Vehicles Congestion Control in Transport Networks Using an Adaptive Weight Model

This paper proposed an adaptive weight congestion control model in a vehicle transport network. Our focus was to construct a quantitative index series to describe the network congestion distribution, and to shunt vehicles on seriously congested links based on such index sequence. We achieved this goal by combing both feedback and iteration strategy in the congestion control field. First, we developed an agent based model which captured the nonlinear feedback mechanism between the vehicle routing behavior and the road congestion state. Then, the model implemented an adaptive intersection weight adjustment mechanism based on the evolutionary congestion degree of the nearby links, through which to achieve congestion distribution evaluation and network congestion control at the same time. The simulation results verified the validity of our model for congestion control under predefined networks, and proved an applicability of the intersection weight sequence as a measurement for the congestion degree and distribution of road networks.