Traction control based on friction coefficient estimation
Method and apparatus are disclosed for traction control based on friction coefficient estimation. An example vehicle includes a plurality of sensors to measure qualities of a surface of a road and an anti-lock brake system module. The anti-lock brake system module (a) estimates confidence values for different road surface types based on the qualities of the surface of the road, (b) estimates a coefficient of friction between the road and tires of the vehicle based on the confidence values, and (c) adapt a traction control system by altering a target slip based on the coefficient of friction.
1. A vehicle comprising:
a plurality of sensors to measure qualities of a road surface;
a processor configured to:
receive a signal from a first sensor of the plurality of sensors;
apply a first filter to the signal, the first filter configured to filter out signals from a road surface of a first road surface type;
estimate a first confidence value that a road the vehicle is on is a road surface of the first road surface type based on a change to the signal that results from applying the first filter to the signal;
estimate a coefficient of friction between the road surface and tires of the vehicle based on a final confidence value, the final confidence value being based on the first confidence value; and
control wheels of the vehicle by altering a target slip based on the coefficient of friction.
2. The vehicle of claim 1 , wherein the first confidence value is representative of a likelihood that the road surface corresponds with a particular road surface type.
3. The vehicle of claim 1 , wherein the plurality of sensors includes a camera.
4. The vehicle of claim 3 , wherein the processor configured to estimate the first confidence value is further configured to:
capture an image of a road surface ahead of the vehicle; and
compare the image to a reference image of the first road surface type.
5. The vehicle of claim 3 , wherein the processor configured to estimate the first confidence value is further configured to:
capture a series of images of a road surface ahead of the vehicle;
determine luminosity values and changes of the luminosity values within the series of images; and
compare the luminosity values and changes of the luminosity values to values stored in a table.
6. The vehicle of claim 1 , wherein the plurality of sensors includes an ultrasonic sensor.
7. The vehicle of claim 6 , wherein the processor configured to estimate the first confidence value is further configured to:
broadcast a wave signal in front of the vehicle; and
analyze reflection patterns and refraction patterns of the wave signal off the road surface to determine the first confidence value.
8. The vehicle of claim 1 , wherein the plurality of sensors includes at least one of a suspension vibration sensor or an accelerometer.
9. The vehicle of claim 1 , wherein the processor is further configured to:
apply a weighing factor to the first confidence value based on environmental data information received from a remote weather server.
10. The vehicle of claim 1 , wherein the processor configured to estimate the first confidence value is further configured to:
determine a steering current draw of the vehicle.
11. The vehicle of claim 1 , wherein the processor is further configured to:
determine a second confidence value that the road is a road surface of the first road type; and
aggregate the first confidence value and the second confidence value to determine the final confidence value.
12. The vehicle of claim 1 , wherein estimating the coefficient of friction between the road surface and tires of the vehicle based on the final confidence value is further based on a determination that the first confidence value is greater than a third confidence value that the vehicle is on a road of a second road type.
13. The vehicle of claim 1 , wherein estimating the coefficient of friction between the road surface and tires of the vehicle based on the final confidence value is further based on a determination that the final confidence value is greater than a threshold.
14. A method comprising:
receiving a signal from a first sensor of a plurality of sensors of a vehicle;
applying a first filter to the signal, the first filter configured to filter out signals from a road surface of a first road surface type;
estimating a first confidence value that a road the vehicle is on is a road surface of the first road surface type based on a change to the signal that results from applying the first filter to the signal;
estimating a coefficient of friction between the road surface and tires of the vehicle based on a final confidence value, the final confidence value being based on the first confidence value; and
controlling wheels of the vehicle by altering a target slip based on the coefficient of friction.