MOTOR VEHICLE DRIVER ASSISTANCE SYSTEM AND METHOD

Abstract

A motor vehicle driver assistance system including a vehicular data module configured to derive a trailer weight and a vehicular control parameter determiner configured to determine a parameter value of a vehicular control parameter based on the trailer weight derived.

Claims

1. A motor vehicle driver assistance system comprising: a vehicular data module configured to derive a trailer weight value; and a vehicular control parameter determiner configured to determine a parameter value of a vehicular control parameter based on the trailer weight value derived.

2. The motor vehicle driver assistance system as in claim 1, wherein the vehicular data module is configured to receive engine torque data and to derive the trailer weight value from the engine torque data received.

3. The motor vehicle driver assistance system as in claim 2, wherein the vehicular data module is configured to receive vehicular speed data and to derive the trailer weight value by correlating the engine torque data received with the vehicular speed data received.

4. The motor vehicle driver assistance system as in claim 1, wherein the vehicular control parameter comprises a steering angle of a motor vehicle.

5. The motor vehicle driver assistance system as in claim 1, further comprising a vehicular category classifier configured to classify a motor vehicle into one of a plurality of trailer categories based on the trailer weight value derived.

6. The motor vehicle driver assistance system as in claim 5, wherein the vehicular control parameter determiner is configured to determine the parameter value of the vehicular control parameter based on the one of the plurality of trailer categories that the motor vehicle is classified into.

7. The motor vehicle driver assistance system as in claim 1, further comprising a vehicular control parameter calibrator configured to fine-tune the vehicular control parameter.

8. The motor vehicle driver assistance system as in claim 7, wherein the vehicular data module is configured to receive vehicular data, and the vehicular control parameter calibrator is configured to fine-tune the vehicular control parameter based on the vehicular data received.

9. The motor vehicle driver assistance system as in claim 8, wherein the vehicular control parameter calibrator is configured to fine-tune the vehicular control parameter based on the vehicular data comprising at least one of engine torque data, steering angle data, yaw rate data, row rate data, pitch rate data, row axis direction acceleration data, pitch axis direction acceleration data, row axis direction velocity data, pitch axis direction velocity data, vehicular speed data, trailer dimensions data, road pitch axis incline angle data, road row axis incline angle data or lane curvature data.

10. The motor vehicle driver assistance system as in claim 1, further comprising a vehicular controller configured to control a motor vehicle using the parameter value of the vehicular control parameter determined.

11. (canceled)

12. A motor vehicle driver assistance system comprising: a vehicular data module configured to derive a trailer weight value; wherein the vehicular data module is configured to receive engine torque data and to derive the trailer weight value from the engine torque data received; wherein the vehicular data module is configured to receive vehicular speed data and to derive the trailer weight value by correlating the engine torque data received with the vehicular speed data received; wherein the vehicular control parameter comprises a steering angle of a motor vehicle; a vehicular category classifier configured to classify the motor vehicle into one of a plurality of trailer categories based on the trailer weight value derived; a vehicular control parameter determiner configured to determine a parameter value of a vehicular control parameter based on the trailer weight value derived; wherein the vehicular control parameter determiner is configured to determine the parameter value of the vehicular control parameter based on the one of the plurality of trailer categories that the motor vehicle is classified into; a vehicular control parameter calibrator configured to fine-tune the vehicular control parameter; wherein the vehicular data module is configured to receive vehicular data, and the vehicular control parameter calibrator is configured to fine-tune the vehicular control parameter based on the vehicular data received; wherein the vehicular control parameter calibrator is configured to fine-tune the vehicular control parameter based on the vehicular data comprising at least one of engine torque data, steering angle data, yaw rate data, row rate data, pitch rate data, row axis direction acceleration data, pitch axis direction acceleration data, row axis direction velocity data, pitch axis direction velocity data, the vehicular speed data, trailer dimensions data, road pitch axis incline angle data, road row axis incline angle data or lane curvature data; and a vehicular controller configured to control a motor vehicle using the parameter value of the vehicular control parameter determined.

13. A computer-implemented motor vehicle driver assistance method comprising the acts of: deriving a trailer weight value; and determining a parameter value of a vehicular control parameter based on the trailer weight value derived.

14. The computer-implemented motor vehicle driver assistance method as in claim 13, further comprising the act of receiving engine torque data, wherein the act of deriving the trailer weight value comprises the act of deriving the trailer weight value from the engine torque data received.

15. The computer-implemented motor vehicle driver assistance method as in claim 14, further comprising the act of receiving vehicular speed data, wherein the act of deriving the trailer weight value from the engine torque data received comprises the act of correlating the engine torque data received with the vehicular speed data received.

16. The computer-implemented motor vehicle driver assistance method as in claim 13, wherein the act of determining the parameter value of the vehicular control parameter comprises the act of determining the parameter value of the vehicular control parameter comprising a steering angle of a motor vehicle.

17. The computer-implemented motor vehicle driver assistance method as in claim 13, further comprising the act of classifying a motor vehicle into one of a plurality of trailer categories based on the trailer weight value derived.

18. The computer-implemented motor vehicle driver assistance method as in claim 17, wherein the act of determining the parameter value of the vehicular control parameter comprises the act of determining the parameter value of the vehicular control parameter based on the one of the plurality of trailer categories that the motor vehicle is classified into.

19. The computer-implemented motor vehicle driver assistance method as in claim 13, further comprising the act of fine-tuning the vehicular control parameter.

20. The computer-implemented motor vehicle driver assistance method as in claim 13, further comprising the act of controlling a motor vehicle using the parameter value of the vehicular control parameter determined.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0076] These and other features, aspects, and advantages will become better understood with regard to the following description, appended claims, and accompanying drawings where:

[0077] FIG. 1 shows a motor vehicle driver assistance system;

[0078] FIG. 2 shows a motor vehicle comprising the motor vehicle driver assistance system of FIG. 1; and

[0079] FIG. 3 shows a diagram for a motor vehicle driver assistance method.

[0080] In the drawings, like parts are denoted by like reference numerals.

DESCRIPTION

[0081] In the summary above, in this description, in the claims below, and in the accompanying drawings, reference is made to particular features (including method steps) of the invention. It is to be understood that the disclosure in this specification includes all possible combinations of such particular features. For example, where a particular feature is disclosed in the context of a particular aspect or embodiment, or a particular claim, that feature may also be used, to the extent possible, in combination with and/or in the context of other particular aspects and embodiments, and in the disclosures generally.

[0082] FIG. 1 shows a motor vehicle driver assistance system 100 that may include a vehicular data module 110, a vehicular category classifier 120, a vehicular control parameter determiner 130, a vehicular control parameter calibrator 140 and a vehicular controller 150. The motor vehicle driver assistance system 100 may comprise hardware, such as at least one processor, volatile memory, and/or non-volatile memory, software including instructions executable by a processor, or a combination of software and hardware.

[0083] The vehicular data module 110 is configured to derive a trailer weight value. The vehicular data module 110 may be configured to receive engine torque data and to derive a trailer weight value from the engine torque data received. The vehicular data module 110 may also be configured to receive vehicular speed data and engine torque data, and to derive a trailer weight value by correlating the engine torque data received with the vehicular speed data received. Further, the vehicular data module may be configured to receive vehicular data. The vehicular data module 110 may comprise hardware, such as at least one processor, volatile memory, and/or non-volatile memory, software comprising instructions executable by a processor, or a combination of software and hardware.

[0084] Vehicular data may include at least one of engine torque data, steering angle data, yaw rate data, row rate data, pitch rate data, row axis direction acceleration data, pitch axis direction acceleration data, row axis direction velocity data, pitch axis direction velocity data, vehicular speed data, trailer dimensions data, road pitch axis incline angle data, road row axis incline angle data or lane curvature data.

[0085] The vehicular category classifier 120 is configured to classify a motor vehicle into one of a plurality of trailer categories based on a trailer weight value. The vehicular category classifier 120 may be configured to receive information from a trailer connection sensor that detects whether a trailer is connected to a motor vehicle. The vehicular category classifier 120 may comprise hardware, such as at least one processor, volatile memory, and/or nonvolatile memory, software comprising instructions executable by a processor, or a combination of software and hardware.

[0086] A trailer category may, for example, be “No Trailer”, “Light Trailer”, “Average Trailer” or “Heavy Trailer”. Each category may comprise at least one predetermined parameter value for at least one vehicular control parameter. For instance, if a motor vehicle is classified under an “Average Trailer” category, the lane curvature detected is 10 meters radius and the vehicular speed is 30 km/h, then a vehicular control parameter, for example, a steering angle of the motor vehicle, may comprise a parameter value of 20 degrees.

[0087] The vehicular control parameter determiner 130 is configured to determine a parameter value of a vehicular control parameter based on a trailer weight value. The vehicular control parameter determiner 130 may be configured to determine a value of a vehicular control parameter based on one of a plurality of trailer categories that a motor vehicle is classified into. The vehicular control parameter determiner 130 may comprise hardware, such as at least one processor, volatile memory, and/or non-volatile memory, software comprising instructions executable by a processor, or a combination of software and hardware.

[0088] The vehicular control parameter calibrator 140 is configured to fine-tune a vehicular control parameter. The vehicular control parameter calibrator 140 may be configured to fine-tune a vehicular control parameter based on vehicular data. For instance, if vehicular data received indicate a non-zero pitch axis direction acceleration, suggesting that a motor vehicle is skidding sideways, the vehicular control parameter calibrator 140 may fine-tune a vehicular control parameter, for example, a steering angle, by changing its parameter value from 20 degrees to 15 degrees. The vehicular control parameter calibrator 140 may comprise hardware, such as at least one processor, volatile memory, and/or non-volatile memory, software comprising instructions executable by a processor, or a combination of software and hardware.

[0089] The vehicular controller 150 is configured to control a motor vehicle using a value of a vehicular control parameter. The vehicular controller 150 may cause a physical change to a vehicle, for example, a change in a steering angle, a shift into a different gear or an application of brakes. The vehicular controller 150 may comprise hardware, such as at least one processor, volatile memory, and/or non-volatile memory, software comprising instructions executable by a processor, or a combination of software and hardware.

[0090] FIG. 2 shows a motor vehicle 160 comprising the motor vehicle driver assistance system 100. The motor vehicle 160 may be a car.

[0091] FIG. 3 shows a diagram for a motor vehicle driver assistance method 200 using the motor vehicle driver assistance system 100. The steps or acts of the motor vehicle driver assistance method 200 may be performed by at least one processor, for instance, by the at least one processor executing instructions stored on at least one non-transitory computer-readable medium.

[0092] At step 202, the motor vehicle driver assistance method 200 begins, for example, when a motor vehicle 160 is started or when the motor vehicle 160 is driven off from rest. At step 204, a trailer weight value is derived. The trailer weight value may be obtained directly, such as, by weighing a trailer and providing the trailer weight value to the motor vehicle driver assistance system 100. The trailer weight value may also be obtained indirectly, for example, by estimation. When the trailer is connected to the motor vehicle 160, the weight of the trailer may be estimated by using the engine torque data. For instance, more engine torque would be required to drive off the motor vehicle 160 when it is towing a heavier trailer compared to when it is towing a lighter trailer. In addition, more engine torque would be required to drive the motor vehicle 160 at a certain speed when it is towing a heavier trailer compared to when it is towing a lighter trailer.

[0093] Then at step 206, the motor vehicle 160 is classified into one of a plurality of trailer categories based on the trailer weight value. Subsequently, at step 208, at least one parameter value of at least one vehicular control parameter is determined based on the trailer category the motor vehicle 160 is classified into.

[0094] Thereafter, at step 210, vehicular data are received. Then, at step 212, the at least one vehicular control parameter is fine-tuned based on the vehicular data received. Subsequently, at step 214, the motor vehicle 160 is controlled using the parameter value of the vehicular control parameter.

[0095] Optionally, step 210, step 212 and step 214 may be iteratively performed until the motor vehicle driver assistance method 200 ends.

[0096] Finally, at step 216, the motor vehicle driver assistance method 200 ends, for example, when the ignition is turned off.

[0097] Although the invention has been described in considerable detail with reference to certain embodiments or aspects, other embodiments or aspects are possible.

[0098] For example, at step 206, the motor vehicle driver assistance system 100 receives information on whether a trailer is connected to the motor vehicle 160, for example, by a trailer connection sensor.

[0099] Therefore, the spirit and scope of the appended claims should not be limited to the description of the embodiments contained herein.

[0100] All features disclosed in this specification (including the appended claims, abstract, and accompanying drawings) may be replaced by alternative features serving the same, equivalent, or similar purpose, unless expressly stated otherwise. Thus, unless expressly stated otherwise, each feature disclosed is one example only of a generic series of equivalent or similar features.