Title: Situation-cognitive traffic light control based on object detection using YOLO algorithm

Authors: Sung-Dong Kim

Addresses: School of Computer Engineering, Hansung University, Seoul 02876, South Korea

Abstract: Current traffic lights provide the green signal with fixed-time interval without considering the traffic situation. As a result, cars in a long line have to wait long time, which causes traffic jams and makes the drivers be irritated. In order to solve the problem, it is necessary to control the green signal interval according to the analysed traffic volume using the image processing and the machine learning techniques. This paper presents a situation-cognitive traffic light control algorithm that measures the traffic volume using object detection algorithm called you only look once (YOLO) and controls the traffic signal intervals according to the traffic volume. The algorithm expects the smooth traffic flow and the reduction of the driver's stress.

Keywords: you only look once; YOLO; object detection; situation-cognitive; traffic light control; computer vision.

DOI: 10.1504/IJCVR.2020.105682

International Journal of Computational Vision and Robotics, 2020 Vol.10 No.2, pp.133 - 142

Received: 06 Feb 2019
Accepted: 26 Mar 2019

Published online: 04 Mar 2020 *

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