To relieve severe traffic congestion and the over-saturation of rail transit system, this study integrates the service and demand from the perspective of system optimization, and considers the continuous arrival characteristics of passenger flow in the analysis. A collaborative optimization method is developed for the train operation schedule and passenger flow control at stations using the skip-stop pattern strategy. By introducing the train schedule and passenger flow control decision variables, a bi-objective integer nonlinear collaborative optimization model is formulated to improve the train operation efficiency and to reduce the number of delayed passengers. Then, the nonlinear constraints are linearized by time reconstruction and big-M method with 0-1 variables to solve the proposed model. The model is reconstructed into an integer linear programming model, which can be easily solved by the CPLEX solver. The numerical examples are executed to verify the effectiveness of the proposed model. The results show that compared to the single objective optimization method and only with the train service time, the proposed model significantly reduces the number of delayed passengers. Compared to only considering number of delayed passengers, the train running time is reduced by 2% to 3%.
|Translated title of the contribution||Collaborative Optimization of Urban Rail Transit Operation and Passenger Flow Control at Stations Using Skip-stop Pattern Strategy|
|Original language||Chinese (Traditional)|
|Number of pages||7|
|Journal||Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology|
|Publication status||Published - 1 Jun 2021|