Multi-Thread State Update Schemes for Microscopic Traffic Simulation

Microscopic traffic simulation is an essential tool for the evaluation of intelligent transportation systems (ITS). With the increasing complexity of ITS applications, higher-detail simulation models, and the need to analyze large-scale scenarios, simulation run-times can grow exceedingly large. One way to counter this problem is the use of parallel computing techniques, such as shared-memory multi-thread parallelism. While the foundations of parallel traffic simulation are well-known, the effects of different synchronization and agent-update mechanisms on simulation performance have not been explored systematically. In this paper, we first analyze the common properties of models used in microscopic traffic simulation to understand the impact of their data dependencies. We discuss synchronous and asynchronous agent update schemes and compare them in terms of performance and requirements. We conclude that although it requires more memory and additional conflict handling, the synchronous agent-state updating approach is favourable in terms of scalability.