Cross-line Train Service Plan Optimization in Urban Rail Transit Network

In order to improve the service quality of urban rail transit by reducing transfer times, a method for generating cross-line train routes and an optimization model for planning train routes with cross-line operation are proposed based on the characteristics of passenger flow in the network. First, with the developed inference method of passenger travel routes, the various passenger flows and proportions in the network are calculated to obtain the cross-line times, thereby generating the set of alternative long cross-line train routes. Then, with the goal of minimizing passenger transfer times, an optimization model for the operation of long cross-line train routes in the network is constructed, which satisfies the constraints of basic operating conditions and cross-line capacity. An improved genetic algorithm with a frequency-based passenger flow assignment method is used to solve the problem to obtain the operating frequency of the mainline and cross-line train routes in the network. Finally, the effect of long cross-line train routes is analyzed based on an urban rail network. The results show that the optimized train service plan reduces the transfer times of all transfer passengers by 2.02% to 5.97%. Thus, the passenger transfer time and network transfer coefficient are reduced, and the direct passenger flow is increased by 1.58% to 4.58% with the operated long cross-line train routes. The operated long cross-line train routes play the role of short train routes in the connected line to supplement the sectional transportation capacity, thus reducing the total number of running trains on the line and the train kilometers on the main line. In addition, when the transfer passenger volume at the transfer station is high, the cross-line train route cannot be operated due to the high operating frequency of the main-line train on the connected line, and the effect of improving the operational services gradually decreases as the operating frequency of the cross-line train route reaches the upper limit of the cross-line capacity. © 2024 Science Press. All rights reserved.