori & Euclydes N Gottsfritz & Douglas D Lieira & Marco AC da Silva & Geraldo P Rocha Filho & Rodolfo I Meneguette, 2020. "ITSMEI: An intelligent transport system for monitoring traffic and event information," International Journal of Distributed Sensor Networks, , vol. 16(10), pages 15501477209, October.
    • Handle: RePEc:sae:intdis:v:16:y:2020:i:10:p:1550147720963751
    DOI: 10.1177/1550147720963751
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    References listed on IDEAS

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    1. Dia, Hussein, 2001. "An object-oriented neural network approach to short-term traffic forecasting," European Journal of Operational Research, Elsevier, vol. 131(2), pages 253-261, June.
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