Abstract
Traffic flow is a specific line of moving vehicles where the degree of interaction between the factors of the flow is extremely high. The vehicles’ interaction is a consequence of human imperfection in driving. For that reason, the determination of traffic flow parameters depends on the drivers’ assessment. That is, their abilities to receive signals from other traffic participants about their manner of moving and the regime. The artificial intelligence hybrid Markovian ants in Queuing System has been applied in the traffic flow research in this paper. The driver’s human intelligence has been substituted by Swarm intelligence. The analysed entropy of the pheromone signal among the ants in a column is analogue to the entropy of signals among successive vehicles in a traffic flow.
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References
Kinzer, J.P.: Application of The Theory of Probability to Problems of Highway Traffic, B.C.E. Thesis, Polytechnic Institute of Brooklyn, Proceedings Institute Traffic Engineering (1933)
Adams, W.F.: Road Traffic Considered as A Random Series. J. Institute Civil Engineering 4 (1936)
Greenshields, B.D., Shapiro, D., Ericksen, E.L.: Traffic Performance at Urban Street Intersections, Technical Report No. 1, Yale Bureau of Highway Traffic, New Haven, Conn. (1947)
Mahnkea, R., Kaupužsb, J., Lubashevskyc, I.: Probabilistic description of traffic flow. Physics Reports 408, 1–130 (2005)
Pipes, L.A.: Vehicle acceleration in the hydrodynamic theory of traffic flow. Transp. Res. 3, 229–234 (1969)
Sun, D.-H., et al.: Effect of looking backward on traffic flow in an extended multiple car-following model. Physica A (2010), doi:10.1016/j.phusa.2010.10.016
Tang, T.Q., Huang, H.J., Zhao, S.G., Shang, H.Y.: A new dynamic model for heterogeneous traffic flow. Physics Letters A 373, 2461–2466 (2009)
Jin, S., Wang, D., Tao, P., Li, P.: Non-lane-based full velocity difference car following model. Physica A: Statistical Mechanics and its Applications 389, 4654–4662 (2010)
Teodorović, D.: Swarm intelligence systems for transportation engineering: Principles and applications. Transportation Research Part C: Emerging Technologies 16, 651–667 (2008)
John, A., Schadschneider, A., Chowdhury, D., Nishinari, K.: Characteristics of ant-inspired traffic flow. Swarm Intelligence 2, 25–41 (2008)
Traffic flow theory A state-of-the-Art Report, Revised 2001, Organized by the Committee on Traffic Flow Theory and Characteristics (AHB 45), pp. 2-1 (2001)
Kuzović, L., Bogdanović, V.: Teorija saobraćajnog toka, Fakultet tehničkih nauka, Novi Sad, p. 104 (2010)
Traffic flow theory A state-of-the-Art Report, Revised 2001, Organized by the Committee on Traffic Flow Theory and Characteristics (AHB 45), pp. 2-5 (2001)
Badr, A., Fahmy, A.: A proof of convergence for Ant algorithms. Information Sciences 160, 267–279 (2004)
Yin, H., Wong, S.C., Xu, J., Wong, C.K.: Urban traffic flow prediction using a fuzzy-neural approach. Transportation Research Part C: Emerging Technologies 10, 85–98 (2002)
Tanackov, I., Simić, D., Sremac, S., Tepić, J., Kocić-Tanackov, S.: Markovian ants in a queuing system. In: Graña Romay, M., Corchado, E., Garcia Sebastian, M.T. (eds.) HAIS 2010. LNCS, vol. 6076, pp. 32–39. Springer, Heidelberg (2010)
Menendez, M.L.: Shannon’s entropy in exponential families: Statistical applications. Applied Mathematics Letters 13, 37–42 (2000)
Abraham, A., Corchado, E., Corchado, J.M.: Hybrid learning machines. Neurocomputing 72, 2729–2730 (2009)
Corchado, E., Abraham, A., de Carvalho, A.: Hybrid intelligent algorithms and applications. Information Science 180, 2633–2634 (2010)
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Tanackov, I., Bogdanović, V., Tepić, J., Sremac, S., Ruškić, N. (2011). The Application of Artificial Intelligence Hybrid in Traffic Flow. In: Corchado, E., Kurzyński, M., Woźniak, M. (eds) Hybrid Artificial Intelligent Systems. HAIS 2011. Lecture Notes in Computer Science(), vol 6678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21219-2_12
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DOI: https://doi.org/10.1007/978-3-642-21219-2_12
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