A Stackelberg Game and Improved Logit Model based traffic guidance model

In order to improve the traffic guidance efficiency and the transportation quality of the road network, a traffic guidance model called Stackelberg-Logit Game Model is presented. It is a Stackelberg Game Model between traffic manager and travelers which combined two traffic assignment principles, the User Equilibrium and the System Optimum. Meanwhile, the Improved Logit Model is employed to calculate the probability of path selection so as to make travelers´ path selection behaviors better fit the real world. In order to present the dynamics and time variability of the traffic guidance system, the traffic demand uncertainty is introduced in the simulation experiment and also the Rolling Horizon Implementation to the solution algorithm. The simulation experimental results show that the presented game model is able to improve the vehicle speed, realize the traffic flow equilibrium and optimize the global road network performance.