Abstract
In city traffic flow, vehicles driven by human interact with each other with velocity fluctuations. We simulate the such city traffic and analyze it. It should be important to research the relation between traffic signals and drivers’ strategies. Then, we prepare two CML(coupled map lattice) models to treat complex traffic system with varying their characteristics, and research the effects of traffic signals. Each model has different strategies to avoid collision between vehicles. The one is the “Mixture Model” strategy which changes vehicles’ running dynamics when their gaps have gotten narrow, and the other is the “Tracking Model” strategy which decelerate vehicles’ goal velocities to follow previous one when their gaps have gotten narrow. We compare these CML models on a oneway traffic lane under the aperiodic boundary condition. “The transition point of the jam” which separates between “free flow phase” and “congestion phase” is observed. In free flow phase, major differences are not confirmed between these models. But, when it gets congested, each model takes on dissimilar complex features stem from difference of strategies. Additionally, we research effect of signal control parameters in free flow phase. We observed that whole performance is improved as cycle length is getting shorter, at that time offset can’t be very effective. When cycle length is long, whole performance is not very lower if offset is proper.
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© 2005 Springer-Verlag Berlin Heidelberg
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Hamaoka, K., Wada, M., Ishimura, K. (2005). Coupled Map Lattice Model based on Driving Strategy for City Traffic Simulation. In: Abraham, A., Dote, Y., Furuhashi, T., Köppen, M., Ohuchi, A., Ohsawa, Y. (eds) Soft Computing as Transdisciplinary Science and Technology. Advances in Soft Computing, vol 29. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32391-0_120
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DOI: https://doi.org/10.1007/3-540-32391-0_120
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25055-5
Online ISBN: 978-3-540-32391-4
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