Determining the characteristics of a road surface by means of a 3D camera
A method and a device are provided for detecting the condition of a pavement or roadway travel surface on which a vehicle is traveling. A 3D camera acquires 3D camera image data including at least one image of surroundings including the roadway travel surface extending in front of the vehicle in the direction of motion thereof. Transverse height profiles of the roadway travel surface that respectively extend along transverse lines extending transversely to the vehicle's direction of motion are determined from the 3D camera image data. The condition of the roadway travel surface is detected from the determined transverse height profiles.
1. A method of detecting a condition of a roadway travel surface on which a vehicle is traveling, wherein the method comprises:
with a 3D camera of the vehicle, acquiring 3D camera image data including at least one image of surroundings including the roadway travel surface extending in front of the vehicle in a direction of motion thereof on the roadway travel surface,
analyzing the 3D camera image data and therefrom determining transverse height profiles of the roadway travel surface that respectively extend along successive transverse lines which extend transversely to the direction of motion of the vehicle on the roadway travel surface, and
detecting the condition of the roadway travel surface from the transverse height profiles that have been determined from the 3D camera image data along the transverse lines.
2. The method according to claim 1 , wherein the condition of the roadway travel surface is detected by comparing the transverse height profiles with stored height profiles having respective known conditions.
3. The method according to claim 1 , further comprising additionally analyzing 2D image data of at least one monocular camera included in the 3D camera, and including the 2D image data into the detecting of the condition of the roadway travel surface.
4. The method according to claim 3 , wherein the 2D image data are analyzed by at least one of a texture analysis and a pattern analysis.
5. The method according to claim 3 , wherein the 2D image data are analyzed by at least one of an edge analysis and a color analysis.
6. The method according to claim 1 , further comprising estimating a coefficient of friction from the detected condition of at least one area of the roadway travel surface extending in front of the vehicle in the direction of motion thereof.
7. The method according to claim 6 , further comprising pre-controlling at least one of steering interventions and braking interventions of the vehicle dependent on the coefficient of friction.
8. The method according to claim 1 , wherein the 3D camera is a stereo camera.
9. A device for detecting a condition of a roadway travel surface on which a vehicle is traveling in a direction of motion, wherein the device comprises:
a 3D camera of the vehicle configured to produce 3D camera image data including an image of surroundings including the roadway travel surface in front of the vehicle in the direction of motion thereof,
an image analyzer of the vehicle configured to analyze the 3D camera image data and therefrom to determine transverse height profiles of the roadway travel surface that respectively extend along successive transverse lines extending transversely to the direction of motion of the vehicle on the roadway travel surface, and
a detecting circuit arrangement configured to detect the condition of the roadway travel surface from the transverse height profiles.
10. The method according to claim 1 , wherein the analyzing of the 3D camera image data is performed by an image analyzer of the vehicle, and the detecting of the condition of the roadway travel surface is performed by a circuit arrangement of the vehicle.
11. The method according to claim 1 , wherein the detected condition of the roadway travel surface comprises a detected material of the roadway travel surface selected from asphalt, gravel, sand and/or cobblestone.
12. The method according to claim 1 , wherein the detected condition of the roadway travel surface comprises a detected material on the roadway travel surface selected from oil, water, ice and/or snow.
13. The method according to claim 1 , wherein the detected condition of the roadway travel surface comprises a detected shape or evenness of the roadway travel surface along each respective one of the transverse height profiles and in the direction of motion of the vehicle across successive ones of the transverse height profiles.
14. The method according to claim 13 , wherein the detected shape or evenness is selected from a bumpy surface shape, a rutted surface shape and/or a pot-holed surface shape.
15. The method according to claim 1 , wherein the detecting of the condition of the roadway travel surface comprises performing a quantitative analysis of the transverse height profiles.
16. The method according to claim 15 , wherein the quantitative analysis comprises a frequency analysis of the transverse height profiles.
17. The method according to claim 15 , wherein the quantitative analysis comprises an analysis of the transverse width and longitudinal length of depressions and/or bumps represented in the transverse height profiles, wherein the transverse width extends along the transverse height profiles, and the longitudinal length extends in the direction of motion of the vehicle transversely across a succession of the transverse height profiles.
18. The method according to claim 15 , wherein the quantitative analysis comprises an amplitude determination of an amplitude of roughness or unevenness represented in the transverse height profiles.