Fuzzy logic to optimize traffic signal control in a congested area / Nor Suhaili Abdul Aziz and Noraini Noordin - Abdul Aziz, Nor Suhaili Abdul Aziz; Noordin, Noraini (Universiti Teknologi MARA, Perlis, 2019)
Traffic congestion is a critical problem to road users worldwide. The present traffic signal control system in Malaysia has not produced optimal solutions for existing traffic congestions. This case study was carried out to test if applying fuzzy logic to traffic signal controllers can optimally solve traffic congestion at the four junctions in a developed urban area on Jalan Kerinchi, Kuala Lumpur. Two input variables (average number of vehicles queueing and arriving at a junction) and one input variable (green time duration) were considered in the study. Five linguistics were associated to each of the input variables thus MATLAB generated 25 fuzzy inference base rules. Results showed large differences between current green time duration (90.81 seconds, 92.72 seconds, 31.58 seconds, 13.88 seconds) and fuzzy logic green time duration (15.30 seconds, 55.00 seconds, 20.00 seconds, 10.00 seconds). Consequently, green time signal durations were minimized. Effectiveness of fuzzy logic applications can be further researched on and tested by adding more input variables or varying the conditions of the junctions.