  The optimal information feedback has a significant effect on many
socioeconomic systems like stock market and traffic systems aiming to make full
use of resources. In this paper, we studied dynamics of traffic flow with
real-time information provided and the influence of a feedback strategy named
prediction feedback strategy is introduced, based on a two-route scenario in
which dynamic information can be generated and displayed on the board to guide
road users to make a choice. Our model incorporates the effects of adaptability
into the cellular automaton models of traffic flow and simulation results
adopting this optimal information feedback strategy have demonstrated high
efficiency in controlling spatial distribution of traffic patterns compared
with the other three information feedback strategies, i.e., vehicle number and
flux.
