  This paper presents an evolution model of weighted networks in which the
structural growth and weight dynamics are driven by human behavior, i.e.
passenger route choice behavior. Transportation networks grow due to people's
increasing travel demand and the pattern of growth is determined by their route
choice behavior. In airline networks passengers often transfer from a third
airport instead of flying directly to the destination, which contributes to the
hubs formation and finally the scale-free statistical property. In this model
we assume at each time step there emerges a new node with m travel
destinations. Then the new node either connects destination directly with the
probability p or transfers from a third node with the probability 1-p. The
analytical result shows degree and strength both obey power-law distribution
with the exponent between 2.33 and 3 depending on p. The weights also obey
power-law distribution. The clustering coefficient, degree assortatively
coefficient and degree-strength correlation are all dependent on the
probability p. This model can also be used in social networks.
