An equilibrium assignment of mixed traffic flow at intersections based on fuzzy ant colony algorithm

Equilibrium traffic flow refers to the reasonable organization of traffic flow so that it is evenly distributed on the road network to avoid traffic congestion and congestion in local sections and periods. It is of great significance to control and regulate the traffic flow in different time and space to evenly distribute on the road network and avoid traffic congestion and congestion. In order to overcome low allocation accuracy and long allocation time in traditional methods, an equilibrium assignment method of mixed traffic flow at intersections based on fuzzy ant colony algorithm is proposed. Firstly, the mixed traffic flow track data at the intersection is obtained through the monocular camera, and the data is preprocessed. Then, the characteristics of mixed traffic flow at the intersection are analyzed, and the hidden Markov model is used to distinguish the operation state of mixed traffic at the intersection. Finally, a multi-objective optimization function for the balanced distribution of mixed traffic flow at the intersection is established, and the ant colony algorithm is used to solve the multi-objective optimization function to obtain the balanced distribution strategy of traffic flow. The experimental results show that the proposed method has high accuracy and short allocation time for mixed traffic flow equilibrium allocation at intersections.