城市路网交通流的数学模型及仿真

Mathematical Model and Simulation of Urban Road Network Traffic Flow

提出了一种基于改进的蜂群智能算法的路径选择分配方法。首先利用双向信息传递技术得到实时路段的交通流状况,将路段的通行能力分级,通过模仿蜂群个体的局部寻优比较得到最优解,具有较快的收敛速度。仿真结果表明,提出的模型和算法不仅能有效解决城市交通路径分配问题,而且计算复杂度较低,算法的计算效率较高,为提高交通路网的效率及实用性和有效性提供了依据。

Urban traffic congestion is complex and changeable, and the choice of path is difficult for users. In order to optimize the distribution of urban traffic path, and solve the problem that existing traffic flow model algorithm has large computation and long operation time, an improved swarm intelligence algorithm based on improved swarm is proposed.Two way information transfer technology is applied to get the real-time traffic flow status.and the traffic capacity is graded. The best solution is obtained by imitating the local optimization of the bee colony, which has a faster convergence speed.The simulation results show that the proposed models and algorithms can not only solve the problem of urban traffic assignment effectively, but also have low computational complexity and high computational efficiency, which indicates that the improved algorithm provides a basis for improving the efficiency and practicability and effectiveness of the road network.