Optimizing train service plans to coordinate transport capacity for urban rail transit lines

In view of big passenger flow volume and high passenger risk at transfer stations during the peak period, this paper studied the coordination method of urban rail transit network transportation organization from the perspective of capacity matching. The change law of passenger flow was analyzed, and the calculation methods of train remaining carrying capacity, waiting passenger demand and the largest number of people gathered on the platform were determined. The concept of capacity coordination degree (CCD) was proposed, used to describe the matching degree between traffic demand and transport capacity of each line. Based on this, taking the optimal comprehensive CCD of the transfer station as the goal, the first train departure time and train departure interval as decision variables, and guarantee of passenger safety within station as the main constraint, a nonlinear integer programming model of train service plans collaborative optimization was established, and the genetic algorithm was designed. A case study of a two-line intersecting network was carried out. The results show that, after the use of capacity coordination scheme, the total number of running trains increases by only 1, the number of remaining passengers reduces by 68.44%, comprehensive CCD is closer to 1, and the largest number of people gathered in big passenger flow directions decreases by 11.77% and 19.68%, respectively. Transport supply can better meet the passenger demand in all directions, effectively improving the interests of both passengers and operators.