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All Journal CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC)
Muslih Rayullan Feter
Universitas Ahmad Dahlan
Aerospace Engineering Computer Science & IT Education Electrical & Electronics Engineering Engineering Other

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Journal : CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro

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Prototype Lampu Lalu Lintas Adaptif Berdasarkan Panjang Antrian Kendaraan Berbasis Arduino Uno Phisca Aditya Rosyady; Zakky Ahmad Ikhsan M; Muslih Rayullan Feter
Circuit: Jurnal Ilmiah Pendidikan Teknik Elektro Vol 6, No 2 (2022)
Publisher : PTE FTK UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/crc.v6i2.13748

Abstract

Jamming has become a major problem in the big cities in Indonesia. One of the vulnerable points that cause congestion/jam is at the crossroads. Traffic lights should be a very important component in the traffic control system, especially at crossroads. Had a significant change in the number of vehicles and there is no data update, it will cause a longer waiting time. The purpose of this research to design an adaptive traffic light system based on the queue length of vehicles on each road section and testing the traffic light control simulation design. This research used Arduino Uno as a microcontroller and infrared detection sensor. Sensor readings will detect the condition of each road which will be sent to the microcontroller and processed in determining the duration of each traffic light. The results of this study indicates a traffic light system designed to control traffic lights based on the queue length of vehicles on each road segment. Meanwhile, in testing the system, the error value is 0.00404% for the duration of the green light. 0.00917% for the duration of the yellow light, and 0.0217% for the duration of the red light. Based on the results, it is expected that there should be development using a microcontroller that put more input and output pins so that it can detect density on roads more accurately.
Co-Authors Phisca Aditya Rosyady Zakky Ahmad Ikhsan M