Big Data-Based Timetable Management

Project information

  • Big Data-Based Timetable Management
  • Project director: Vincent Vu
  • Project manager: Vincent Vu
  • Status: ongoing project
  • Project code: 3RASIBDTMA

Project description

According to the 2050 Vision for the UIC Asia Pacific, data management is one of the key technologies to enable strategic development. Today’s railway management systems operate in the context of changing demand, variable information and various types of interference. Such systems should take into account all such factors, while being cost efficient and oriented towards the customers, who care most about the quality of delivered services, i.e. the accuracy of arrival to destination, timely delivery of goods, etc. However, conventional approaches to analysis of indices describing the operation of railway systems prevent from taking into account the fast changing environment. Many factors are hard to formalize and can’t be obtained through direct measurements. It is should also be noted that the amount of information generated by railway systems is on an exponential rise. A must for modern railway management systems is accurate and fast processing of data (preferably in real time) with the capability to predict interferences.
With the high-speed rail traffic expansion at the current rate, the onset of new hazards and threats, an extended class of risks (challenges) can now be observed that is based on various threats that affect the transportation process and train schedule performance.
The project will aim to:

  • develop a harmonized data structure required for implementation in an advanced timetable management system taking into account the constantly changing environment,
  • describe interfaces with required information sources,
  • develop approaches and algorithms for practical software implementation taking into account the interferences caused by non-formalized factors that affect the quality of timetable management.
    Testing will also involve the development of a simulation system using the railML data format.
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Sunday 29 March 2020
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