Distributed Optimal Train Adjustment and Waiting Passengers Control for Metro Lines Based on ADMM Algorithm

This paper investigates the distributed optimization of train scheduling and waiting passengers control problem for metro lines to improve the operational efficiency and service level. Integrating the train departure time and waiting passengers, a multi-train coupling state-space model is established. To improve computational efficiency, we propose a distributed optimization algorithm to decompose the complex joint optimization problem of multiple trains into several subproblems that can be computed in parallel. Based on the alternating direction method of multiplier (ADMM) algorithm, the coupling constraints between trains are effectively eliminated, and each subproblem is solved through iterative coordination with other subproblems. Numerical examples illustrate the effectiveness of the proposed distributed optimization algorithm for train automatic train regulation and waiting passengers control.