Pemodelan Sistem Transportasi Cerdas (Intelligent Transportation System) untuk Mengurangi Kemacetan Perkotaan - Tira Resma (Jurnal Sains dan Teknologi Indonesia, 2025)
This study explores the modeling of Intelligent Transportation Systems (ITS) as an innovative approach to reducing urban traffic congestion. ITS integrates advanced technologies such as Internet of Things (IoT), big data analytics, and sensor-based control systems to optimize traffic flow, enhance mobility, and improve urban sustainability. Data were obtained from case studies and literature focusing on adaptive traffic signal control, real-time traffic monitoring, and integrated public transport management. The findings indicate that ITS-based traffic modeling can reduce average travel time by up to 25% and improve vehicle flow efficiency by 30%. Furthermore, predictive modeling using machine learning allows proactive traffic management and accident prevention. The research concludes that ITS represents a strategic solution to address congestion while supporting the transition towards smart and sustainable cities. Recommendations include integrating artificial intelligence, cloud computing, and vehicle-to-infrastructure communication to further improve system performance.