Improving urban traffic management and emergency priority through the integration of Geographic Information Systems (GIS) and MATLAB simulation

Abstract

Traffic congestion and delayed emergency response remain major challenges facing modern cities, necessitating innovative solutions that integrate advanced technologies. This study explores the integrated application of Geographic Information Systems (GIS) and MATLAB-based simulation models to improve traffic management and prioritize emergency vehicle movement. GIS provides spatial data for real-time traffic monitoring, while MATLAB enables dynamic simulation of traffic flow and emergency routing scenarios. By combining spatial data analysis and computational modeling, the research develops a framework that enhances traffic signal control, reduces response times, and improves overall urban mobility. Case studies and simulation experiments demonstrate the potential of this integrated approach to support smart city initiatives, offering scalable strategies for sustainable traffic management and life-saving emergency prioritization. The findings highlight the pivotal role of GIS-MATLAB integration in developing intelligent transportation systems and fostering resilient urban infrastructure.