Title: Coordination game in bidirectional flow,
Abstract: We have introduced evolutionary game dynamics to a one-dimensional
cellular-automaton to investigate evolution and maintenance of cooperative
avoiding behavior of self-driven particles in bidirectional flow. In our model,
there are two kinds of particles, which are right-going particles and
left-going particles. They often face opponent particles, so that they swerve
to the right or left stochastically in order to avoid conflicts. The particles
reinforce their preferences of the swerving direction after their successful
avoidance. The preference is also weakened by memory-loss effect.
Result of our simulation indicates that cooperative avoiding behavior 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.
Furthermore, when the right-going particles occupy the majority of the system,
we observe that their flow increases when the number of left-going particles,
which prevent the smooth movement of right-going particles, becomes large. It
is also investigated that the critical memory-loss rate of the cooperative
avoiding behavior strongly depends on the size of the system. Small system can
prolong the cooperative avoiding behavior in wider range of memory-loss rate
than large system.