Hideki Fujii*, Yuta Ushimaru, Tomonori Yamada, Shinobu Yoshimura
The International Conference on Computational & Experimental Engineering and Sciences, Vol.21, No.3, pp. 63-63, 2019, DOI:10.32604/icces.2019.05442
Abstract In order to evaluate transportation policies quantitatively, virtual social experiments using traffic simulators are adequate. In particular, simulators with features of both precision and scalability are preferable for applications to real-world and wide-spread traffic phenomena. In this research, we tried to parallelize a multi-agent-based traffic simulator (ADVENTURE_Mates) and enhance its parallelization performance. In the simulator, a road map is modeled as a graph and cars are modeled as autonomous agents. A car agent acquires information from its circumference (other cars, traffic lights, etc.), makes a decision autonomously, and acts based on the decision. The precision… More >