Accelerating Distributed Urban Traffic Simulation via Enhanced Stale Synchronous Parallelism

Modeling urban mobility behaviours with micro-scopic traffic flow simulation is now crucial for studying intel-ligent urban decision-making algorithms, such as traffic light control and road congestion charging. However, in urban-scale traffic environments, simulation is computationally intensive. Most existing studies use distributed traffic simulations based on the Bulk Synchronous Parallel (BSP) model, leading to significant time and data transfer costs due to the need for coordination and data synchronization. To address these issues, we propose an enhanced Stale Synchronous Parallel (ESSP) model. Our model reduces the waiting time of the simulation compute nodes, and we design it to control and measure errors during simulation. We also develop a distributed traffic simulator to validate our model, and the results show a performance improvement of 30% to 50% compared to conventional synchronization methods.