METHOD AND ELECTRONIC CONTROL SYSTEM FOR ASCERTAINING A DISTANCE TRAVELLED BY A VEHICLE

Abstract

A method and a corresponding electronic control system for ascertaining a distance traveled by a vehicle predicts with a Kalman filter a distance traveled by the vehicle using a change in angle of rotation of at least one right wheel and/or at least one left wheel of the vehicle for a specific period of time while the vehicle is traveling and an ascertained radius of the right wheel and/or ascertained circumference of the right wheel of the vehicle and/or an ascertained radius of the left wheel and/or ascertained circumference of the left wheel of the vehicle; and corrects the predicted traveled distance by a Kalman filter correction to ascertain the distance traveled by the vehicle using the predicted traveled distance and a local distance between at least two absolute positions of the vehicle recorded within the specific period of time with a time interval while the vehicle is traveling.

Claims

1. A method for ascertaining a distance traveled by a vehicle comprising: carrying out a prediction step of a Kalman filter so as to predict a predicted distance traveled by the vehicle using a change in angle of rotation of at least one right wheel and/or at least one left wheel of the vehicle for a specific period of time while the vehicle is traveling and an ascertained radius of the right wheel and/or ascertained circumference of the right wheel of the vehicle and/or an ascertained radius of the left wheel and/or ascertained circumference of the left wheel of the vehicle; and carrying out a correction step of the Kalman filter so as to correct the predicted traveled distance so as to ascertain the distance traveled by the vehicle using the predicted traveled distance and a local distance between at least two absolute positions of the vehicle that are recorded within the specific period of time with a time interval while the vehicle is traveling.

2. The method as claimed in claim 1, wherein the ascertained radius of the right wheel and/or the ascertained circumference of the right wheel of the vehicle is ascertained based on a stored radius of the right wheel and/or stored circumference of the right wheel of the vehicle and an ascertained radius error of the right wheel and/or ascertained circumference error of the right wheel of the vehicle and/or the ascertained radius of the left wheel and/or ascertained circumference of the left wheel of the vehicle is ascertained based on a stored radius of the left wheel and/or stored circumference of the left wheel of the vehicle and an ascertained radius error of the left wheel and/or ascertained circumference error of the left wheel of the vehicle.

3. The method as claimed in claim 2, wherein the ascertained radius error of the right wheel and/or the ascertained circumference error of the right wheel of the vehicle and/or the stored radius of the right wheel and/or the stored circumference of the right wheel of the vehicle and/or the ascertained radius error of the left wheel and/or the ascertained circumference error of the left wheel of the vehicle and/or the stored radius of the left wheel and/or the stored circumference of the left wheel of the vehicle are corrected for use in a subsequent iteration of the Kalman filter based on a residual ascertained during the correction step of the Kalman filter and/or a Kalman gain.

4. The method as claimed in claim 1, wherein a state vector {circumflex over (x)} for describing a state of the vehicle has the form:
{circumflex over (x)}[xy.sub.R.sub.LS].sup.T where: x vehicle position in odometry coordinates with respect to an X-axis of an underlying coordinate system; y vehicle position in odometry coordinates with respect to a Y-axis of an underlying coordinate system; yaw angle (yaw) of the vehicle; .sub.R radius error between an ascertained radius of a right wheel and the stored radius of the right wheel; .sub.L radius error between an ascertained radius of the left wheel and the stored radius of the left wheel; and S using the traveled distance recorded by way of a global navigation satellite system.

5. The method as claimed in claim 1, wherein the prediction step is based on a non-linear motion model and/or the correction step is based on a linear measurement model.

6. The method as claimed in claim 5, wherein the non-linear motion model f is in the form: $f=\left[\begin{array}{c}{x}_{\left(k.Math.k-1\right)}\\ y_{\left(k.Math.k-1\right)}\\ {}_{\left(k.Math.k-1\right)}\\ {}_{\left(R,k.Math.k-1\right)}\\ {}_{\left(L,k.Math.k-1\right)}\\ S_{\left(k.Math.k-1\right)}\end{array}\right]=\left[\begin{array}{c}{x}_{\left(k-1.Math.k-1\right)}+s_k\cos \left({}_{\left(k-1.Math.k-1\right)}+\frac{{}_k}{2}\right)\\ y_{\left(k-1.Math.k-1\right)}+s_k\sin \left({}_{\left(k-1.Math.k-1\right)}+\frac{{}_k}{2}\right)\\ {}_{\left(k-1.Math.k-1\right)}+{}_k\\ {}_{\left(R,k-1.Math.k-1\right)}\\ {}_{\left(L,k-1.Math.k-1\right)}\\ S_{\left(k-1.Math.k-1\right)}+s_k\end{array}\right]$ where: s traveled distance recorded using odometry; L.sub.TW distance between right and left wheel; r.sub.R, real radius of the right wheel; r.sub.L, real radius of the left wheel; r.sub.R,s stored radius of the right wheel; r.sub.L,s stored radius of the left wheel; r.sub.R,e ascertained radius of the right wheel; r.sub.L,e ascertained radius of the left wheel; .sub.R change in angle of rotation of the right wheel; .sub.L change in angle of rotation of the left wheel; change in yaw angle of the vehicle.

7. The method as claimed in claim 6, wherein the traveled distance (s) recorded using odometry and/or the change in yaw angle of the vehicle () of the non-linear motion model are ascertained as follows: $s_k=\frac{1}{2}\left({}_{R,k}\left(r_{R,s}+{}_{R,k}\right)+{}_{L,k}\left(r_{L,s}+{}_{L,k}\right)\right)\mathrm{and}/\mathrm{or}{}_k=\frac{1}{L_{\mathrm{TW}}}\left({}_{R,k}\left(r_{R,s}+{}_{R,k}\right)-{}_{L,k}\left(r_{L,s}+{}_{L,k}\right)\right)$

8. The method as claimed in claim 5, wherein the linear measurement model of the correction step of the Kalman filter is in the following form:
z.sub.k=[S.sub.(k|k)].sup.T, wherein S describes the traveled distance ascertained by way of a global navigation satellite system.

9. The method as claimed in claim 1, wherein the traveled distance (S) recorded by way of a global navigation satellite system is reset with a chronologically new GNSS measurement after carrying out the correction step of the Kalman filter.

10. The method as claimed in claim 1, wherein the ascertained traveled distance and/or position information of the vehicle determined using the ascertained traveled distance is provided for use by an at least partially automated driving control system.

11. An electronic control device for ascertaining a distance traveled by a vehicle, wherein the control device is configured to carry out a method having the following steps: carrying out a prediction step of a Kalman filter so as to predict a predicted distance traveled by the vehicle using a change in angle of rotation of at least one right wheel and/or at least one left wheel of the vehicle for a specific period of time while the vehicle is traveling and an ascertained radius of the right wheel and/or ascertained circumference of the right wheel of the vehicle and/or an ascertained radius of the left wheel and/or ascertained circumference of the left wheel of the vehicle; carrying out a correction step of the Kalman filter so as to correct the predicted traveled distance so as to ascertain the distance traveled by the vehicle using the predicted traveled distance and a local distance between at least two absolute positions of the vehicle that are recorded within the specific period of time with a time interval while the vehicle is traveling.

12. The electronic control device as claimed in claim 11, wherein the ascertained radius of the right wheel and/or the ascertained circumference of the right wheel of the vehicle is ascertained based on a stored radius of the right wheel and/or stored circumference of the right wheel of the vehicle and an ascertained radius error of the right wheel and/or ascertained circumference error of the right wheel of the vehicle and/or the ascertained radius of the left wheel and/or ascertained circumference of the left wheel of the vehicle is ascertained based on a stored radius of the left wheel and/or stored circumference of the left wheel of the vehicle and an ascertained radius error of the left wheel and/or ascertained circumference error of the left wheel of the vehicle.

13. The electronic control device as claimed in claim 12, wherein the ascertained radius error of the right wheel and/or the ascertained circumference error of the right wheel of the vehicle and/or the stored radius of the right wheel and/or the stored circumference of the right wheel of the vehicle and/or the ascertained radius error of the left wheel and/or the ascertained circumference error of the left wheel of the vehicle and/or the stored radius of the left wheel and/or the stored circumference of the left wheel of the vehicle are corrected for use in a subsequent iteration of the Kalman filter based on a residual ascertained during the correction step of the Kalman filter and/or a Kalman gain.

14. The electronic control device as claimed in claim 11, wherein a state vector {circumflex over (x)} for describing a state of the vehicle has the form:
{circumflex over (x)}[x y .sub.R .sub.L S].sup.T where: x vehicle position in odometry coordinates with respect to an X-axis of an underlying coordinate system; y vehicle position in odometry coordinates with respect to a Y-axis of an underlying coordinate system; yaw angle (yaw) of the vehicle; .sub.R radius error between an ascertained radius of a right wheel and the stored radius of the right wheel; .sub.L radius error between an ascertained radius of the left wheel and the stored radius of the left wheel; and S using the traveled distance recorded by way of a global navigation satellite system.

15. The electronic control device as claimed in claim 11, wherein the prediction step is based on a non-linear motion model and/or the correction step is based on a linear measurement model.

16. The electronic control device as claimed in claim 15, wherein the non-linear motion model f is in the form: $f=\left[\begin{array}{c}{x}_{\left(k.Math.k-1\right)}\\ y_{\left(k.Math.k-1\right)}\\ {}_{\left(k.Math.k-1\right)}\\ {}_{\left(R,k.Math.k-1\right)}\\ {}_{\left(L,k.Math.k-1\right)}\\ S_{\left(k.Math.k-1\right)}\end{array}\right]=\left[\begin{array}{c}{x}_{\left(k-1.Math.k-1\right)}+s_k\cos \left({}_{\left(k-1.Math.k-1\right)}+\frac{{}_k}{2}\right)\\ y_{\left(k-1.Math.k-1\right)}+s_k\sin \left({}_{\left(k-1.Math.k-1\right)}+\frac{{}_k}{2}\right)\\ {}_{\left(k-1.Math.k-1\right)}+{}_k\\ {}_{\left(R,k-1.Math.k-1\right)}\\ {}_{\left(L,k-1.Math.k-1\right)}\\ S_{\left(k-1.Math.k-1\right)}+s_k\end{array}\right]$ where: s traveled distance recorded using odometry; L.sub.TW distance between right and left wheel; r.sub.R, real radius of the right wheel; r.sub.L, real radius of the left wheel; r.sub.R,s stored radius of the right wheel; r.sub.L,s stored radius of the left wheel; r.sub.R,e ascertained radius of the right wheel; r.sub.L,e ascertained radius of the left wheel; .sub.R change in angle of rotation of the right wheel; .sub.L change in angle of rotation of the left wheel; change in yaw angle of the vehicle.

17. The electronic control device as claimed in claim 16, wherein the traveled distance (s) recorded using odometry and/or the change in yaw angle of the vehicle () of the non-linear motion model are ascertained as follows: $s_k=\frac{1}{2}\left({}_{R,k}\left(r_{R,s}+{}_{R,k}\right)+{}_{L,k}\left(r_{L,s}+{}_{L,k}\right)\right)\mathrm{and}/\mathrm{or}{}_k=\frac{1}{L_{\mathrm{TW}}}\left({}_{R,k}\left(r_{R,s}+{}_{R,k}\right)-{}_{L,k}\left(r_{L,s}+{}_{L,k}\right)\right)$

18. The electronic control device as claimed in claim 15, wherein the linear measurement model of the correction step of the Kalman filter is in the following form:
z.sub.k=[S.sub.(k|k)].sup.T, wherein S describes the traveled distance ascertained by way of a global navigation satellite system.

19. The electronic control device as claimed in claim 11, wherein the traveled distance (S) recorded by way of a global navigation satellite system is reset with a chronologically new GNSS measurement after carrying out the correction step of the Kalman filter.

20. The electronic control device as claimed in claim 11, wherein the ascertained traveled distance and/or position information of the vehicle determined using the ascertained traveled distance is provided for use by an at least partially automated driving control system.

Description

DESCRIPTION OF THE FIGURES

[0082] Some refinements of the method and of the electronic control device are specified in the dependent claims. Further embodiments also emerge from the following description of exemplary embodiments on the basis of figures.

[0083] In each case schematically:

[0084] FIG. 1 shows one embodiment of the method 100 for ascertaining a distance traveled by a vehicle 300 according to a first aspect of the disclosure, and

[0085] FIG. 2 shows one embodiment of the electronic control device 200 of the vehicle 300 for ascertaining a distance traveled by the vehicle 300 according to a second aspect of the disclosure.

DETAILED DESCRIPTION OF THE FIGURES

[0086] FIG. 1 shows one embodiment of the method 100 for ascertaining a distance traveled, in particular by way of an electronic control device 200 according to FIG. 2, by a vehicle 300 according to a first aspect of the disclosure, wherein, in a step 102, a prediction step of a Kalman filter 226 is carried out so as to predict a predicted distance traveled by the vehicle 300 using a change in angle of rotation of at least one right wheel and/or at least one left wheel of the vehicle 300 for a specific period of time while the vehicle 300 is traveling and an ascertained radius of the right wheel and/or ascertained circumference of the right wheel of the vehicle 300 and/or an ascertained radius of the left wheel and/or ascertained circumference of the left wheel of the vehicle 300. In a step 104, a correction step of the Kalman filter 226 is carried out so as to correct the predicted traveled distance so as to ascertain the distance traveled by the vehicle 300 using the predicted traveled distance and a local distance between at least two absolute positions of the vehicle 300 that are recorded within the specific period of time with a time interval while the vehicle 300 is traveling.

[0087] FIG. 2 shows one embodiment of the electronic control device 200 of the vehicle 300 for ascertaining a distance traveled by the vehicle 300 according to a second aspect of the disclosure, wherein the control device 200 is configured to carry out a method 100 as described with reference to FIG. 1. To this end, the electronic control device 200 has a controller 220 for carrying out a prediction step of a Kalman filter 226, wherein the prediction step is used to predict a predicted distance traveled by the vehicle 300 using a change in angle of rotation of at least one right wheel and/or at least one left wheel of the vehicle 300 for a specific period of time while the vehicle 300 is traveling and an ascertained radius of the right wheel and/or ascertained circumference of the right wheel of the vehicle and/or an ascertained radius of the left wheel and/or ascertained circumference of the left wheel of the vehicle 300. The wheels of the vehicle 300 are not illustrated separately in FIG. 2. Changes in angle of rotation of a wheel when rolling and the speed of a wheel may be recorded using a respective wheel speed sensor 260, 270, which is assigned to a wheel and for example outputs signals 262, 272 triggered by an encoder. An output signal 262, 272 from an encoder may for example describe a square-wave signal or a sinusoidal signal. It is thus possible to detect a change in angle of a wheel by counting the number of pulses in relation to the total number of pulses during one revolution of the wheel. The accuracy of the detection of the change in angle depends here on the resolution of the encoder. According to the example, the signals 262 from the speed sensor of the right rear wheel 260 and the signals 272 from the speed sensor of the left rear wheel 270 are used by the controller for the processing performed by the Kalman filter 226.

[0088] The controller 220 is furthermore designed to carry out a correction step of the Kalman filter 226 so as to correct the predicted traveled distance so as to ascertain the distance traveled by the vehicle 300, for which purpose use is made of the predicted traveled distance and a local distance between at least two absolute positions of the vehicle that are recorded within the specific period of time with a time interval while the vehicle is traveling. Absolute positions that are ascertained in particular using the GNSS receiver 280 for receiving signals from a global navigation satellite system (GNSS) should be understood to mean in particular positions in coordinates of a global coordinate system, such as for example WGS84. In contrast thereto, odometry coordinates are often represented in a local vehicle coordinate system. The data 282 recorded by way of the GNSS receiver 280 are provided to the controller 220. To record odometry data, the electronic control device 200 may have sensors suitable for recording odometry, for example acceleration sensors and/or yaw rate sensors.

[0089] According to a further aspect of the disclosure, the electronic control device 200 is configured to perform a method according to at least one of the described embodiments of the disclosure.

[0090] According to at least one embodiment, the electronic control device 200 or the controller 220 comprises a processor 222 for data processing. In one development of the specified device 200, the specified device 200 has a data memory 224. In this case, the specified method is stored in the memory 224 in the form of a computer program, and the processor 222 is provided for carrying out the method when the computer program is loaded into the computing device from the memory. According to a further aspect of the invention, a computer program comprises program code means in order to perform all of the steps of one of the specified methods when the computer program is executed by the device 200. The Kalman filter 226 is in particular executed by way of the processor 222.

[0091] According to at least one embodiment, the controller 220 is designed to output signals 232, in particular the ascertained traveled distance and/or position information of the vehicle, by way of a signal interface 230, to a further electronic control device of the vehicle 300, for example for executing a driver assistance system or for (semi-)automated driving control 320, such as in particular automated parking assistance. According to at least one embodiment, the electronic control device 200 or the controller 220 or the method 100 may also be an integral part of a relevant (semi-)automated driving system 320, in particular in such a way that the (semi-)automated driving controls are also carried out by way of the electronic control device 200.

[0092] If it is found in the course of the proceedings that a feature or a group of features is not absolutely necessary, then the applicant aspires right now to a wording of at least one independent claim that no longer has the feature or the group of features. This may be, for example, a subcombination of a claim present on the filing date or a subcombination of a claim present on the filing date that is restricted by further features. Claims or combinations of features of this kind requiring rewording are intended to be understood as also covered by the disclosure of this application.

[0093] It should also be pointed out that refinements, features and variants of the invention which are described in the various embodiments or exemplary embodiments and/or shown in the figures may be combined with one another in any desired manner. Single or multiple features are interchangeable with one another in any desired manner. Combinations of features arising therefrom are intended to be understood as also covered by the disclosure of this application.

[0094] Back-references in dependent claims are not intended to be understood as a relinquishment of the attainment of independent substantive protection for the features of the back-referenced dependent claims. These features may also be combined with other features in any desired manner.

[0095] Features which are only disclosed in the description or features which are only disclosed in the description or in a claim in conjunction with other features may in principle be of independent significance essential to the invention. They may therefore also be individually included in claims for the purpose of delimitation from the prior art.