Explainable AI-based Planning of Production Variants, Circulations, and Shifts in Railway Systems

Research-to-Practice (with dwh and ÖBB)

The project ExplAIn-TrAIn-Plan - Explainable AI-based Planning of Production Variants, Circulations and Shifts in Railway Systems - addresses the increasing complexity of modern railway networks and the growing diversity of locomotive types. These present significant challenges for railway operators in achieving efficient and robust locomotive circulation planning. The project aims to develop AI-supported optimization and simulation methods to identify energy-efficient and robust planning variants and to assess their effects on vehicle circulation and crew schedules. By combining optimization, simulation, and machine learning, the project creates explainable and practically relevant decision support systems that enable sustainable and reliable planning. The international consortium brings together ÖBB-Produktion GmbH as an industry partner with its cooperate program ARP - Automated Resource Planning and interdisciplinary expertise in data analysis, optimization, simulation, and railway operations.