GB2416900A

GB2416900A - Modelling the operation of a railway.

Info

Publication number: GB2416900A
Application number: GB0416921A
Authority: GB
Inventors: Edward Morland; Stuart Iain Robertson
Original assignee: AEA Technology PLC
Current assignee: Ricardo AEA Ltd
Priority date: 2004-07-29
Filing date: 2004-07-29
Publication date: 2006-02-08
Also published as: GB0416921D0

Abstract

A process for modelling a railway system comprises the steps of obtaining timetable data, data on a first parameter that is an input required for train movement and combining the two to produce an output so as to model the parameter as a function of the state of the train for each section of the rail network at any given time. The timetable data is used to arrive at model data for specific sections of the network which includes details of the train arrival times, speeds and accelerations. The parameter may be related to electrical consumption, operational cost, noise, gaseous emissions, track damage or passenger distribution. The model may also validate parameters against permitted ranges. The timetable data maybe either actual, planed or stochastic data.

Description

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241 6900 - 1 Railway Computer System This invention relates to a process for modelling a railway network and a computer system for use in modelling a railway network.

Nowadays many aspects of railway system operation are controlled and monitored by computer systems. A computer system may be used to store measurements made on the track, for example to monitor rail wear. However, it is typically difficult to predict the effects of running the railway as whole. For example, there is increasing interest in being able to predict how the operation of a railway network affects its environment in terms of noise generation and gaseous emissions. There is also interest in being able to predict the wear that will occur to track and the operational costs of the network during the operation of a timetable.

The present invention seeks to address this problem.

The present invention provides a computer modelling system which can use timetable data and additional data to predict the costs and consequences of running a particular timetable. For example, it can be used to predict the track damage, electricity consumption, operational costs, noise and pollution at any time during

the timetable.

According to the present invention there is provided a process for modelling the operation of a railway network, the modelling being performed by a first computer, the process comprising ::: e. a:. .e 2 i) obtaining timetable datai ii) deducing from the timetable data, model data comprising the times at which the trains arrive at specific sections of the network, the speeds and accelerations of the trains, and the times for which any passenger-carrying trains are stationary at stations; iii) obtaining data on a first parameter that is an input required for train movement, an output produced by train movement or a state existing during train movement, and deducing where necessary how that input, output or state changes with train speed or train acceleration) iv) combining the model data with the data on the first parameter using the first computer so as to model that input, output or state of train movement for each section of the network at any given time or for a unit of time, and v) repeating steps iii) and iv) for at least one other parameter.

Typical inputs, outputs and states of train movement which may be calculated for any given timetable include noise generation, gaseous pollution, electricity consumption, passenger movement, operational costs, track damage and train distribution.

The data on a particular input, output or state of train movement may be provided on the first computer or it may be provided on a second computer which is linked to the first computer.

ë teee ece ice The process may be repeated for the same timetable in order to predict as many inputs, outputs or states of train movement as required.

The present invention also provides a computer system comprising timetable data and data on the inputs, outputs and/or states of train movement which can calculate how each input, output or state varies with position on the network or over time.

Each input, output or state of train movement typically has an effect on decision making processes elsewhere in the management of the rail network or in the running of totally different systems.

For example, the noise and/or gaseous emissions generated by trains may be unpleasant at some places on a network at certain times or may even exceed safe limits.

By predicting these outputs in advance, the effect of a particular timetable can be evaluated before the timetable comes into operation. Where the noise or emissions exceed safety limits at a particular time, or limits imposed in a particular area for any other reason then, once this becomes apparent from the calculation, the timetable can be changed to avoid the problem.

The electricity consumption of the electric trains on a network has an effect on the supply of electricity to the train network, for example by the National Grid in the UK. Once the electricity consumption for all sections of the network has been calculated for any given time, then it is possible to compare the proposed usage with the amount of electricity available. The timetable can then be changed or alterations can be made to the ë e a - 4 - electricity supply as necessary in order to make it possible to run the trains to a particular timetable.

The distribution of passengers on the train network at a given time can have an effect on outside services such as mobile phone networks. If a particular timetable causes hotspots of passenger density at particular times this information can be provided to mobile phone networks or the timetable can be changed.

The operational costs of running a train network include costs such as employing train drivers and guards, buying fuel such as electricity or diesel for trains and costs of buying and maintaining trains. By combining these costs with timetable data it is possible to predict the overall cost of running trains on a rail network to a particular timetable and by further analysing the data to predict the number of trains, drivers and guards etc. required to run the network to that particular timetable.

This information can then be provided to those parts of the organization which deal with employing staff, buying trains etc. From the timetable data it is also possible to predict which trains will pass over which portions of track and how many times this will happen during the course of the timetable. By incorporating data on the types of train used, it is then possible to calculate the damage that will occur to the track with time and the incremental damage that will have occurred to the track at any one time during the running of the timetable.

This data can also be combined with data on the state of the track at the beginning of the timetable. This . : :::e . . . ë. - 5 -

information can then be used to decide on a suitable maintenance schedule for the track.

Timetable data can also be used to calculate the distribution of trains at any time across the network.

The process can thereby also calculate when trains appear to need to use the same sections of track as one another in order for the timetable to be adhered to. A further calculation step can then be used to calculate how the signal system will need to operate in order to keep the trains apart. Calculations of risk e.g. the risk of a crash, can also be made based on closeness of trains to one another.

The timetable data used for the model can be actual timetable data on the position of trains that was gathered using sensors on the network. Alternatively, the timetable data may merely data assume accurate operation of the timetable as planned. Finally, the timetable data may be a stochastic distribution based on the timings in the planned timetable.

The present invention also provides a process which further comprises evaluating the values of the input, output or state against permitted ranges of values and recalculating the timetable so as to avoid generating a value of the said input, output or state that is outside the permitted range.

The train network can be local, national or international.

The present invention is further described by way of

Example.

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Example 1

The model of the present invention can be used to run a simulation of a new planned timetable and to generate the corresponding model data. By adding in the data for the noise generated by each type of train at certain speeds and when stationary the model can then deduce the noise generated by the trains at any speed.

This information combined with the model data is then used to calculate the noise produced by the trains at each section on the network at any given time. The model can then show where and when the noise exceeds acceptable safety limits.

The model data is then combined with appropriate data so as to calculate the particulate emissions generated by the trains when run according to the planned timetable. The model can then show where and when the emissions exceed acceptable safety limits.

The model can then be rerun using the stochastic timetable data in order to indicate the probable noise and emissions generated. The results from the stochastic timetable and the planned timetable can then be compared.

Example 2

The model of the present invention is run to predict the electricity consumption required by the trains according to the planned timetable. The model is also rerun using the same model data to calculate the track damage caused by the trains during the period of the timetable. The model predicts that certain sections of :. : .. :: .: Be. - 7 -

rail may fail during the timetable. This prediction can then be further refined by combining it with further data on the state of the rails at the beginning of the timetable. This increases the number of sections of rail that are predicted to fail as some rails that will receive only a small amount of wear may fail due to their bad state at the beginning of the timetable. This information is then provided to the maintenance division to ensure that those sections of the network are maintained in advance of the predicted failure time.

The timetable is then rerun taking into account the planned maintenance, both in terms of the damage caused by the maintenance vehicles and the new state of the rails once maintenance has occurred. The model then indicates that the rails will last for the duration of

the timetable.

The model can then be rerun to calculate the electricity required for the new timetable. Thus, the present invention can be used to help calculate the cost of running the network in terms of electricity and maintenance required.

Claims

.e tee. .' He' '.

Claims 1. A process for modelling the operation of a railway network, the modelling being performed by a first computer, the process comprising i) obtaining timetable datai ii) deducing from the timetable data, model data comprising the times at which the trains arrive at specific sections of the network, the speeds and accelerations of the trains, and the times for which any passenger-carrying trains are stationary at stations; iii) obtaining data on a first parameter that is an input required for train movement, an output produced by train movement or a state existing during train movement, and deducing where necessary how that input, output or state changes with train speed or train acceleration;

iv) combining the model data with the data on the first parameter using the first computer so as to model that input, output or state of train movement for each section of the network at any given time or for a unit of time, and v) repeating steps iii) and iv) for at least one other parameter.
2. A process according to claim 1 wherein the input is electricity or operational cost.
3. A process according to claim 1 wherein the output is noise, gaseous emissions or track damage.

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4. A process according to claim 1 wherein the state is passenger distribution.
5. A process according to any one of claims 1 to 4 wherein the timetable data is actual timetable data, planned timetable data or stochastic timetable data.
6. A process according to any one of claims 1 to 5 which further comprises evaluating the values of an input, output or state against permitted ranges of values and recalculating the timetable so as to avoid generating a value of the said input, output or state that is outside the permitted range.
7. A computer program comprising instructions for performing a process according to any one of claims 1 to 6.
8. A computer readable recording medium comprising a program according to claim 7.
9. A process substantially as hereinbefore described with reference to any one of the examples.