Energy-efficient timetabling for urban rail transit network considering passenger path choice behaviors

Abstract

The high energy consumption of urban rail transit (URT) in metropolitan areas becomes a hotspot problem due to the ever-increasing operation mileages and pressing agendas of carbon neutralization. The majority of energy-efficient timetabling studies focus on a single URT line and are insufficient for a URT network with multiple interlinked lines. We propose a general model framework including timetabling and passenger path choice behaviors to optimize energy consumption of a URT network under passenger travel time constraints. A novel dynamic programming and heuristic search method for determining travel time components are incorporated in an iterative solution algorithm to find energy-efficient timetables. The proposed model and solution algorithm are validated with a real-world URT network under various scenarios.