Detection of Road Traffic Congestion Using V2V Communication Based on IoT

  • Zainab A. Abood University of Thi-Qar, College of Education for Pure Science, Computer Science Department
  • Hazeem B. Taher University of Thi-Qar, College of Education for Pure Science, Computer Science Department
  • Rana F. Ghani University of Technology, College of Science, Computer Science Department
Keywords: Vehicle to vehicle (V2V), internet of things (IoT), Raspberry Pi, fuzzy logic

Abstract

Intelligent Transportation Systems (ITS) have been developed to improve the efficiency and safety of road transport by using new technologies for communication. Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) are a subset of ITS widely used to solve different issues associated with transportation in cities. Road traffic congestion is still the most significant problem that causes important economic and productivity damages, as well as increasing environmental effects. This paper introduces an early traffic congestion alert system in a vehicular network, using the internet of things (IoT) and fuzzy logic, for optimizing the traffic and increasing the flow. The proposed system detects critical driving conditions, or any emergency situation blocking the road, and broadcasts remote warnings to the following vehicles. Since not all vehicles are equipped with new technologies, Liquid Crystal Display (LCD) fixed on the roads displays the alert to warn the other vehicles which have neither communication nor sensors. The system was designed with Raspberry Pi 3 Model B equipped with sensors and GPS module to emulate real-world vehicles. The results and observations collected during the experiments showed that the proposed system is able to monitor the road conditions, detect the emergency situation, and broadcast a warning message to the approaching vehicles.

Published
2021-01-30
How to Cite
AboodZ. A., TaherH. B., & GhaniR. F. (2021). Detection of Road Traffic Congestion Using V2V Communication Based on IoT. Iraqi Journal of Science, 62(1), 335-345. https://doi.org/10.24996/ijs.2021.62.1.32
Section
Computer Science