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Deep Learning Based Emergency Response Traffic Signal Control System

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2023, 28(2), pp.121-129
  • DOI : 10.9708/jksci.2023.28.02.121
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : January 16, 2023
  • Accepted : February 6, 2023
  • Published : February 28, 2023

Jeong-In Park 1

1유에프엠시스템즈(주)

Accredited

ABSTRACT

In this paper, we developed a traffic signal control system for emergency situations that can minimize loss of property and life by actively controlling traffic signals in a certain section in response to emergency situations. When the emergency vehicle terminal transmits an emergency signal including identification information and GPS information, the surrounding image is obtained from the camera, and the object is analyzed based on deep learning to output object information having information such as the location, type, and size of the object. After generating information tracking this object and detecting the signal system, the signal system is switched to emergency mode to identify and track the emergency vehicle based on the received GPS information, and to transmit emergency control signals based on the emergency vehicle's traveling route. It is a system that can be transmitted to a signal controller. This system prevents the emergency vehicle from being blocked by an emergency control signal that is applied first according to an emergency signal, thereby minimizing loss of life and property due to traffic obstacles.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.