Abstract
The paper presents a genetic algorithm approach for a traffic light optimization problem. The algorithm was tested using Traffic Simulation Framework, a quite advanced software tool for simulating and investigating vehicular traffic in cities.
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
Barlovic, R., Huisinga, T., Schadschneider, A., Schreckenberg, M.: Adaptive Traffic Light Control in the ChSch Model for City Traffic. In: Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multi Agent Systems- AAMAS-2006, part 3, pp. 331–336 (2005)
Muller-Schloer, C.: Organic Computing - On the Feasibility of Controlled Emergence. In: CODES+ISSS 2004 Proceedings of the International Conference on Hardware/Software Codesign and System Synthesis, pp. 2–5 (2004)
Chowdhury, D., Schadschneider, A.: Self-organization of traffic jams in cities: effects of stochastic dynamics and light periods. Physical Review E (Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics) 59(2), 1311–1314 (1999)
Chen, S.W., Yang, C.B., Peng, Y.H.: Algorithms for the Traffic Light Setting Problem on the Graph Model. In: Proc. of the 12th Conference on Artificial Intelligence and Applications, TAAI (2007)
Fehon, K.: Adaptive Traffic Signals. In: ITE District 6 2004 Annual Meeting (2004)
Favilla, J., Machion, A., Gomide, F.: Fuzzy traffic control: Adaptive Strategy. In: Proc. 2nd IEEE Int. Conf. on Fuzzy Systems, San Francisco, CA, pp. 1371–1376 (March 1993)
Gora, P.: Adaptive planning of vehicular traffic, Master Thesis. University of Warsaw (2010)
Horynski, M.: Intelligent Electric Systems in Urban Traffic Control. TEKA Kom. Mot. Energ. Roln.- OL PAN 7, 110–115 (2007)
International Conference on Data Mining (2010), http://datamining.it.uts.edu.au/icdm10/
Gora, P.: Traffic Simulation Framework - a cellular automaton-based tool for simulating and investigating real city traffic. In: Recent Advances in Intelligent Information Systems, pp. 641–653, ISBN 978-83-60434-59-8
Wiering, M., van Veenen, J., Vreeken, J., Koopman, A.: Intelligent Traffic Light Control, Technical Report UU-CS-2004-029. University Utrecht (2004)
Kwasnicka, H., Stanek, M.: Genetic Approach to Optimize Traffic Flow by Timing Plan Manipulation. In: Yuehui, C., Abraham, A. (eds.) ISDA 2006 Proceedings, vol. II, pp. 1171–1176. IEEE Computer Society, Los Alamitos (2006)
Kuyer, L., Whiteson, S., Bakker, B., Vlassis, N.: Multiagent Reinforcement Learning for Urban Traffic Control Using Coordination Graphs. In: Daelemans, W., Goethals, B., Morik, K. (eds.) ECML PKDD 2008, Part I. LNCS (LNAI), vol. 5211, pp. 656–671. Springer, Heidelberg (2008)
Qi, Y., Koutsopoulos, H.N., Ben-Akiva, M.E.: A Simulation Laboratory for Evaluating Dynamic Trac Management Systems. Center for Transportation Studies. Massachusetts Institute of Technology, TRB Paper No. 00-1688 (1999)
.NET Framework Platform: Developer Center, http://msdn.microsoft.com/en-us/netframework/aa496123
Nagel, K., Schreckenberg, M.: A cellular automaton model for freeway traffic. Journal de Physique, 2221–2229(1992)
OpenTreetMap - project of editable map of a world, http://www.openstreetmap.org/
Traffic Simulation Framework - a tool for simulating and investigating vehicular traffic, http://www.mimuw.edu.pl/~pawelg/TSF
Priyono, A., Ridwan, M., Alias, A.J., Rahmat, R., Hassan, A., Ali, M.: Application of LVQ neural network in real-time adaptive traffic signal control. Journal Teknologi 42(B), 29–44 (2005)
Prothmann, H., Rochner, F., Tomforde, S., Branke, J., Müller-Schloer, C., Schmeck, H.: Organic Control of Traffic Lights. In: Rong, C., Jaatun, M.G., Sandnes, F.E., Yang, L.T., Ma, J. (eds.) ATC 2008. LNCS, vol. 5060, pp. 219–233. Springer, Heidelberg (2008)
Schadschneider, A., Chowdhury, D., Brockfeld, E., Klauck, K., Santen, L., Zittartz, J.: A new cellular automata model for city traffic. In: Traffic and Granular Flow 1999 (1999)
Schadschneider, A.: The Nagel-Schreckenberg model revisited. The European Physical Journal B 10(3), 573–582 (1999)
Singh, L., Tripathi, S., Arora, H.: Time Optimization for Traffic Signal Control Using Genetic Algorithm. International Journal of Recent Trends in Engineering 2(2) (November 2009)
Sha’aban, J., Tomlinson, A., Heydecker, B.G., Bull, L.: Adaptive traffic control using evolutionary algorithms. In: Dell’Orco, M., Ottomanelli, M. (ed.) Procs 9th Meeting of the EURO Working Group on Transportation, Bari, Italy (June 2002)
de Oliveira, D., Bazzan, A.L.C.: Traffic Lights Control with Adaptive Group Formation Based on Swarm Intelligence. In: Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds.) ANTS 2006. LNCS, vol. 4150, pp. 520–521. Springer, Heidelberg (2006)
Turky, A.M., Ahmad, M.S., Yusoff, M.Z.M., Hammad, B.T.: Using genetic algorithm for traffic light control system with a pedestrian crossing. In: Wen, P., Li, Y., Polkowski, L., Yao, Y., Tsumoto, S., Wang, G. (eds.) RSKT 2009. LNCS, vol. 5589, pp. 512–519. Springer, Heidelberg (2009)
Gora, P.: Complex process modeling based on vehicular traffic simulation, Master Thesis. University of Warsaw (2010)
IEEE ICDM Contest: TomTom Traffic Prediction for Intelligent GPS Navigation, http://tunedit.org/challenge/IEEE-ICDM-2010
Wurtz, R.P.:Organic Computing. Springer, Heidelberg, ISBN: 978-3-540-77656-7
Yang, C.B., Yeh, Y.J.: The model and properties of the traffic light problem. In: Proc. of International Conference on Algorithms, Kaohsiung, Taiwan, pp. 19–26 (December 1996)
Zhiyong, L.: A Survey of Intelligence Methods in Urban Traffic Signal Control. In: Proc. of American Control Conference (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Gora, P. (2011). A Genetic Algorithm Approach to Optimization of Vehicular Traffic in Cities by Means of Configuring Traffic Lights. In: Ryżko, D., Rybiński, H., Gawrysiak, P., Kryszkiewicz, M. (eds) Emerging Intelligent Technologies in Industry. Studies in Computational Intelligence, vol 369. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22732-5_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-22732-5_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22731-8
Online ISBN: 978-3-642-22732-5
eBook Packages: EngineeringEngineering (R0)