DECISION SUPPORT FOR DYNAMIC CITY TRAFFIC MANAGEMENT USING VEHICULAR COMMUNICATION

Jana Görmer, Jan Fabian Ehmke, Maksims Fiosins, Daniel Schmidt, Henrik Schumacher, Hugues Tchouankem

Abstract

In this paper, we present an integrated simulation approach featuring centralized and decentralized traffic management in urban areas. Our aim is to improve traffic flows by dynamic traffic management which is supported by vehicular communication interlinking centralized and decentralized decision making. We focus on traffic state estimation and the optimization of traffic lights as a central component to influence local traffic states, while individual traffic participants’ behavior is modeled by multiagent systems. Traffic participants achieve their individual goals by formation of groups and improving their knowledge about the road network by means of learning. Modeling of vehicular communication takes into account specific characteristics of urban areas, ensuring the realistic collection and dissemination of (de)centralized information. We provide a comprehensive microscopic traffic simulation framework featuring innovative functionality regarding dynamic traffic management, decentralized decision making as well as realistic communication modeling. To illustrate and validate our approach, we present a use case in a city scenario. Simulations are implemented based on the microscopic traffic simulator AIMSUN, which is significantly extended using the AIMSUN API.

References

  1. Agogino, A. and Tumer, K. (2004). Team formation in partially observable multi-agent systems. In Proceedings of the International Joint Conference on Neural Networks, Budapest, Hungary.
  2. Bergenthal, T., Frommer, A., and Paulerberg, D. (2004). Wege auf Graphen. Mathe Prisma: Fachbereich C / Mathematik der Bergischen Universitä t Wuppertal.
  3. Boltze, M. and Wolfermann, A. (2011). Der Einfluss von Zwischenzeiten auf die Kapazität von Knotenpunkten mit Lichtsignalanlage. HEUREKA 7811, Stuttgart, Germany.
  4. ETSI (2010). Intelligent Transport Systems (ITS); European profile standard for the physical and medium access control layer of Intelligent Transport Systems operating in the 5 GHz frequency band. ETSI ES 202 663 V1.1.0 (2010-01).
  5. FGSV (2001). Handbuch für die Bemessung von Straßenverkehrsanlagen HBS (Manual for the dimensioning of road infrastructure). FGSV-Verlag, Cologne, Germany.
  6. FGSV (2010). Richtlinien für Lichtsignalanlagen RiLSA (Guidelines for Traffic Signals). FGSV-Verlag, Cologne, Germany.
  7. Fiosins, M., Fiosina, J., Müller, J., and Görmer, J. (2011). Agent-based integrated decision making for autonomous vehicles in urban traffic. In Demazeau, Y., Pechoucek, M., Corchado, J., and Pérez, J., editors, Advances on Practical Applications of Agents and Multiagent Systems, volume 88 of Advances in Intelligent and Soft Computing, pages 173-178. Springer Berlin / Heidelberg.
  8. Shelby, S., Bullock, D., and Gettman, D. (2006). Transition methods in traffic signal control. Transportation Research Record: Journal of the Transportation Research Board, pages 130-140.
  9. Sommer, C., Eckhoff, D., German, R., and Dressler, F. (2010). A computationally inexpensive empirical model of ieee 802.11p radio shadowing in urban environments. In Technical Report CS-2010-06, Universität Erlangen-Nürnberg, Erlangen.
  10. Song, S. K., Han, S., and Youn, H. Y. (2007). A new agent platform architecture supporting the agent group paradigm for multi-agent systems. In IAT 7807: Proceedings of the 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, pages 399-402, Washington, DC, USA. IEEE Computer Society.
  11. Sutton, R. S. and Barto, A. G. (1998). Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning). The MIT Press.
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Paper Citation


in Harvard Style

Görmer J., Fabian Ehmke J., Fiosins M., Schmidt D., Schumacher H. and Tchouankem H. (2011). DECISION SUPPORT FOR DYNAMIC CITY TRAFFIC MANAGEMENT USING VEHICULAR COMMUNICATION . In Proceedings of 1st International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-8425-78-2, pages 327-332. DOI: 10.5220/0003598503270332


in Bibtex Style

@conference{simultech11,
author={Jana Görmer and Jan Fabian Ehmke and Maksims Fiosins and Daniel Schmidt and Henrik Schumacher and Hugues Tchouankem},
title={DECISION SUPPORT FOR DYNAMIC CITY TRAFFIC MANAGEMENT USING VEHICULAR COMMUNICATION},
booktitle={Proceedings of 1st International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2011},
pages={327-332},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003598503270332},
isbn={978-989-8425-78-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of 1st International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - DECISION SUPPORT FOR DYNAMIC CITY TRAFFIC MANAGEMENT USING VEHICULAR COMMUNICATION
SN - 978-989-8425-78-2
AU - Görmer J.
AU - Fabian Ehmke J.
AU - Fiosins M.
AU - Schmidt D.
AU - Schumacher H.
AU - Tchouankem H.
PY - 2011
SP - 327
EP - 332
DO - 10.5220/0003598503270332