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Published in:
2016 | OriginalPaper | Chapter
Investigation on Cooperative Avoiding Behaviour in Bi-directional Flow
Author : Daichi Yanagisawa
Published in: Traffic and Granular Flow '15
Publisher: Springer International Publishing
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Abstract
We have introduced an evolutionary game dynamics to a one-dimensional cellular automaton to investigate evolution and maintenance of cooperative avoiding behaviour in bidirectional flow of self-driven particles. In our model, there are two kinds of particles, which are right-going particles and left-going particles. Since the model is one dimension, they often face opponent particles. In order to avoid conflicts, the particles try to avoid their opponents by swerving to the right or left stochastically. The particles have a memory and reinforce their preference after their successful avoidance. Result of our simulation indicates that cooperative avoiding behaviour is achieved, i.e., swerving directions of the particles are unified, when the density of particles is close to 1/2 and the memory-loss rate is small. Application of our research will be useful to study evolution and maintenance of cooperative avoiding behaviour in pedestrian dynamics.