Characteristic of Transportation Network with LOGIT Model

In this research, we employ LOGIT model, which is widely used in statistical field, to describe the individual decision-making process instead of shortest path rule in transportation network models. With the idea of congestion effects, we can derive a stationary flow distribution solution analytically under any given network structure which is solved by a numeric iterative approach approximately. Based on that, simulations are made to compare the cumulative the difference of load distribution under shortest path law and our LOGIT law. Meanwhile, four different classes of networks are tested to uncover the relationship between traffic flow and topological structures under LOGIT law. The results indicated that random network and scale-free network outperform than the others two in the measurement of TSC.