Application of Big Data in Energy-Efficient Management of Rail Systems

Dear Colleagues,

We are pleased to launch a new Special Issue focusing on recent developments in the field of application data in rail systems in terms of its relationship to energy efficiency.

Advanced rail system plays an increasingly important role for passenger mobility both in intercity communication and urban commuting. For the design of a train control system, the energy efficiency should be borne in mind.

In this respect, introducing eco-driving strategies or energy-saving infrastructures have been promoted for trains running safely and efficiently. The traditional mathematical modeling approach, where the train trajectory and device usage are the results of a theoretical analysis with highly idealized assumptions, has deviated far from its application in actual life. With the application of data mining and algorithms, the mathematical models and computer simulations in rail system could correct parameters, and further verify applicability.

In view of the above concerns, the aim of the Special Issue is to collect the most promising approaches of modeling newly introduced energy-efficient operation in rail system with big data technology supplements. We want to show the complexity of the analysis and present how to solve the problem associated with the application of big data based on highly advanced technologies. The Special Issue will be focused on modeling techniques, quantitative analysis and advanced solution algorithms, resulting in the development of this research area.

Potential topics include but are not limited to the following:

• Energy analysis in rail systems;
• Energy-efficient scheduling;
• Energy-efficient timetable optimization;
• Energy-efficient speed profile optimization;
• Energy-efficient train control;
• Simulations of the power supply system;
• Carbon emission evaluation or reduction;
• Data analysis on energy-efficient management;
• Decision making on energy-efficient management;

Other topics relevant to big data and machine learning in rail transit systems.

Prof. Dr. Xin Yang
Dr. Songpo Yang
Dr. Xiaoming Xu
Guest Editors

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