Optimization of smart traffic lights to prevent traffic congestion using fuzzy logic

According to the Indonesian Central Statistics Agency (BPS, Badan Pusat Statistik), the number of four-wheeled cars and motorcycles in 2016 reached more than 14 million and 105 million each. Hawi et al. describe the smart traffic light for an isolated for-way junction that incorporates Wireless Sensor Network (WSN) for collecting road traffic data, fuzzy logic control (FLC) for decision making, and a routing algorithm that assigns green light (period) based on data retrieved from FLC. According to research conducted by D. Hartanti et al about crossroads using algorithms and data structures programmed in the Arduino control device system, with the input of maximum speed and length of vehicles it is known that traffic density is seen to increase in the morning and evening [17], Simulation experiments on scale models in detecting the length of the vehicle queue using the help of infrared sensors placed in each intersection path, then applying the Greedy algorithm to help speed up the movement of the green light duration for the path that needs [18], simulation applications of movement and traffic control are used for monitoring queue length and duration of green light in traffic [19]. New Smart Traffic Light Using Traveling Salesman Problem and Greedy Algorithm. in 3rd Asia Future Conference (AFC).