Abstract
Multiagent-based simulations are a key part of several research fields. Multiagent-based simulations yield multiagent societies that well reproduce human societies, and so are seen as an excellent tool for analyzing the real world. A multiagent-based simulation allows crowd behavior to emerge through interactions among agents where each agent is affected by the emerging crowd behavior. The interaction between microscopic and macroscopic behaviors has long been considered an important issue, termed the “micro-macro problem”, in the field of sociology, but research on the issue is still premature in the engineering domain. We are focusing on citywide traffic as a target problem and are attempting to realize mega-scale multiagent-based traffic simulations. While macro-level simulations are popular in the traffic domain, it has been recognized that micro-level analysis is also beneficial. However, there is no software platform that can realize analyses based on both micro and macro viewpoints due to implementation difficulties. In this paper, we propose a traffic simulation platform that can execute citywide traffic simulations that include driving behavior models. Our simulation platform enables the introduction of individual behavior models while still retaining scalability.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Jacyno, M., Bullock, S., Luck, M., Payne, T.: Emergent service provisioning and demand estimation through self-organizing agent communities. In: Proceedings of the 8th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), pp. 481–488 (2009)
Tesfatsion, L.S.: Introduction to the special issue on agent-based computational economics. Journal of Economic Dynamics & Control 25(3-4), 281–293 (2001)
Vasirani, M., Ossowski, S.: A market-inspired approach to reservation-based urban road traffic management. In: Proceedings of the 8th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), pp. 617–624 (2009)
Balmer, M., Cetin, N., Nagel, K., Raney, B.: Towards truly agent-based traffic and mobility simulations. In: 3rd International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004, pp. 60–67 (2004)
Halle, S., Chaib-draa, B.: A collaborative driving system based on multiagent modelling and simulations. Journal of Transportation Research Part C 13, 320–345 (2005)
Panait, L.: A pheromone-based utility model for collaborative foraging. In: Proceedings of the 3rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2004), pp. 36–43 (2004)
Ishida, T., Nakajima, Y., Murakami, Y., Nakanishi, H.: Augmented experiment: Participatory design with multiagent simulation. In: International Joint Conference on Artificial Intelligence (IJCAI 2007), pp. 1341–1346 (2007)
Tanaka, Y., Nakajima, Y., Hattori, H., Ishida, T.: A driver modeling methodology using hypothetical reasoning for multiagent traffic simulation. In: Ghose, A., Governatori, G., Sadananda, R. (eds.) PRIMA 2007. LNCS (LNAI), vol. 5044, pp. 278–287. Springer, Heidelberg (2009)
Hattori, H., Nakajima, Y., Ishida, T.: Agent modeling with individual human behaviors. In: Proceedings of the 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), pp. 1369–1370 (2009)
Moyaux, T., Chaib-draa, B., D’Amours, S.: Multi-agent simulation of collaborative strategies in a supply chain. In: 3rd International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004, pp. 52–59 (2004)
Yamashita, T., Izumi, K., Kurumatani, K., Nakashima, H.: Smooth traffic flow with a cooperative car navigation system. In: AAMAS 2005, pp. 478–485. ACM Press, New York (2005)
Poole, D.: Theorist: A logical reasoning system for defaults and diagnosis. In: The Knowledge Frontier. Springer, Heidelberg (1987)
Murakami, Y., Sugimoto, Y., Ishida, T.: Modeling human behavior for virtual training systems. In: AAAI 2005, pp. 127–132 (2005)
Illenberger, J., Flotterod, G., Nagel, K.: Enhancing matsim with capabilities of within-day re-planning. In: Intelligent Transportation Systems Conference (ITSC 2007), pp. 94–99 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Nakajima, Y., Nakai, Y., Hiromitsu, H., Ishida, T. (2009). Wide-Area Traffic Simulation Based on Driving Behavior Model. In: Yang, JJ., Yokoo, M., Ito, T., Jin, Z., Scerri, P. (eds) Principles of Practice in Multi-Agent Systems. PRIMA 2009. Lecture Notes in Computer Science(), vol 5925. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11161-7_32
Download citation
DOI: https://doi.org/10.1007/978-3-642-11161-7_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11160-0
Online ISBN: 978-3-642-11161-7
eBook Packages: Computer ScienceComputer Science (R0)