Road surface reflectivity detection by lidar sensor

1. A method of determining a surface condition of a road of travel, the method comprising the steps of:

transmitting a light beam directed at a surface in the road of travel utilizing a lidar system;

analyzing a response at a photodetector of the lidar system after transmitting the light beam;

determining whether a form of precipitation is present on the road of travel in response to analyzing the response at the photodetector;

generating a precipitation indicating signal in response to the determination that the ground surface includes a form of precipitation on the road of travel, the precipitation indicating signal provided to an output device to enable stability control functionality.

2. The method of claim 1 wherein analyzing a response at the photodetector includes determining whether a reflective signal is received at the photodetector, wherein no reflective signal received by the photodetector indicates that the form of precipitation is present on the road of travel.

3. The method of claim 2 wherein a secondary sensing device is utilized in cooperation with the lidar system for increasing a probability of determining precipitation on the surface of the road.

4. The method of claim 3 wherein the secondary sensing device determines a type of precipitation on the surface of the road.

5. The method of claim 1 wherein the response includes light signals received at the photodetector, wherein the scattering of the light signals is increased for the received response in comparison to an expected reflective signal where precipitation is present.

6. The method of claim 5 wherein determining whether a scattering of the light signal is present comprises the steps of:

applying a sliding window to a reflected signal received by the photodetector;

applying a feature extraction technique to each respective window of the received reflected signal;

identifying whether a scattering is present within the reflected signal in response to analyzing the extracted features from each respective window.

7. The method of claim 6 wherein the feature extraction technique includes short signal statistics.

8. The method of claim 6 wherein the feature extraction technique includes a standard deviation.

9. The method of claim 6 wherein the feature extraction technique includes Fast Fourier Transforms coefficients.

10. The method of claim 6 wherein the feature extraction technique includes a wavelet transforms technique.

11. The method of claim 6 wherein the feature extraction technique includes principal component analysis.

12. The method of claim 6 wherein a secondary sensing device is utilized in cooperation with the lidar system for increasing a probability of determining precipitation on the surface of the road.

13. The method of claim 12 wherein the secondary sensing device determines a type of precipitation on the surface of the road.

14. The method of claim 5 wherein a classifier is applied to the extracted features identifying the road surface condition.

15. The method of claim 1 wherein analyzing a response at the photodetector includes determining whether a false object is present in a reflective surface on the road of travel.

16. The method of claim 15 wherein the false object are analyzed as objects located beneath the surface of the road based on distance that extends beyond a distance to an intersection of the light beam and the surface of the road.

17. The method of claim 15 wherein the distance to the false object outside of a predetermined threshold of an expected distance to the surface of the road.

18. The method of claim 15 wherein analyzing a response at the photodetector includes determining whether a false object is present in a reflective surface on the road of travel comprises the steps of:

identifying a ground plane using a plane fitting;

identifying false object points located below the surface of the road;

collecting false object points from a plurality of reflected rays received by the photodetector, the plurality of reflected rays intersecting the surface of the road is at a substantially same location of the road surface.

19. The method of claim 18 wherein a secondary sensing device is utilized in cooperation with the lidar system for increasing a probability of determining precipitation on the surface of the road.

20. The method of claim 19 wherein the secondary sensing device determines a type of precipitation on the surface of the road.