OPEN ACCESS
Microscopic simulations of road traffic are a typical application domain for Multi- Agent Systems. Indeed, the individual-based approach allows to take into account the diversity of behaviors so as to consider real situations. More recently, geographical databases provide environmental information under open formats, which offers the opportunity to design agentbased traffic simulators which can be continuously informed of changes in traffic conditions. The use of such data, together with the adaptability of MAS, allows the realization of decision support systems that are able to integrate environmental and behavioral modifications in a direct way; and compare various scenarios built from different hypothesis in terms of actors, behaviors, environment and flow. We describe here a process which leads to the development of such a tool
multi-agent simulation, GIS, road traffic, traffic generator
Al-Zinati M., Araujo F., Kuiper D., Valente J.,Wenkstern R. (2013). DIVAs 4.0: A multi-agent based simulation framework. In IEEE/ACM 17th Int. Symp. on Distributed Simulation and Real Time Applications, p. 105-114.
Bazzan A., Klügl F. (2014, 1). A review on agent-based technology for traffic and transportation. The Knowledge Engineering Review, vol. FirstView, p. 1–29.
Bonhomme A., Mathieu P., Picault S. (2015). TrafficGen: a flexible tool for informing agentbased traffic simulations with open data. In Y. Demazeau, K. S. Decker, J. Bajo Pérez, F. de la Prieta (Eds.), Proc. of the 13th Int. Conf. on Practical Applications of Agents and Multi-Agent Systems (PAAMS’2015), vol. 9086, p. 259–262. Springer. (Demonstration paper)
Bonhomme A., Mathieu P., Picault S. (2016). A versatile multi-agent traffic simulator framework based on real data. International Journal on Artificial Intelligence Tools, vol. 25, no 1, p. 20.
Bonte L., Espié S., Mathieu P. (2007). Virtual lanes interest for motorcycles simulation. In 5th European Workshop on Multi-Agent Systems (EUMAS’07), p. 580–596. ATIA.
Bonte L., Mathieu P., Espié S. (2006). Modélisation et simulation des usagers des deux-roues motorisés dans archisim. In V. Chevrier (Ed.), 14e journées francophones sur les systèmes multi-agents (jfsma), p. 31–44. Hermès.
Bourbakis N. (1997). A traffic priority language for collision-free navigation of autonomous mobile robots in dynamic environments. Trans. Sys. Man Cyber. Part B, vol. 27, no 4, p. 573–587.
Bourbakis N., Findler M. (2001). Smart cars as autonomous intelligent agents. In IEEE 13th Int. Conf. on Tools with Artificial Intelligence (ICTAI’2001), p. 25–32. IEEE.
Bourgois L., Saunier J., Auberlet J.-M. (2012). Towards contextual goal-oriented perception for pedestrian simulation. In F. J., A. Fred (Eds.), Proceedings of the 4th International Conference on Agents and Artificial Intelligence (ICAART), p. 197–202. SciTePress.
Champion A., Mandiau R., Kolski C., Heidet A., Kemeny A. (1999). Traffic generation with the SCANeRTM simulator: towards a multi-agent architecture. In Driving Simulation Conference, p. 311–324.
Chen B., Cheng H. (2010). A review of the applications of agent technology in traffic and transportation systems. Trans. Intell. Transport. Sys., vol. 11, no 2, p. 485–497.
Doniec A., Mandiau R., Piechowiak S., Espié S. (2008). A behavioral multi-agent model for road traffic simulation. J. Eng. Appl. of AI, p. 1443–1454.
Dresner K., Stone P. (2007). Sharing the road: Autonomous vehicles meet human drivers. In 20th Int. Joint Conf. on Artificial Intelligence (IJCAI’2007), p. 1263–1268.
Espié S., Saad F., Schnetzler B., Bourlier F., Djemane N. (1994). Microscopic traffic simulation and driver behaviour modelling: the ARCHISIM project. In Conf. Road Safety in Europe and Strategic Highway Research Program (SHRP), p. 22–31.
Gibson J. (1979). The ecological approach to visual perception. Hillsdale. Girres J.-F., Touya G. (2010). Quality assessment of the french OpenStreetMap dataset. Transactions in GIS, vol. 14, no 4, p. 435–459.
Koenig S., Likhachev M. (2005). Fast replanning for navigation in unknown terrain. Transactions on Robotics, vol. 21, no 3, p. 354–363.
Krajzewicz D., Erdmann J., Behrisch M., Bieker L. (2012, December). Recent development and applications of SUMO - Simulation of Urban MObility. Int. J. on Advances in Systems and Measurements, vol. 5, no 3–4, p. 128–138.
Kubera Y., Mathieu P., Picault S. (2010). Everything can be agent! In W. van der Hoek et al. (Eds.), 9th Int. Joint Conf. on Auton. Agents and Multi-Agent Systems (AAMAS), p. 1547–1548. IFAAMAS.
Kubera Y., Mathieu P., Picault S. (2011). IODA: An interaction-oriented approach for multiagent based simulations. J. of Auton. Agents and Multi-Agent Systems, vol. 23, no 3, p. 303–343.
Kuiper D., Wenkstern R. (2014). Agent vision in multi-agent based simulation systems. J. of Auton. Agents and Multi-Agent Systems, p. 1–31.
Lacroix B., Mathieu P., Kemeny A. (2009). Generating various and consistent behaviors in simulations. In Y. Demazeau et al. (Eds.), Proceedings of the 7th International conference on Practical Applications of Agents and Multi-Agents Systems (PAAMS’2009), vol. 55, p. 110–119. Springer.
Lacroix B., Mathieu P., Kemeny A. (2013). Formalizing the construction of populations in multi-agent simulations. J. Eng. App. of AI, vol. 26, no 1, p. 211–226.
Mandiau R., Champion A., Auberlet J.-M., Espié S., Kolski C. (2008). Behaviour based on decision matrices for a coordination between agents in a urban traffic simulation. Appl. Intell., vol. 28, no 2, p. 121–138.
Mathieu P., Picault S. (2013). From real purchase to realistic populations of simulated customers. In Y. Demazeau et al. (Eds.), 11th Int. Conf. on Practical Applications of Agents and Multi-Agent Systems (PAAMS), vol. 7879, p. 216–227. Springer.
Mokbel M., Alarabi L., Bao J., Eldawy A., Magdy A., Sarwat M. et al. (2013). MNTG: An extensible web-based traffic generator. In 13th Int. Symp. on Spatial and Temporal Databases (SSTD), vol. 8098, p. 38-55. Springer.
Osogami T., Imamichi T., Mizuta H., Morimura T., Raymond R., Suzumura T. et al. (2012). IBM Mega Traffic Simulator. Rapport technique. IBM.
Picault S., Mathieu P. (2011). An interaction-oriented model for multi-scale simulation. In T. Walsh (Ed.), 22nd Int. Joint Conf. on Artificial Intelligence (IJCAI’2011), p. 332–337.
Raney B., Nagel K. (2006). An improved framework for large-scale multi-agent simulations of travel behavior. Towards better performing European Transportation Systems, p. 305–347.
Taillandier P., Vo D.-A., Amouroux E., Drogoul A. (2012). GAMA: A simulation platform that integrates geographical information data, agent-based modeling and multi-scale control. In N. Desai et al. (Eds.), Principles and Practice of Multi-Agent Systems, vol. 7057, p. 242–258. Springer.
Tlig M., Buffet O., Simonin O. (2012). Cooperative behaviors for the self-regulation of autonomous vehicles in space sharing conflicts. In IEEE 24th International Conference on Tools with Artificial Intelligence (ICTAI), p. 1126-1132. IEEE.
Visvalingam M., Wyatt J. (1993, 5). Line generalization by repeated elimination of points. Cartographic Journal, vol. 30, no 1, p. 46–51.
Wilensky U. (1999). Netlogo. Consulté sur http://ccl.northwestern.edu/netlogo/Yang Q. (1997). Simulation laboratory for evaluating dynamic traffic management systems. Thèse de doctorat, Massachusetts Institute of Technology.