Optimisasi Koloni Semut dan Sistem Fuzzy untuk Kendali Lampu Lalu Lintas Pintar
Abstract
Pola pengaturan lampu lalu lintas waktu tetap yang tidak mempertimbangkan kondisi aktual persimpangan bisa menimbulkan kemacetan. Kemacetan dapat menyebabkan banyak kerugian, diantaranya yaitu banyaknya waktu terbuang dan bahan bakar yang habis dengan sia- sia. Masalah ini dapat diatasi dengan pengatur lampu lalu lintas pintar yaitu sebuah sistem pengatur lampu lalu lintas yang mampu beradaptasi dengan kondisi setiap ruas jalan pada persimpangan. Pada penelitian ini telah dilakukan pengembangan sistem pengatur lampu lalu lintas pintar berbasis pada logika fuzzy bertingkat dan algoritma optimisasi koloni semut (Ant Colony Optimization). Pada Logika Fuzzy Bertingkat, keluaran dari sistem logika fuzzy tahap pertama menjadi masukan ke sistem logika fuzzy tahap berikutnya. Keluaran dari Sistem Fuzzy adalah menentukan skala prioritas untuk fase hijau berikutnya. Selanjutnya algoritma optimisasi koloni semut melakukan perhitungan waktu hijau yang optimal pada fase tersebut. Berdasarkan hasil simulasi yang dilakukan diperoleh bahwa dengan menggunakan sistem pengatur lampu lalu lintas pintar dibanding dengan sistem pengatur lampu lalu lintas waktu tetap terjadi pengurangan panjang antrian kendaraan dan waktu tunggu kendaraan.
Fixed time traffic light control is a traffic light control system that does not take into account the actual conditions of the intersection, which can cause congestion. Congestion can cause a lot of losses, including a lot of wasted time and wasted fuel. This problem can be solved with a smart traffic light controller, which is a traffic light control system that is able to adapt to the conditions of each road section at the intersection. In this research, the development of smart traffic light control based on multi stage fuzzy logic and ant colony optimization (ACO) algorithm has been carried out. In multi stage fuzzy logic, the output of the first stage of the fuzzy logic becomes the input to the next stage of the fuzzy logic. The output of the fuzzy system is to determine the priority scale for the next green phase. Furthermore, Ant Colony Optimization calculates the optimal green time in that phase. Based on the simulation result, it is found that by using smart traffic light control system compared to a fixed time traffic light control system, there is a reduction in queue length and waiting time.
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DOI: https://doi.org/10.37905/jjeee.v4i2.14473
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