CONTROL METHOD AND CONTROL DEVICE FOR OPERATING A RAIL VEHICLE

Abstract

A control method operates a rail vehicle. The method is carried out in a computer-assisted manner on the basis of a vehicle control program. Accordingly, it is provided that the vehicle control program operates with the use of detected driving and/or surroundings data being detected by on-board or train-board sensors.

Description

The invention relates to a control method for operating a rail vehicle, wherein the method is carried out in a computer-assisted manner on the basis of a vehicle control program. Control methods of this type are known in the field of rail vehicle technology.

The object underlying the invention is to specify an improved control method for operating a rail vehicle.

This object is inventively achieved by a method having the features according to claim 1. Advantageous embodiments of the inventive method are disclosed in dependent claims.

Accordingly it is inventively provided that the vehicle control program works with the use of detected driving and/or environment data. Using detected driving and/or environment data advantageously enables the control method to be adapted to the respective current vehicle situation, for example with a view to the current driving behavior of the rail vehicle (acceleration or braking behavior), environmental conditions (e.g. rain or ice) and/or the technical surroundings on the system (e.g. ungated level crossing with approach by people or vehicles); this is explained in greater detail below on the basis of examples.

Vehicle-specific driving behavior data is preferably at least also detected by measurement as driving and/or environment data during the journey of the rail vehicle. For example, the acceleration power and/or braking power can be detected as vehicle behavior data and can be used to control the rail vehicle.

It is advantageous if previously detected driving and/or environment data is updated during the journey of the rail vehicle, for example regularly.

In a preferred embodiment of the method it is provided that the vehicle control program is parameterized with the use of the detected driving and/or environment data.

In the latter embodiment variant it is advantageous if the driving and/or environment data is used to form a control profile dataset, and a fixed-program control module of the vehicle control program is parameterized by means of the control profile dataset. The control profile dataset can be generated and/or updated before and/or during the journey using the driving and/or environment data.

Alternatively it can be provided that based on the driving and/or environment data a control profile dataset can be selected from a predefined group (preferably a plurality) of stored control profile datasets, and a fixed-program control module of the vehicle control program is parameterized by means of the selected control profile dataset. The latter method variant can be carried out particularly simply and quickly, because the stored group of stored control profile datasets can be accessed and there is no requirement to generate a completely new control profile dataset.

In another preferred embodiment variant of the method it is provided that an experience database is accessed, in which actuating commands by a real rail vehicle driver during previous journeys are stored as a function of driving situations, wherein the stored driving situations are determined using the driving and/or environment data detected by measurement during the previous journeys and are stored with the corresponding actuating commands by the real rail vehicle driver.

If an experience database such as this is available, it is advantageous if sensor signals from sensors connected to a control facility of the rail vehicle or connected thereto are evaluated during the journey and the respective current driving situation is determined, the self-determined current driving situation is compared with the driving situations stored in the experience database and, if there is conformity or at least—according to predefined conformity criteria—sufficient similarity between the respective self-detected driving situation and one of the stored driving situations in the experience database, the stored actuating commands by the real rail vehicle driver that correspond to the stored driving situation are read and output.

The method is preferably carried out on the rail vehicle side by means of a control facility installed on the rail vehicle side.

The invention additionally relates to a control facility for a rail vehicle which comprises a vehicle computer and a vehicle control program that can run on the vehicle computer.

It is inventively provided in respect of such a control facility that the vehicle control program is designed such that it works with the use of detected driving and/or environment data.

With regard to the advantages of the inventive control facility, reference is made to the above explanations in conjunction with the inventive control method.

The vehicle control program preferably has an observation module, a parameterization module and a control module, wherein the observation module detects the driving and/or environment data during the journey of the rail vehicle, the parameterization module parameterizes the control module with the use of the detected driving and/or environment data and the parameterized control module outputs actuation commands for the rail vehicle.

It is particularly advantageous if the parameterization module is embodied such that it forms a control profile dataset with the driving and/or environment data or selects a control profile dataset from a group of stored control profile datasets and parameterizes the control module by means of the formed or selected control profile dataset.

In an alternative embodiment of the control facility which is however likewise regarded as very advantageous it is provided that the vehicle control program has an experience database or is connected to an experience database, in which actuating commands by a real rail vehicle driver during previous journeys are stored as a function of driving situations, wherein the stored driving situations are determined with the driving and/or environment data detected by measurement during the previous journeys and are stored together with the corresponding actuating commands by the real rail vehicle driver during the previous journeys.

In the latter embodiment it is advantageous if the vehicle control program has an observation module which evaluates the driving and/or environment data during the journey of the rail vehicle and detects the respective current driving situation, and the vehicle control program has a selection module that compares the self-detected current driving situation with the driving situations stored in the experience database and, if there is conformity or at least—in accordance with predefined conformity criteria—sufficient similarity between the respective self-detected driving situation and one of the stored driving situations in the experience database, the stored actuating commands by the real rail vehicle driver that correspond to the stored driving situation are read and output from the experience database to control the rail vehicle.

The invention also relates to a rail vehicle with a control facility, as has been described above.

The invention is explained in more detail below on the basis of exemplary embodiments, in which, by way of example:

FIG. 1 shows an exemplary embodiment of an inventive rail vehicle, based on which an exemplary embodiment of an inventive train control method is explained,

FIG. 2 shows a second exemplary embodiment of an inventive rail vehicle, based on which a second exemplary embodiment of an inventive train control method is explained,

FIG. 3 shows a third exemplary embodiment of an inventive rail vehicle, based on which a third exemplary embodiment of an inventive train control method is explained, and

FIG. 4 shows by way of example the operation of the third exemplary embodiment according to FIG. 3.

For the sake of clarity, in the figures, the same reference characters are always used for identical or similar components.

FIG. 1 shows a rail vehicle 10 which is fitted with a control facility, referred to hereinafter as a train control facility 20. The train control facility 20 comprises a vehicle computer 30 and a storage device 40 which is connected to the vehicle computer 30.

The rail vehicle 10 can—as is further explained below—have multiple units or consist of multiple coaches and can form a train; this is not illustrated in greater detail in the figures for the sake of clarity.

Stored in the storage device 40 is a vehicle control program 50 which can be or is run by the vehicle computer 30 and on the output side can output actuating commands SB to control the rail vehicle 10 or outputs them during operation.

In the exemplary embodiment according to FIG. 1 the vehicle control program 50 comprises an observation module BM, a parameterization module PM and a fixed-program control module STM.

If the vehicle computer 30 runs the vehicle control program 50, the observation module BM, the parameterization module PM and the control module STM preferably work as follows:

The observation module BM detects driving and/or environment data FUD arriving or present on the input side, which for example is supplied or imported from on-board or train-board sensors; the sensors are not illustrated in FIG. 1 for reasons of clarity. Suitable sensors are for example those which directly describe the driving behavior of the train, such as for example speed sensors, location sensors or acceleration sensors, or those which detect the surroundings by measurement, such as for example inclination sensors to detect inclines or gradients, moisture, ice or snow sensors for identifying a dry, wet or icy track or for detecting friction on the track. Alternatively or additionally, driving and/or environment data FUD can originate from external sources, for example from an interlocking or a control center, and be transmitted to the rail vehicle, for example by radio.

The observation module BM detects the driving and/or environment data present on the input side and forwards it to the parameterization module PM.

The parameterization module PM evaluates the driving and/or environment data FUD and uses it to generate a control profile dataset SD, with which it parameterizes the control module STM.

The parameterization module PM can infer physical properties of the rail vehicle 10 based on the driving and/or environment data FUD and adjust control parameters in accordance with these properties. For example, the parameterization module PM can infer on the basis of acceleration measurement values the overall mass of the rail vehicle 10 and in the event of a large mass can provide a flatter braking curve, in other words start braking earlier before a stop than in the case of a smaller mass.

In addition, based on the driving and/or environment data it is possible to determine the train length, the weight distribution within the train and/or the coupling distances or buffer distances between individual coaches of the train in the case of a multi-unit rail vehicle or train, and this data can be taken into account in the control profile dataset SD for example with a view to an optimized braking behavior, in particular when it is a matter of particularly good position accuracy when stopping the train.

The parameterization module PM can also take the environmental conditions into account and in the event of icy or wet conditions can provide a flatter braking curve and/or can accelerate with less drive force than in dry conditions in order to prevent slipping.

The determination of a suitable control profile dataset SD is carried out in respect of the vehicle-related parameters advantageously on the basis of data which is determined in the context of a test starting operation and/or a test braking operation at the start of the respective journey, in other words individually for each journey. A procedure such as this ensures that changes to the rail vehicle or train, for example as a result of coaches being decoupled or coupled, are identified and can be taken into account in the formation of the control profile dataset SD.

In the exemplary embodiment according to FIG. 1 the control module STM is a fixed-program module and is parameterized merely by means of the control profile dataset SD supplied by the parameterization module PM. As soon as the parameterization module PM has imported the control profile dataset SD into the control module STM, the control module STM can generate the actuating commands SB to control the rail vehicle and output them on the output side.

FIG. 2 shows an exemplary embodiment of a rail vehicle 10 which is fitted with an embodiment variant of the train control facility 20 according to FIG. 1.

Unlike the exemplary embodiment according to FIG. 1, in the exemplary embodiment according to FIG. 2 a group of control profile datasets SD is stored in the storage device 40, for example in the parameterization module PM, such that the parameterization module PM—unlike the embodiment variant according to FIG. 1—does not have to generate its own control profile dataset SD for controlling the control module STM, but merely has to search for a suitable control profile dataset SD from the group of stored control profile datasets, based on the driving and/or environment data FUD present on the input side.

For example, three control profile datasets SD can be stored in the storage device 40, for example one for the case of a heavy rail vehicle, one for the case of a moderately heavy rail vehicle and one for the case of a light rail vehicle. The control dataset SD for a heavy rail vehicle can for example provide a particularly flat braking curve, in other words start braking earlier before a stop, than the control profile datasets for moderately heavy or light rail vehicles. The control profile dataset SD for a light rail vehicle can provide a particularly steep braking curve.

Further subdivisions while increasing the number of control profile datasets SD can be provided as a function of further parameters, for example—in the case of a multi-unit rail vehicle or train—as a function of the train length, the weight distribution within the train, the coupling distances or buffer distances between individual coaches of the train and/or as a function of the respective environmental conditions, such as icy or wet conditions, as has already been explained above in connection with FIG. 1.

The control profile dataset SD selected from the parameterization module PM is imported into the control module STM, as a result of which the control module STM is parameterized and can output actuating commands SB to control the rail vehicle 10 on the output side; in this respect reference is made to the explanations above in connection with FIG. 1.

The train control facilities 20 according to FIGS. 1 and 2 have the advantage that the fixed-program control module STM is parameterized in a self-actuating or automatic manner, without requiring any external intervention, for example by a rail vehicle driver.

FIG. 3 shows an exemplary embodiment of a rail vehicle 10, in which a vehicle control program 50 of a train control facility 20 comprises an observation module BM and a selection module AM and is connected to an experience database EFD. Actuating commands by a real rail vehicle driver during previous journeys are stored in the experience database EFD as a function of driving situations. The driving situations have been determined from driving and/or environment data FUD detected by measurement during the previous journeys and stored with the corresponding actuating commands by the real rail vehicle driver. The vehicle control program 50 preferably works as follows:

The observation module BM evaluates driving and/or environment data present on the input side and detects the respective current driving situation FS of the rail vehicle 10. The determined current driving situation FS is transmitted to the selection module AM, which compares the current driving situation FS with the driving situations stored in the experience database EFD and, if there is conformity or at least—in accordance with predefined conformity criteria—sufficient similarity between the self-detected driving situation FS and one of the stored driving situations in the experience database EFD, selects the most similar stored driving situation. For the selected most similar driving situation the stored actuating commands SB by the real rail vehicle driver corresponding thereto can be read and output to control the rail vehicle 10.

This will be explained in greater detail using an example with reference to FIG. 4: for example, the following four driving situations FS1-FS4 can be stored in the experience database EFD, and relate to secured and unsecured level crossings which people and/or motor vehicles do or do not approach:

Driving situation FS1:

secured level crossing, no approach by people and/or motor vehicles

Driving situation FS2:

secured level crossing with approach by people and/or motor vehicles

Driving situation FS3:

unsecured level crossing, no approach by people and/or motor vehicles

Driving situation FS4:

unsecured level crossing with approach by people and/or motor vehicles

If what is stored in the experience database EFD for driving situation FS4 is that rail vehicle drivers reduce speed when driving situation FS4 is present, in other words when a motor vehicle is approaching an unsecured level crossing, the selection module AM can read and output the actuating commands SB stored for driving situation FS4, if such a driving situation FS4 is currently identified by the observation module BM, for example based on video, track and location data.

The method described permits a stepped or graduated upgrade from train operation with a driver to higher levels of automation without a driver and guard. In train operation with a driver (equivalent to GoA2=Grade of Automation 2=semiautomatic driving with driver) the various situations and the driver's response to this situation can be learned by the train control facility 20, in that these are stored in the experience database EFD. Thus as many situations as possible can be learned, which for example have to be mastered by the automatic train control facility in fully automatic operation without a driver (GoA3=driverless running). In this way the introduction of fully automatic systems with their enhanced demands can be supported and prepared for effectively and systematically.

Although the invention has been illustrated and described in detail based on preferred exemplary embodiments, the invention is not restricted by the examples given and other variations can be derived therefrom by a person skilled in the art without departing from the protective scope of the invention.

Claims

1-15. (canceled)

16. A control method for operating a rail vehicle, which comprises the steps of:

carrying out the control method in a computer-assisted manner on a basis of a vehicle control program, the vehicle control program works with detected driving and/or environment data.

17. The method according to claim 16, wherein vehicle-specific driving behavior data is at least also detected by measurement as part of the detected driving and/or environment data during a journey of the rail vehicle.

18. The method according to claim 16, wherein previously detected driving and/or environment data is updated during a journey of the rail vehicle.

19. The method according to claim 16, which further comprises parameterizing the vehicle control program based on the detected driving and/or environment data.

20. The method according to claim 19, which further comprises:

forming a control profile dataset from the detected driving and/or environment data; and

parameterizing a fixed-program control module of the vehicle control program by means of the control profile dataset.

21. The method according to claim 16, which further comprises:

selecting a control profile dataset from a predefined group of stored control profile datasets based on the detected driving and/or environment data; and

parameterizing a fixed-program control module of the vehicle control program by means of the control profile dataset selected.

22. The method according to claim 16, wherein:

an experience database is accessed, in which actuating commands by a real rail vehicle driver during previous journeys are stored in dependence on driving situations; and

the driving situations are determined based on the detected driving and/or environment data detected by measurement during the previous journeys and are stored together with corresponding ones of the actuating commands by the real rail vehicle driver.

23. The method according to claim 22, wherein:

during a journey, sensor signals from sensors linked or connected to a control facility of the rail vehicle are evaluated and a respective current driving situation is determined; and

the respective current driving situation is compared with the driving situations stored in the experience database and if there is conformity or at least, in accordance with predefined conformity criteria, sufficient similarity between the respective current driving situation and one of the driving situations stored in the experience database, stored actuating commands by the real rail vehicle driver that correspond to a stored driving situation are read and output.

24. The method according to claim 16, which further comprises carrying out the method on a rail vehicle side by means of a control facility installed on the rail vehicle side.

25. A control facility for a rail vehicle, the control facility comprising:

a vehicle computer; and

a vehicle control program running on said vehicle computer, said vehicle control program is embodied such that it works with detected driving and/or environment data.

26. The control facility according to claim 25, wherein:

said vehicle control program has an observation module, a parameterization module and a control module;

said observation module detects the detected driving and/or environment data during a journey of the rail vehicle;

said parameterization module parameterizes said control module based on the detected driving and/or environment data; and

said parameterized control module outputs actuating commands for the rail vehicle.

27. The control facility according to claim 26, wherein said parameterization module is embodied such that it forms a control profile dataset based on the detected driving and/or environment data or selects the the control profile dataset from a group of stored control profile datasets and parameterizes said control module by means of a formed or selected control profile dataset.

28. The control facility according to claim 25, wherein:

said vehicle control program has an experience database or is connected to said experience database, in which actuating commands by a real rail vehicle driver during previous journeys are stored as a function of driving situations; and

the driving situations are determined from the detected driving and/or environment data detected by measurement during the previous journeys and are stored together with corresponding ones of the actuating commands by the real rail vehicle driver during the previous journeys.

29. The control facility according to claim 28, wherein:

said vehicle control program has an observation module which evaluates the detected driving and/or environment data during a journey of the rail vehicle and detects a respective current driving situation; and

said vehicle control program has a selection module that compares the respective current driving situation with the driving situations stored in said experience database and, if there is conformity or at least, in accordance with predefined conformity criteria, sufficient similarity between the respective current driving situation and one of the driving situations stored in said experience database, stored said actuating commands by the real rail vehicle driver that correspond to a stored driving situation are read and output from said experience database to control the rail vehicle.

30. A rail vehicle, comprising:

a control facility having a vehicle computer and a vehicle control program running on said vehicle computer, said vehicle control program is embodied such that it works with detected driving and/or environment data.