Minimization traffic congestion with smart traffic light by using fuzzy logic

Traffic congestion is a pervasive problem with significant negative social, economic and environmental impacts. This study aims to reduce traffic congestion on Raja Ashman Shah Road in lpoh by implementing an intelligent fuzzy logic traffic light system. The system aims to reduce waiting times and improve traffic flow by automatically adjusting green light durations based on real-time traffic conditions. Data on the number of vehicles and queue lengths during peak hours were collected to compare congestion levels before and after the intervention. The results of this study demonstrate the effectiveness of deploying an intelligent traffic light system with fuzzy logic in minimizing traffic congestion and reducing waiting times. By dynamically adjusting green light duration based on real-time traffic conditions, the system optimized traffic flow and improved overall congestion. A comparison of congestion levels before and after the introduction showed a significant reduction in congestion and an improvement in traffic flow. The adaptability of the intelligent traffic light system makes better use ofroad capacity, reducing waiting times and minimizing congestion. As a result, we found a significant reduction in waiting time compared to the previous static system. The results highlight the effectiveness of intelligent traffic light systems based on fuzzy logic in minimizing congestion and optimizing traffic flow. This study will provide valuable information to improve the transportation system and improve the quality oflife for road users in lpoh.