The situation in freight operation

The driving pattern e.i. the speed over time diagram has a considerable influence on the energy consumed by a train on a given trip. Whereas in passenger operation this pattern is mainly governed by timetable, stops at stations and speed limits, the situation in freight operation is quite different. Most freight trains do not have to obey strict time schedules but rather stay within certain time windows. On the one hand, this leaves more room for the energetic optimisation of the driving pattern. On the other hand, in mixed infrastructures passenger trains usually have priority over freight trains which leads to frequent unscheduled stops for freight trains. These unexpected stops impede the operation of a DAS.

Low-density networks

Railways with low traffic density and/or homogeneous freight operation therefore offer the greatest potential for freight DAS. This is the case in countries like the US or Australia, but also on individual lines in Europe. In such cases, DAS does not aim at coasting only but rather on an optimised running pattern for the whole trip.

Dense and or mixed networks

In cases where freight operation has a high density and or shares the infrastructure with passenger trains, DAS can only operate in an effective way, if the system takes into account the traffic situation. This requires a radio (or other) link to the control centre level.

Components of a DAS

Just as in passenger operation, DAS for freight operation require the following on-board components:

• Storage medium storing all the relevant data for an individual trip (infrastructure data, vehicle data)
• Information system monitoring driving time and train position
• Computer unit using the above data to determine driving strategies and display them to the driver

In order for freight DAS to operate in a reliable manner several issues have to be resolved:

Train positioning

The exact train position is essential for the calculation of driving recommendations. On main lines a precision of 100 m is usually sufficient.

• In suburban DAS the wheel impulse counters (odometers) are sufficient since frequent stops at stations can be used to compensate slippage-induced errors. This method alone is usually not sufficient in main line operation since stops are too rare to minimise this inaccuracy.
• Therefore additional satellite-based positioning (GPS, Galileo) has to be used: This method usually has an accuracy of 5 m, but due to signal reflections on metal surfaces along the track (multipath propagation) there may be exceptional errors of up to several hundred meters. In addition the positioning signal may be interrupted in tunnels or stations.
• Combined positioning (by sensor fusion): The most reliable method is a combination of the two methods. If the resulting position data differ, a so called sensor fusion calculates a weighted combination of the two. A field test of this system realised in Switzerland (cf. Meyer et al. 2002) yielded only in less than 5% of all cases an error exceeding 10 meters.

Data supply

A DAS requires different classes of data to be updated in different time intervals:

• Permanent data: Vehicle data
• Long-term data: Track data base (to be updated annually)
• Mid-term data: Time table
• Short-term data: Data on temporary low-speed sections (to be updated daily or even in real-time). This includes train configuration and vehicle mass which vary permanently in freight operation.