Data-driven perspectives for energy efficient operations in railway systems: Current practices and future opportunities
place - europe, mode - rail, literature review - literature review, operations - performance, operations - reliability, planning - methods
Data driven, Model based, Railway energy efficiency, Calibration
Railway systems must increase their performance and economic competitiveness to remain an effective and efficient transport mode. Energy efficiency goals are one of the main drivers for the future evolution of planning and operations of transport systems. An opportunity to improve energy efficiency together with reliability and feasibility of railway systems come from the huge amount of data being currently collected and available in the future. The hidden potential in large sets of data for improving energy efficiency can be fully exploited through novel, data-driven approaches. This paper discusses the relation of those future approaches with the current state of the art and challenges, highlighting natural advantages and possible weak points. We identify dimensions within the current literature describing the suitability of current approaches to embrace the data revolution, and the possible enhancements resulting from that. We refer to practical test cases based on real on-board monitoring of electric trains in Switzerland to identify current and future challenges in improving energy efficiency of train operations. We conclude with a discussion and a roadmap on the introduction of data-driven approaches for improving energy efficiency of railway systems.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
De Martinis, V., & Corman, F. (2018). Data-driven perspectives for energy efficient operations in railway systems: Current practices and future opportunities. Transportation Research Part C: Emerging Technologies, Vol. 95, pp. 679-697.