Point of departure

In many countries existing infrastructure has reached its capacity limits. The consequence are frequent train conflicts caused by trains running out of their slots due to delays. These conflicts are especially abundant in bottlenecks of the infrastructure, such as junctions and lines with high traffic density.

They usually lead to deceleration or stopping of one or several of the trains which in turn leads to new train conflicts. This domino effect leads to a propagation of delays in the network which reduces overall performance and service quality. Traffic fluidity is also a major issue for energy efficiency since any additional stop (and subsequent acceleration) along the way requires additional traction energy.

Future solution

One of the most promising ways to avoid train conflicts or reduce their negative effects is an electronic conflict management on the control center level. If at the train control center the exact position of all trains in the controlled area is known, train conflicts leading to signalled stops may be foreseen at an early stage. The speed regime of the involved trains may then be modified in order to avoid the conflict or reduce its effects (delays, energy consumption through stop-and-go driving). An example for such a situation is shown in a simplified manner in Fig. 1.

Figure 1: Principle of conflict management by control center

Source: IZT

Technical requirements

Currently, if at all this conflict management is made manually at the hierarchy level of the signal boxes. A more systematic IT based optimisation on a higher level (for a bigger area of the network) is not in place in today's infrastructure management.

The operation of effective future train control systems is sketched in Figure 2.

Figure 2: Components of a train control for optimised traffic fluidity (simplified)

Source: IZT

As can be seen such a system required the following components:

• GPS (or Galileo) on all trains
• Up-link to transmit train position to control centre (to be realized by GSM-R or other communcation channel).
• An optimisation software at the control centre to support complex decision making
• Down-link to transmit driving recommendations from control centre to train (to be realized by GSM-R or other communcation channel).
• An on-board unit displaying these speed recommendations to the driver in a clear and simple way (should be integrated into DAS systems if existing).

Integration into DAS

Driving recommendations received from a traffic optimisation tool at the control centre could be an interesting upgrade for on-board DAS. These recommendations could just over-rule the recommendations generated by the on-board DAS. They should be displayed in the same manner so that the driver is not confused by different types of recommendations.

Train conflicts and have a major effect on energy consumption for train operation. Although the prominent role of traffic fluidity on energy efficiency is undoubted, there is little quantitative data on its impact.

A study by Adtranz Switzerland (Meyer et al. 2000) measured the energy consumption of different real train runs between Luzern and Zurich. The figures revealed that the average energy consumption of the runs on which no unexpected stops occurred was 10-15% lower than the corresponding average of all runs with one or several unexpected stops. The authors conclude that an improved traffic situation could save up to 10 % of the energy.