Quantitative Methodology for Comparing Microscopic Traffic Simulators

Abstract

As part of transportation planning processes, simulators are used to mirror real-world situations to test new policies and evaluate infrastructure changes. In practice, simulator selection has often been based on availability rather than on technical suitability, particularly for microscopic-scale applications. In this study, a quantitative methodology focusing on simulation runtime, memory usage, runtime consistency, travel time, safe gap distance, and scalability is proposed. A combined index was developed to assess simulators across different scales and traffic densities. VISSIM, SUMO, and MATSim were tested, and the results indicate that SUMO and MATSim demonstrate strong performance in runtime and memory usage. In large-scale scenarios, both simulators proved suitable for high-demand simulations, with MATSim exhibiting greater scalability. VISSIM matches real-world travel times more closely and fairly handles realistic safe gap distances, making it more suitable for less dense, detailed, microscopic simulations.