In the process of urban rail transit network design, the urban road network, urban trips and land use are the key factors to be considered. At present, the subjective and qualitative methods are usually used in most practices. In this paper, a quantitative model is developed to ensure the matching between the factors and the urban rail transit network. In the model, a basic network, which is used to define the roads that candidate lines will pass through, is firstly constructed based on the locations of large traffic volume and main passenger flow corridors. Two matching indexes are proposed: one indicates the matching degree between the network and the trip demand, which is calculated by the deviation value between two gravity centers of the stations’ importance distribution in network and the traffic zones’ trip intensity; the other one describes the matching degree between the network and the land use, which is calculated by the deviation value between the fractal dimensions of stations’ importance distribution and the traffic zones’ land-use intensity. The model takes the maximum traffic turnover per unit length of network and the minimum average volume of transfer passengers between lines as objectives. To solve the NP-hard problem in which the variables increase exponentially with the increase of network size, a neighborhood search algorithm is developed based on simulated annealing method. A real case study is carried out to show that the model and algorithm are effective.
Linkage between passenger demand and surrounding land-use patterns at urban rail transit stations: A canonical correlation analysis method and case study in Chongqing