Optimization of the Transport Structure Driven by Urban Rail Transit Under Low-Carbon Target

A reasonable urban transport structure is necessary to develop low-carbon transport and establish a cleaner and more efficient urban transport system. Urban rail transit plays a significant role in the development of low-carbon transport due to its advantages of efficiency, punctuality, safety, and environmental protection. In this paper, we construct a multi-objective model driven by urban rail transit to optimize the urban passenger transport structure from a systemic perspective. The objective functions of this model include minimizing transport CO2 emissions and travel costs while maximizing travel quality and the utilization rate of public transport operation lines. The non-dominated sorting genetic algorithm II (NSGA–II) is a classic multi-objective optimization algorithm used to optimize conflicting objectives simultaneously. In this paper, the multi-objective optimization model is solved using an improved NSGA–II, extending the local search mechanism into the NSGA–II. To evaluate the validity of the model, this paper takes Beijing, China, as the case area. Based on the development plans of urban rail transit, we analyze from a specific year and multiple years. The results illustrate a structural transformation in urban passenger transport and embody a sustainable urban passenger transport structure driven by urban rail transit. This paper proposes a valid method, providing guidance for optimizing the urban transport structure.