ORIENTATION-BASED POSITION DETERMINATION FOR RAIL VEHICLES

Abstract

A method for orientation-based localization or position determination of a rail vehicle includes capturing sensor data that are correlated with a change of orientation of the rail vehicle. A time-dependent change of orientation of the rail vehicle is determined on the basis of the sensor data. Moreover, an estimated velocity of the rail vehicle is determined on the basis of the captured sensor data and/or on the basis of additionally captured sensor data. A distance-dependent orientation of the rail vehicle is subsequently determined on the basis of the estimated velocity and the time-dependent change of orientation of the rail vehicle. Furthermore, an absolute position of the rail vehicle is determined by comparing the determined distance-dependent orientation of the rail vehicle with reference data of a distance-dependent orientation. A localization facility and a rail vehicle are also described.

Claims

1-15. (canceled).

16. A method for orientation-based localization of a rail vehicle, the method comprising the following steps: capturing sensor data correlated with a change of orientation (dO/dt) of the rail vehicle; determining a time-dependent change of orientation (dO/dt) of the rail vehicle based on the sensor data; determining an estimated velocity (Vloc) of the rail vehicle at least one of based on the captured sensor data or based on additionally captured sensor data; determining a distance-dependent orientation (O(s)) of the rail vehicle based on the estimated velocity (Vloc) and the time-dependent change of orientation (dO/dt) of the rail vehicle; and determining an absolute position (pabs(t)) of the rail vehicle by comparing the determined distance-dependent orientation (O(s)) of the rail vehicle with reference data (Oref(s)) of a distance-dependent orientation.

17. The method according to claim 16, which further comprises carrying out the comparison by determining a cross-correlation function (r(k)) between the determined distance-dependent orientation (O(s)) and the reference data (Oref(s)) of the distance-dependent orientation.

18. The method according to claim 17, which further comprises providing the cross-correlation function (r(k)) with a complex cross-correlation function (rc(s)).

19. The method according to claim 17, which further comprises providing the cross-correlation function (r(k)) with a real cross-correlation function (rr(s)).

20. The method according to claim 16, which further comprises capturing the sensor data correlated with the change of orientation (dO/dt) of the rail vehicle by using one of a plurality of sensor systems as follows: a radar system, or an inertial measuring unit, or a satellite navigation system, or an acceleration sensor system, or a magnetic field sensor system, or an ultrasound sensor system, or a laser-based measuring system, or a measuring system based on the modulation of radioactive radiation, or a camera-based measuring system.

21. The method according to claim 16, which further comprises: determining a scalar velocity (v(t)) of the rail vehicle based on the estimated velocity (Vloc); determining a covered distance of the rail vehicle based on the scalar velocity (v(t)) of the rail vehicle; and carrying out a calibration between the determined distance-dependent orientation (O(s)) and the reference data (Oref(s)) of the distance-dependent orientation based on the covered distance.

22. The method according to claim 16, which further comprises: initially determining a starting point for the captured orientation data (O(s)) in the reference data (Oref(s)) corresponding to a starting point of a route traveled in the reference data (Oref(s)), by comparing the determined distance-dependent orientation (0(s)) of the rail vehicle with reference data (Oref(s)); and determining an absolute start position (pabs0) of the rail vehicle by an absolute position in a map allocated to the starting point in the reference data (Oref(s)); and determining a dynamic absolute position (pabs(t)) of the rail vehicle (2) by determining a covered path (s(t)) based on the correlated reference data (Oref(s)) and a projection of a length of the covered path (s(t)) on a course of a route indicated in the map.

23. The method according to claim 16, which further comprises checking a reliability of the determined absolute position (pabs(t)) of the rail vehicle by: determining confidence values based on the determination of the orientation values (O(s), Oref(s)), or determining, based on a curve shape of the cross-correlation function (r(k)), whether a distinct comparison is possible between the determined distance-dependent orientation (O(s)) of the rail vehicle and the reference data (Oref(s)).

24. The method according to claim 16, which further comprises carrying out a calibration of a sensor orientation of sensors of the rail vehicle by correlation of uncalibrated measurement data (O(s)) with reference data (Oref(s)).

25. The method according to claim 24, which further comprises based on at least one of the localization or the calibration, carrying out at least one of: status monitoring or asset monitoring.

26. The method according to claim 25, which further comprises at least one of: carrying out status monitoring by performing one method step as follows: creating a map by way of a specified trajectory, or determining at least one of defects or errors in an existing map based on the specified trajectory, or determining defects in a rail of a track system, or identifying at least one of a yawing or a side motion of the rail vehicle; or carrying out asset monitoring by performing one method step as follows: determining at least one of density or moisture or health of vegetation surrounding a rail region, or determining a condition of infrastructure including organic material.

27. A localization facility, comprising: an orientation sensor unit for capturing sensor data correlated with a change of orientation (dO/dt) of a rail vehicle; a change of orientation determining unit for determining a time-dependent change of orientation (dO/dt) of the rail vehicle based on the sensor data; a velocity determining unit for determining an estimated velocity (Vloc) of the rail vehicle based on at least one of the captured sensor data or additionally captured sensor data; an orientation determining unit for determining a distance-dependent orientation (O(s)) of the rail vehicle based on the estimated velocity (Vloc) and the determined time-dependent change of orientation (dO/dt) of the rail vehicle; and a localization unit for determining an absolute position (pabs(t) of the rail vehicle by comparing the determined distance-dependent orientation (O(s)) of the rail vehicle with reference data (Oref(s)) of the distance-dependent orientation.

28. . A rail vehicle, comprising: the localization facility according to claim 27; a control unit for controlling a journey of the rail vehicle based on a position of the rail vehicle determined by the localization facility; and a drive unit for driving the rail vehicle based on control commands of the control unit.

29. A non-transitory computer program product having a computer program which can be loaded directly into a memory unit of a control facility of a rail vehicle, having segments for carrying out all steps of the method according to claim 16 when the computer program is executed in the control facility.

30. A non-transitory computer-readable medium on which program segments which can be executed by a computer unit are stored in order to carry out all steps of the method according to claim 16 when the program segments are executed by the computer unit.

Description

[0067] The invention will be explained once again in more detail below on the basis of exemplary embodiments with reference to the accompanying figures. In the drawings:

[0068] FIG. 1 shows a flowchart, which illustrates a method for orientation-based localization of a rail vehicle according to one exemplary embodiment of the invention,

[0069] FIG. 2 shows a schematic representation of a localization facility according to one exemplary embodiment of the invention,

[0070] FIG. 3 shows a graph, which illustrates a real-valued and a complex-valued autocorrelation function between a measured orientation of a rail vehicle and reference data,

[0071] FIG. 4 shows a graph, which illustrates maxima of a real-valued and a complex-valued autocorrelation function between a measured orientation of a rail vehicle and reference data,

[0072] FIG. 5 shows a graph, which illustrates a displacement between an orientation curve determined by way of real-valued correlation and an orientation curve determined by way of complex-valued correlation,

[0073] FIG. 6 shows a graph, which illustrates a calibration of an orientation sensor by comparing measured orientation data with reference data,

[0074] FIG. 7 shows a schematic representation of a rail vehicle according to one exemplary embodiment of the invention.

[0075] FIG. 1 shows a flowchart 100, which illustrates a method for orientation-based localization of a rail vehicle according to one exemplary embodiment of the invention.

[0076] In step 1.I, sensor data SD from the environment of a rail vehicle 2 is captured with the aid of a radar sensor.

[0077] A velocity vector V.sub.loc relative to the environment is estimated in step 1.II on the basis of the radar sensor data SD. Since there is little traffic in the environment of a rail vehicle 2, at least outside of dense settlement, the environment behaves substantially statically compared to the traveling rail vehicle 2. Using the knowledge of changes in spacing of the rail vehicle 2 in relation to the environment and/or Doppler measurements it is therefore possible to determine or estimate a local velocity vector V.sub.loc. A global velocity vector V or a global orientation O may not be determined directly using the local velocity vector V.sub.loc, but an estimated scalar velocity v(t)=ds/dt of the rail vehicle 2 and a change of orientation dO/dt may be determined. It should be mentioned once again at this point that the change of orientation dO/dt can also be determined by way of other sensor measuring methods, such as acceleration sensor measurements or inertial sensor-measurements. Instead of by way of a measurement of sensor data from the environment of the rail vehicle 2, the estimated scalar velocity v(t) can also be determined by other measuring methods, such as odometry or satellite navigation.

[0078] 23 In step 1.III, a change of orientation dO/dt is determined as a function of the time t using the determined local velocity vector V.sub.loc.

[0079] 26 In step 1.IV, a scalar velocity v(t) of the rail vehicle 2 27 is determined on the basis of the local velocity vector V.sub.loc. The value of the scalar velocity v(t) corresponds to the amount of the local velocity vector V.sub.loc. Furthermore, a distance-dependent orientation O(s) is estimated (see also equation (3)) by dividing the time-dependent change of orientation dO/dt by the scalar velocity v(t) of the rail vehicle 2 and integration according to the distance.

[0080] In step 1.V, what is known as a complex cross-correlation function r.sub.c(s) is determined between the estimated distance-dependent orientation O(s) of the rail vehicle and reference data O.sub.ref(s) of a distance-dependent orientation.

[0081] 7 In step 1.VI, an absolute maximum of the cross-correlation function r.sub.c(s) is determined. At the distance position so allocated to the maximum the starting point for the estimated orientation data O(s) lies in the reference data O.sub.ref(s). The starting point s.sub.0 of a traveled route is therefore exactly determined in the reference data O.sub.ref(s) in step 1.VI.

[0082] In step 1.VII, an absolute start position of the rail vehicle is determined in a map by way of an absolute position p.sub.abs0 allocated to the starting point s.sub.0 in the reference data O.sub.ref(s).

[0083] Furthermore, in step 1.VIII, a dynamic absolute position p.sub.abs(t) is determined by determining a covered path s(t) since the allocated absolute position Pabs0 and on the basis of a projection of the length of the covered path s(t) on a course of the route indicated in the map of the reference data.

[0084] Steps 1.I to 1.VIII are repeated as often as desired during the journey of the rail vehicle 2, so a precise and constantly updated position p.sub.abs(t) of the rail vehicle 2 is always available.

[0085] FIG. 2 schematically represents a localization facility 20 according to one exemplary embodiment of the invention. The localization facility 20 is part of a control system of a rail vehicle 2 (see FIG. 7). The localization facility 20 comprises an orientation sensor unit 21, which is configured to capture radar sensor data SD, which is correlated with a change of orientation of a rail vehicle 2, from the environment of the rail vehicle 2.

[0086] The localization facility 20 also includes a velocity determining unit 22 and this is configured to determine a local velocity vector V.sub.loc of the rail vehicle 2 on the basis of the determined radar sensor data SD. A kind of local map may be generated using the radar sensor data SD, with a movement V.sub.loc of the rail vehicle 2 relative to the static structures of this local map likewise being determined by the radar sensor data SD.

[0087] The localization facility 20 also comprises a change of orientation determining unit 23 for determining a time-dependent change of orientation dO/dt of the rail vehicle 2 on the basis of the radar sensor data SD or the relative movement V.sub.loc of the rail vehicle 2. A local orientation relative to a local map results using the direction of movement of the relative movement V.sub.loc of the rail vehicle 2. A change dO/dt of the orientation can accordingly be calculated using this local orientation.

[0088] The localization facility 20 also comprises an orientation determining unit 24 for determining a distance-dependent orientation O(s) of the rail vehicle 2 on the basis of the change dO/dt of the orientation O(s) and of the scalar local velocity v(t).

[0089] On the basis of the scalar local velocity v(t)=ds/dt and the change dO/dt of the orientation O(s) of the rail vehicle 2, the orientation results according to

[00002]$\begin{array}{cc}O\left(s\right)=?\frac{dO}{\mathrm{dt}}.Math.\frac{\mathrm{dt}}{\mathrm{ds}}\mathrm{ds}.& \left(3\right)\end{array}$

[0090] The orientation O(s) may be calculated on the basis of the scalar local velocity v(t)=ds/dt and the change dO/dt of the orientation of the rail vehicle 2 therefore.

[0091] The localization facility 20 also has a localization unit 25 for determining an absolute position p.sub.abs(t) of the rail vehicle 2.

[0092] Part of the localization unit 25 is a correlation function-generating unit 25a, which is configured to generate a complex cross-correlation function r.sub.c(s) on the basis of the determined distance-dependent orientation O(s) of the rail vehicle 2 and on the basis of reference data O.sub.ref(s) of a distance-dependent orientation. The correlation function-generating unit 25a receives the reference data O.sub.ref(s) from a database 25b. The determined complex cross-correlation function r.sub.c(s) is transmitted to a starting point determining unit 25c, which determines a starting point so in the reference data O.sub.ref(s) at the location at which the maximum of the complex cross-correlation function r.sub.c(s) is situated.

[0093] An absolute start position P.sub.abs0 of the rail vehicle 2 is determined by a start point determining unit 25d using the starting point s.sub.0. The start point determining unit 25d determines an absolute start position Pabs0 r allocated to the starting point s.sub.0 in the reference data O.sub.ref(s), in a map KD, which it receives transmitted from the database 25b already mentioned.

[0094] Finally, a path s(t) is determined on the basis of the correlated reference data O.sub.ref(s), which path the rail vehicle 2 has covered since passing the absolute position P.sub.abs0. Subsequently, a current, dynamic absolute position p.sub.abs(t) of the rail vehicle 2 is determined on the map KD using the determined path s(t) and a projection of this path s(t) onto the railroad on the map KD.

[0095] FIG. 3 represents a graph 30, which represents an auto-correlation a of an orientation of a rail vehicle 2 as a function of the covered distance s of the rail vehicle 2. In particular, a real-valued autocorrelation function a.sub.r(s) (with solid lines) and a complex-valued autocorrelation function a.sub.c(s) (with broken lines) of an orientation as a function of the distance s are shown.

[0096] The main lobe of the complex autocorrelation function a.sub.c(s) at s=0 is narrower than the main lobe of the real autocorrelation function a.sub.r(s). The complex autocorrelation function a.sub.c(s) does have small sidelobes, however, which have a spacing of 600 m from the main lobe and have less than 30% of the correlation value of the main lobe. It does not have any high secondary maxima therefore, and promises a stable, distinct localization in the case of a cross-correlation with a reference signal.

[0097] FIG. 4 shows a graph 40, which illustrates a real-valued cross-correlation function r.sub.r(s) (with solid lines) and a complex-valued cross-correlation function r.sub.c(s) (with broken lines). The cross-correlation functions r.sub.r(s), r.sub.c(s) indicate a correlation value between an orientation O(s) of a rail vehicle 2 determined on the basis of sensor measurement data SD and a reference orientation O.sub.ref(s) of a rail vehicle 2 determined on the basis of map data KD. In the case represented in FIG. 4, the actual starting point so lies at approximately 6,000 m and is illustrated by the absolute maximum of the complex-valued cross-correlation function r.sub.c(s). By contrast, the absolute maximum of the real-valued cross-correlation function r.sub.r(s) lies at approximately 4,900 m and therewith at the wrong location sof. When evaluating the real-valued cross-correlation function r.sub.r(s), instead the secondary maximum at approximately 6,000 m has to be determined as a starting point so although this secondary maximum with a correlation of approximately 0.85 is lower than the main maximum with a correlation of 1. The complex-valued cross-correlation function r.sub.c(s) at approximately 200 m and 3,000 m has secondary maxima with values of approximately 0.7. With 70% of the value of the main maximum, which has a value of 1, however, these are clearly attenuated so a distinct localization is possible.

[0098] FIG. 5 represents a graph 50, which illustrates a comparison of an orientation O(s) determined by measurement with a reference orientation O.sub.ref(s). The orientation O(s), whose starting point s.sub.0 was determined by way of the complex cross-correlation function r.sub.c(s), obviously matches the reference orientation O.sub.ref(s) very accurately. By contrast, an incorrect starting point s.sub.0f would be found by way of the real-valued cross-correlation function r.sub.r(s), so the two orientation functions O(s), Oref(s) would not match well either, and instead would be displaced relative to each other by the value s.sub.0-s.sub.of. Starting from the correct starting point s.sub.0 it will be possible to determine the current route point via the projection of the covered distance onto the mapped route. An absolute position of the rail vehicle can also be determined from this since an absolute position in the map, and therewith also globally, is to be allocated to each point of the route.

[0099] FIG. 6 represents a graph 60, which illustrates a calibration of an orientation sensor by comparing measured orientation data O(s) with reference orientation data O.sub.ref(s). The graph 60 shows orientation value in the angle unit.

[0100] As a rule, a sensor may not be exactly fitted in a rail vehicle 2 at the specified angle since increased accuracy is connected with disproportionate installation effort. A sensor installed in or on a rail vehicle 2 therefore has a deviation, in particular in its orientation, in respect of a predetermined measuring plane. As a result, determination of the change of orientation on the basis of the sensor measurement data SD, which is ascertained, for example, by the REMER method (REMER=Robust Ego Motion Estimation with Radar) already mentioned, supplies a constant rotation rate deviating from the value 0 in the case of travel in a straight line. Such a deviation is disadvantageous for forming a cross-correlation function r(k) as well as for other evaluation processes of the sensor data SD, such as object detection, for example. For this reason, it is expedient to determine the deviation angle ? of a sensor and perform a calibration to be able to carry out more exact localization.

[0101] During calibration, firstly a long straight track section Ak is identified in the reference data O.sub.ref(s) (drawn with solid lines), on which section the rail vehicle 2 has already traveled and orientation data O(s) (drawn in broken lines) has been recorded. A linear trend or a straight line G is subsequently determined in the corresponding measurement data section A.sub.k at the measured orientation O(s) by way of a fitting process. The gradient m=??/?s of the straight lines G is subsequently used to determine the deviation ? of the orientation of the radar sensor. For a straight-line course of the route with an angle in relation to a predetermined reference orientation of ?=0, the following results, as already mentioned, in accordance with equation (2) for the deviation

[00003]$?=\mathrm{arc}\sin \left(l\frac{??}{?s}\right),$

where 1 describes the spacing of the sensor from the turning point of the rail vehicle. The rotation or deviation ? can also be determined by way of regular checking.

[0102] FIG. 7 shows a schematic representation 70 of a track section or rail region 1 on which a rail vehicle 2 is underway in the direction of the arrow. The rail vehicle 2 has a localization facility 20 with which an absolute position p.sub.abs(t) of the rail vehicle 2 is determined in the manner shown in conjunction with FIG. 1 to FIG. 6. The absolute position p.sub.abs(t) is transmitted to a control unit 71, which transmits control commands SB to a drive unit 72.

[0103] To conclude, reference is made once again to the fact that the previously described methods and apparatuses are merely preferred exemplary embodiments of the invention, and that the invention can be varied by a person skilled in the art without departing from the scope of the invention insofar as it is specified by the claims. For the sake of completeness, reference is also made to the fact that use of the indefinite article a or an does not preclude the relevant features from also being present multiple times. Similarly, the term unit does not preclude this from comprising a plurality of components, which can possibly also be spatially distributed.