Multiobjective Optimization on the Operation Speed Profile Design of an Urban Railway Train With a Hybrid Running Strategy

Abstract

In urban railway systems, a predefined speed profile helps train drivers and automatic train operation systems realize eco-driving without ignoring the requirements for punctuality and comfort. This study proposes a multiobjective optimization method for speed profiles of urban railway systems and provides a Pareto front in three dimensions with a hybrid running strategy. First, three popular running strategies are selected and combined. Second, a model of train behavior is constructed, and energy efficiency, running time, and comfort are used to evaluate the speed profiles. Third, a hybrid strategy multiobjective particle swarm optimization algorithm is proposed and utilized with train performance simulation to solve this problem. Finally, two running sections of Beijing subway line 8 are applied in a case study. The results verify the effectiveness of the proposed approach and imply that a single strategy should not be abandoned when comfort is a consideration.