Friction coefficient estimation from camera and wheel speed data

• US 9,643,617 B2
• Filed: 12/09/2013
• Issued: 05/09/2017
• Est. Priority Date: 12/20/2012
• Status: Active Grant

• Current Assignee: Continental Teves AG & Co. OHG (Continental AG)
• Original Assignee: Continental Teves AG & Co. OHG (Continental AG)
• Inventors: Fischer, Daniel, Stoelzl, Stefan, Koebe, Andreas
• Primary Examiner(s): Le, Vu
• Assistant Examiner(s): BEG, SAMAH A
• Application Number:
  US14/431,208
• Publication Number:
  US 20150251659A1
• Time in Patent Office: 1,247 Days
• Field of Search: None
• CPC Class Codes: B60T 8/171 Detecting parameters used in the regulation; Measuring values used in the regulation
• CPC Class Codes: B60T 8/172 Determining control parameters used in the regulation, e.g. by calculations involving measured or detected parameters B60T8/17551 takes precedence
• CPC Class Codes: B60T 8/1725 Using tyre sensors, e.g. Sidewall Torsion sensors [SWT] for tyre pressure and temperature detection B60C23/00
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2520/28 Wheel speed
• CPC Class Codes: B60W 40/068 Road friction coefficient
• CPC Class Codes: G06V 20/588 Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road

Abstract

A method and an apparatus for estimating a friction coefficient in a moving vehicle analyze image data from a forward-looking vehicle camera to produce a camera friction coefficient μ_k, and analyze tire slip and tire vibration based on a wheel speed signal to produce a wheel friction coefficient μ_w. The camera and wheel friction coefficients are both considered to produce a proactive estimated friction coefficient that is primarily based on the camera friction coefficient μ_k, whereas the wheel friction coefficient μ_w is taken into account to check plausibility of the camera friction coefficient μ_k.

Claims

1. A method for a moving vehicle, comprising:

analyzing image data of a forward-looking camera in the vehicle to produce a camera friction coefficient regarding a road surface represented in the image data,

analyzing a tire slip and a tire vibration of a tire of the vehicle based on a wheel speed signal to produce a wheel friction coefficient regarding adhesion between the tire and the road surface;

respectively assigning associated reliability information to the camera friction coefficient and the wheel friction coefficient; and

producing an estimated proactive friction coefficient as a merger of the camera friction coefficient and the wheel friction coefficient, wherein the camera friction coefficient is released directly as the estimated proactive friction coefficient when the associated reliability information assigned to the camera friction coefficient is high, a plausibility of the camera friction coefficient is checked and a value of the camera friction coefficient is confirmed based on the wheel friction coefficient to produce the estimated proactive friction coefficient when the associated reliability information assigned to the camera friction coefficient is low, and when the camera friction coefficient becomes unavailable then the wheel friction coefficient is released as the estimated proactive friction coefficient.

2. The method according to claim 1, further comprising synchronizing the camera friction coefficient and the wheel friction coefficient taking into account a travel speed of the vehicle.

3. The method according to claim 1, which is adjusted to characteristic field conditions of the vehicle and/or a driver of the vehicle by learning, comprising learning typical interferences in the image data which are identified by the checking of the plausibility of the camera friction coefficient using the wheel friction coefficient.

4. The method according to claim 1, wherein a mono camera is used as the camera.

5. The method according to claim 1, wherein a stereo camera is used as the camera.

6. The method according to claim 1, wherein a camera of a panoramic view system is used as the camera.

7. The method according to claim 1, wherein the estimated proactive friction coefficient, the camera friction coefficient and/or the wheel friction coefficient is transmitted to other driver assistance systems or driving dynamics control systems of the vehicle.

8. An apparatus for a moving vehicle,

including a forward-looking camera, at least one wheel speed sensor, and evaluation means,

wherein:

the evaluation means are configured to analyze image data of the camera in the vehicle to produce a camera friction coefficient regarding a road surface represented in the image data,

the wheel speed sensor is configured and arranged to transmit a wheel speed signal to the evaluation means,

the evaluation means are further configured to analyze a tire slip and a tire vibration of a tire of the vehicle based on the wheel speed signal to produce a wheel friction coefficient regarding adhesion between the tire and the road surface,

the evaluation means are further configured to respectively assign associated reliability information to the camera friction coefficient and the wheel friction coefficient, and

the evaluation means are further configured to produce an estimated proactive friction coefficient by a merger of the camera friction coefficient and the wheel friction coefficient, wherein the camera friction coefficient is released directly as the estimated proactive friction coefficient when the associated reliability information assigned to the camera friction coefficient is high, a plausibility of the camera friction coefficient is checked and a value of the camera friction coefficient is confirmed based on the wheel friction coefficient to produce the estimated proactive friction coefficient when the associated reliability information assigned to the camera friction coefficient is low, and when the camera friction coefficient becomes unavailable then the wheel friction coefficient is released as the estimated proactive friction coefficient.

9. A method of estimating an actual friction coefficient of a road surface on which a vehicle is driving, comprising steps:

a) obtaining image data of an image of said road surface, from a forward-looking camera of said vehicle;

b) by analyzing said image data, producing therefrom a camera friction coefficient as a first estimate of said actual friction coefficient of said road surface;

c) obtaining a wheel speed signal from a wheel speed sensor of said vehicle;

d) by analyzing said wheel speed signal, determining therefrom a tire slip and a tire oscillation regarding motion of a tire of said vehicle relative to said road surface;

e) based on said tire slip and said tire oscillation, determining a wheel friction coefficient as a second estimate of said actual friction coefficient of said road surface;

f) respectively assigning associated reliability information to the camera friction coefficient and the wheel friction coefficient; and

g) determining a proactive estimation of said actual friction coefficient of said road surface from said camera friction coefficient and said wheel friction coefficient, wherein said camera friction coefficient is released directly as said proactive estimation of said actual friction coefficient when said associated reliability information assigned to said camera friction coefficient is above a threshold, a plausibility of said camera friction coefficient is checked and a value of said camera friction coefficient is confirmed based on said wheel friction coefficient to produce said proactive estimation of said actual friction coefficient when said associated reliability information assigned to said camera friction coefficient is below said threshold, and when said camera friction coefficient becomes unavailable then said wheel friction coefficient is released as said proactive estimation of said actual friction coefficient.

10. The method according to claim 9, wherein said steps a) to g) are performed by at least one of electronic controllers and electronic evaluation units of said vehicle, and further comprising providing said proactive estimation of said actual friction coefficient to a system of said vehicle selected from a driver assistance system and a driving dynamics control system, and adjusting an operation of said system in response to and dependent on said proactive estimation of said actual friction coefficient.

11. The method according to claim 9, further comprising repetitively performing said steps a) to f) in successive cycles, and in each one of said cycles when said camera friction coefficient fails said plausibility check then adjusting said producing of said camera friction coefficient from said image data so that said camera friction coefficient is brought closer to correspondence with said wheel friction coefficient in subsequent ones of said cycles.

12. A method of estimating an actual friction coefficient of a road surface on which a vehicle is driving, comprising steps:

a) obtaining image data of an image of said road surface, from a forward-looking camera of said vehicle;

b) by analyzing said image data, producing therefrom a camera friction coefficient as a first estimate of said actual friction coefficient of said road surface;

c) obtaining a wheel speed signal from a wheel speed sensor of said vehicle;

d) by analyzing said wheel speed signal, determining therefrom a tire slip and a tire oscillation regarding motion of a tire of said vehicle relative to said road surface;

e) based on said tire slip and said tire oscillation, determining a wheel friction coefficient as a second estimate of said actual friction coefficient of said road surface;

f) providing a first reliability information indicative of a reliability of said camera friction coefficient;

g) when said first reliability information meets or exceeds a reliability threshold, then outputting said camera friction coefficient as an estimation of said actual friction coefficient;

h) when said first reliability information falls below said reliability threshold, then performing a plausibility check of said camera friction coefficient by comparing said camera friction coefficient with said wheel friction coefficient;

i) when said camera friction coefficient passes said plausibility check, then outputting said camera friction coefficient as an estimation of said actual friction coefficient; and

j) when said camera friction coefficient fails said plausibility check, then producing and outputting an estimation of said actual friction coefficient dependent on said wheel friction coefficient.

13. The method according to claim 12, wherein said producing of said estimation of said actual friction coefficient when said camera friction coefficient fails said plausibility check comprises averaging said camera friction coefficient and said wheel friction coefficient.

14. The method according to claim 13, further comprising providing a second reliability information indicative of a reliability of said wheel friction coefficient, and wherein said averaging comprises weighted averaging in which said camera friction coefficient and said wheel friction coefficient are weighted dependent on said first reliability information and said second reliability information respectively.

15. The method according to claim 12, wherein said producing of said estimation of said actual friction coefficient when said camera friction coefficient fails said plausibility check comprises providing said wheel friction coefficient as said estimation of said actual friction coefficient.

16. The method according to claim 12, wherein said steps a) to j) are performed by at least one of electronic controllers and electronic evaluation units of said vehicle, and further comprising providing said estimation of said actual friction coefficient to a system of said vehicle selected from a driver assistance system and a driving dynamics control system, and adjusting an operation of said system in response to and dependent on said estimation of said actual friction coefficient.