Optimalisasi Traffic Light Berbasis Fuzzy Logic Object Detection untuk Mewujudkan Medan Smart City

Abstract

The automotive sector is experiencing significant growth due to technological advancements, leading to an increase in the number of vehicles on the road. This leads to severe traffic congestion, especially during peak hours, with intersections being heavily affected. Traditional fixed timer traffic light systems have proven inadequate in managing this congestion. This research aims to develop an optimised traffic light system using object detection with fuzzy logic. By integrating real-time vehicle detection (YOLO) technology with fuzzy logic, the duration of traffic lights can be adjusted dynamically. This approach is expected to reduce vehicle queues and improve traffic efficiency at major intersections in Medan, contributing to smart city aspirations. The objectives include reducing traffic congestion, overcoming the limitations of traditional fixed timer systems, and supporting advanced traffic management technologies.