Schedule-Based Passenger Flow Assignment Decomposition Method for High-Speed Railway Networks

Based on the high-speed and high-frequency operating characteristics of high-speed railways (HSR), the passenger's demand for travel time is described as the continuous time-varying demand at expected departure time, and the continuous time-varying demand is converted into discrete space-time demand at equal time intervals. HSR time-space network is constructed based on HSR schedule. Without considering train congestion, the equilibrium assignment problem of discrete passenger flow is equivalent to the minimum cost flow problem of multiple OD discrete demands with train seat capacity constraints. A schedule-based linear programming model for HSR passenger flow assignment is constructed. In order to deal with the huge number of decision variables and constraints of the model, the Danzig-Wolfe decomposition algorithm is designed to decompose the model into destination-based minimal cost flow problems with no capacity constraints. Utilizing the acyclic characteristics of HSR time-space networks, the HSR passenger flow assignment model under large-scale network is solved, and the algorithm is verified by an example of the East ring of Hainan Roundabout Railway. Results show that: for all passengers departing from Sanya station on July 1st, 2015, there is no additional cost for purchasing ticket in advance in this network, and the network capacity is relatively loose. When the network passenger flow is 1. 8 times of the original passenger flow, there are three optimal travel routes for passengers with the desired departure time of 14:00 between Qionghai and Haikou. The travel costs of the three routes are all 184. 60 yuan. It means that the network has reached a user equilibrium state, which proves that the model and algorithm are both effective and efficient. © 2020, Editorial Department of China Railway Science. All right reserved.