One of the major trends in traffic simulations is to take into account microscopic aspects of traffic flows at the street level. Multi-agent models such as MATSim (multi-agent transport simulation) have been highlighted for recent years as a solution to address these complex and microscopic simulation requirements. They are viewed as an emergent and collective behavior of agents, (i.e., vehicles). However, as the simulations scale up, their computational requirements could get increased beyond the capability of a single CPU and thus should be fulfilled with parallelization. Multithreading can partially contribute to parallelization by utilizing multi-cores, but cannot give full scalability of both CPU power and memory space. To support distributed-memory parallelization for multi-agent models, we have developed the MASS (multi-agent spatial simulation) library. This paper presents how to parallelize MATSim using the MASS library and demonstrates the library's portability and execution performance in practical transport simulations.
['Zhiyuan Ma', 'Munehiro Fukuda']
A multi-agent spatial simulation library for parallelizing transport simulations