Intelligent Urban Traffic Orbit Current Limiting Model Based on Improved Ant Colony Algorithm

With the development of the economy and society and the accelerating pace of life, people have higher travel requirements. Compared with the traditional urban transportation ways, the subway has the advantages of larger passenger capacity and higher efficiency. Besides, the subway can also alleviating traffic congestion on the ground and reducing environmental pollution. Therefore, the development of underground urban rail transit has become a major trend in the world. However, some problems need to be solved, such as passengers' travel routes choosing and the government's guidance on peak traffic flow, due to the large correlation between rail transit lines, the sharp increase in traffic volume during peak periods, and the major differences in passenger flow between the various sections. Taking Beijing urban rail as an example, this paper analyzed the travel data of each station in some time periods, established the corresponding optimization model, and gave the measures to optimize the travel route and implement the site current limit, which has practical significance for solving urban rail transit problems.