Real Time Traffic Simulation Development on Expressway

Abstract

The increasing demand for expressway usage has created significant challenges in managing traffic flow and responding effectively to incidents in real time. This study focuses on the development and implementation of a real-time traffic simulation model using Aimsun Live for the expressway network. The simulation operates at the mesoscopic level to balance computational efficiency, forecasting accuracy, and scalability for future expansions. The model integrates real-time data from detectors, machine learning-based traffic pattern recognition, and scenario evaluation modules to support dynamic traffic management. The simulation considers critical parameters such as speed limits, lane configurations, vehicle restrictions, and toll plaza layouts. This development reduces the impact of traffic congestion, enhances the convenience for road users, and elevates the management of the expressway network to international standards.