Abstract: The current urban rail transit plane line design is limited by the level and experience of designers, which takes a long time and is difficult to obtain a better scheme. Therefore, an urban rail transit plane obstacle avoidance optimization design system based on improved particle swarm optimization (PSO) algorithm is constructed to realize automatic obstacle avoidance and optimal design of urban rail transit plane lines. In the process of urban rail transit plane line design, the length of plane line largely determines the scale and investment of the project, and the total length of double lines is adopted as the optimization objective. In addition to considering the requirements of the urban rail transit design code for the line, it also considers the constraints of the line to avoid obstacles. Under the premise of given station and obstacle information, the plane route optimization design model is highly nonlinear and complex. The heuristic segmental search algorithm is used to provide feasible initial route scheme, and the improved PSO algorithm combining PSO algorithm and Rosenbrock search is used to optimize the initial route scheme, so as to obtain the optimized plane route in the station area. A case study is conducted on an urban rail line, the obtained design scheme can effectively reduce the length of the plane line and save the project cost while successfully avoiding obstacles compared with the actual design scheme.

Key words: urban rail transit, plane alignment design, automatic obstacle avoidance, particle swarm optimization algorithm, digital intelligent design