Research on Equilibrium Allocation Method of Urban Traffic Network based on Complex Network

Abstract

The increase of traffic demand leads to the continuous expansion and complexity of urban traffic network, and the imbalance between supply and demand of local road network can easily lead to the failure of the whole network state. Based on complex network and big data technology, analyzing the proximity characteristics between nodes of urban road network, this study designs and implements a traffic control method aiming at regional capacity balance. By using the historical and real-time urban traffic data, construct the relationship function between regional in transit traffic volume and traffic status indicators to influence the traffic allocation of key adjacent regions and continuously reduce the traffic status of congested regions. In the actual traffic control process, when the regional short-term traffic volume approaches or exceeds the carrying capacity of the road network, the continuous deterioration of traffic conditions in congested areas can be effectively restrained by continuously and dynamically adjusting the incoming traffic volume in key adjacent areas, distributing or guiding the traffic flow to other roads. Finally, contruct a simulation verification model based on the actual road network of a city. The comparison of simulation data shows that the difference of traffic flow between the core area and the adjacent area is reduced by 15%, and the duration of traffic congestion in the target area is reduced by 12%.