Office Action 1: Non-Final Rejection (2025-02-14)
Rejection types: 102 - Lack of Novelty

CLAIMS:
CL AIMS

1\. A driver-assistance system for keeping a vehicle in a lane of a road when driving along segments of the road, the driver-assistance system comprising:a GNSS receiver;
a camera; and a control unit,
wherein:
the driver-assistance system is configured to calculate respective local lane data dependent on a respective image of at least the respective segment generated by the camera,
the respective local lane data specifies a respective course of the lane on the respective segment relative to the vehicle,
the control unit is configured to steer the vehicle dependent on the respective local lane data such that the vehicle stays in the lane when driving on the respective segment,
the driver-assistance system is configured to convert the respective local lane data into respective global lane data dependent on respective GNSS data of the vehicle generated by the GNSS receiver when driving on the respective segment and to save the respective global lane data, and
the respective global lane data specifies the respective course of the lane on the respective segment in global coordinates.

2\. The driver-assistance system according to claim 1, wherein:
the driver-assistance system is configured to calculate respective further local lane data on the basis of the respective global lane data and on the basis of respective further GNS S data of the vehicle generated by the GNSS receiver when driving on the respective segment for a respective repeated time and to steer the vehicle dependent on the respective further local lane data such that the vehicle stays in the lane when driving on the respective segment the respective repeated time, and
the respective fuirther local lane data specifies the respective course of the lane on the respective segment relative to the vehicle.
3\. The driver-assistance system according to claim 2, wherein:
the driver-assistance system is configured to calculate respective second further local lane Page 26 of 29

data dependent on a respective further image of at least the respective segment generated by the camera when driving on the respective segment for the respective repeated time,the respective second further local lane data specifies the respective course of the lane on the respective segment relative to the vehicle, and
the driver-assistance system is configured to steer the vehicle dependent on the respective further local lane data and dependent on the respective second further local lane data such that the vehicle stays in the lane when driving on the respective segment the respective repeated time.

4\. The driver-assistance system according to claim 2, wherein:
the driver-assistance system is configured to perform a prediction of respective subsequent global lane data specifying the respective course of the lane on a respective subsequent segment in global coordinates dependent on the respective global lane data,
the respective subsequent segment follows the respective segment in a direction of travel of the vehicle,
the driver-assistance system is configured to calculate respective subsequent local lane data on the basis of the respective predicted subsequent global lane data and on the basis of respective subsequent further GNSS data of the vehicle generated by the GNSS receiver when driving on the respective subsequent segment for a respective repeated time and to steer the vehicle dependent on the respective subsequent local lane data such that the vehicle stays in the lane when driving on the respective subsequent segment the respective repeated time, and
the respective subsequent local lane data specifies the respective course of the lane on the respective subsequent segment relative to the vehicle.

5\. The driver-assistance system according to claim 4, wherein the driver-assistance system is configured to perform the prediction of respective subsequent global lane data using a Kalman-Filter.

6\. The driver-assistance system according to claim 1, wherein the local lane data specifies a respective course of at least one sideline of the lane on the respective segment.

7\. The driver-assistance system according to claim 6, wherein the local lane data comprises a first value indicating a distance between the sideline and the vehicle, a second value indicating a direction of the sideline relative to a longitudinal axis of the vehicle, a third value indicating a curvature of the sideline and a fourth value indicating a derivation of the curvature with respect to a direction that is parallel to the longitudinal axis of the vehicle.

8\. The driver-assistance system according to claim 1, wherein driver-assistance system is further configured to:
save the respective global lane data on an external computing device for providing the respective global lane data to a control unit of a further vehicle for steering the ffurther vehicle dependent on the respective global lane data and respective further GNSS data of the further vehicle generated by a GNSS receiver of the further vehicle when driving on the respective segment such that the further vehicle stays in the lane when driving on the respective segment.

9\. A method forkeeping a vehicle in a lane of a road when driving along segments of the road by a driver-assistance system, the driver-assistance system having a GNSS receiver, a camera and a control unit, the method comprising the following steps:generating a respective image of at least the respective segment by the camera;
calculating respective local lane data dependent on the respective image,
wherein the respective local lane data specifies a respective course of the lane on the respective segment relative to the vehicle;steering the vehicle dependent on the respective local lane data by the control unit such that the vehicle stays in the lane when driving on the respective segment;
converting the respective local lane data into respective global lane data dependent on respective GNSS data of the vehicle generated by the GNSS receiver when driving on the respective segment; and
saving the respective global lane data, wherein the respective global lane data specifies the respective course of the lane on the respective segment in global coordinates.

10\. The method according to claim 9 comprising the following further steps:
calculating respective further locallane data on the basis of the respective global lane data and dependent on respective further GNSS data of the vehicle generated by the GNSS receiver when driving on the respective segment for a respective repeated time, wherein the respective further locallane data specifies the respective course of the lane on the respective segment relative to the vehicle; and
steering the vehicle dependent on the respective further local lane data such that the vehicle stays in the lane when driving on the respective segment the respective repeated time.

OFFICE ACTION:
Notice of Pre-AIA  or AIA  Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Inventorship
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary.  Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-10 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Luo et al (WO 2023/129,648).
Luo et al teaches A driver-assistance system for keeping a vehicle in a lane of a road when driving along segments of the road, the driver-assistance system comprising: a GNSS receiver; a camera; and a control unit, wherein: the driver-assistance system is configured to calculate respective local lane data dependent on a respective image of at least the respective segment generated by the camera, the respective local lane data specifies a respective course of the lane on the respective segment relative to the vehicle, the control unit is configured to steer the vehicle dependent on the respective local lane data such that the vehicle stays in the lane when driving on the respective segment, the driver-assistance system is configured to convert the respective local lane data into respective global lane data dependent on respective GNSS data of the vehicle generated by the GNSS receiver when driving on the respective segment and to save the respective global lane data, and the respective global lane data specifies the respective course of the lane on the respective segment in global coordinates (See claims 75-96).
Conclusion


NEXT OFFICE ACTION: Notice of Pre-AIA  or AIA  Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments, see pages 6-7, filed April 23, 2025, with respect to claims 1-10 have been fully considered and are persuasive.
Claims 1-10 are allowed.
Conclusion

CITED REFERENCE SUMMARIES: Ref US20230009269A1: Claims:
A lane centering system for a vehicle, the lane centering system comprising: a light detection and ranging (LIDAR) system configured to (i) emit light pulses towards raised pavement markers on a road along which the vehicle is traveling and (ii) receive light pulses reflected by the raised pavement markers that collectively form LIDAR point cloud data; and a controller configured to: detect a set of lane lines defining one or more lanes on the road based on the LIDAR point cloud data; based on at least the detected set of lane lines, generate a polynomial curve corresponding to a center of a lane in which the vehicle is traveling; and control steering of the vehicle based on the polynomial curve to keep the vehicle centered within the lane.
a light detection and ranging (LIDAR) system configured to (i) emit light pulses towards raised pavement markers on a road along which the vehicle is traveling and (ii) receive light pulses reflected by the raised pavement markers that collectively form LIDAR point cloud data; and
a controller configured to: detect a set of lane lines defining one or more lanes on the road based on the LIDAR point cloud data; based on at least the detected set of lane lines, generate a polynomial curve corresponding to a center of a lane in which the vehicle is traveling; and control steering of the vehicle based on the polynomial curve to keep the vehicle centered within the lane.
detect a set of lane lines defining one or more lanes on the road based on the LIDAR point cloud data;
based on at least the detected set of lane lines, generate a polynomial curve corresponding to a center of a lane in which the vehicle is traveling; and
control steering of the vehicle based on the polynomial curve to keep the vehicle centered within the lane.
The lane centering system of claim 1 , wherein the controller is further configured to receive, from a set of e-horizon systems of the vehicle, e-horizon information including at least map-based data of a portion of the road in front of the vehicle.
The lane centering system of claim 2 , wherein the controller is further configured to: receive, from a camera system of the vehicle, lane information for the road based on an analysis by the camera system of images captured by the camera system; and receive, from the camera system, confidence scores for the lane information for the road.
receive, from a camera system of the vehicle, lane information for the road based on an analysis by the camera system of images captured by the camera system; and
receive, from the camera system, confidence scores for the lane information for the road.
The lane centering system of claim 3 , wherein when the lane information indicates no lane markers are present or the confidence scores for the lane information fail to satisfy a confidence score threshold, the controller is further configured to generate a blended polynomial curve based on a blending of the detected set of lane lines and the e-horizon information.
The lane centering system of claim 4 , wherein the controller is further configured to: control the steering of the vehicle based on the blended polynomial curve for a calibratable period to keep the vehicle centered within the lane; and output a notification to the driver that lane markings are unavailable and the driver will need to takeover steering of the vehicle after the calibratable period.
control the steering of the vehicle based on the blended polynomial curve for a calibratable period to keep the vehicle centered within the lane; and
output a notification to the driver that lane markings are unavailable and the driver will need to takeover steering of the vehicle after the calibratable period.
The lane centering system of claim 5 , wherein: when the driver takes over steering of the vehicle after the calibratable period, lane centering of the vehicle disengages; and when the driver does not take over steering of the vehicle after the calibratable period, the controller is further configured to perform a minimum risk maneuver (MRM) including (i) generating an MRM blended polynomial curve based on at least a blending of the detected set of lane lines and the e-horizon information and (ii) controlling steering of the vehicle based on the MRM polynomial curve to keep the vehicle safely centered within the lane or safely pulled over on a side of the road.
when the driver takes over steering of the vehicle after the calibratable period, lane centering of the vehicle disengages; and
when the driver does not take over steering of the vehicle after the calibratable period, the controller is further configured to perform a minimum risk maneuver (MRM) including (i) generating an MRM blended polynomial curve based on at least a blending of the detected set of lane lines and the e-horizon information and (ii) controlling steering of the vehicle based on the MRM polynomial curve to keep the vehicle safely centered within the lane or safely pulled over on a side of the road.
The lane centering system of claim 3 , wherein when the confidence scores for the lane information satisfy a confidence score threshold, the controller is configured to generate a blended polynomial curve based on a blending of the detected set of lane lines, the e-horizon information, and the lane information.
The lane centering system of claim 1 , wherein the controller is configured to generate the polynomial curve based further on vehicle state data including at least one of vehicle speed, pitch, and yaw.
A lane centering method for a vehicle, the method comprising: receiving, by a controller of the vehicle and from a light detection and ranging (LIDAR) system of the vehicle, LIDAR point cloud data, wherein the LIDAR system is configured to (i) emit light pulses towards raised pavement markers on a road along which the vehicle is traveling and (ii) receive light pulses reflected by the raised pavement markers that collectively form the LIDAR point cloud data; detecting, by the controller, a set of lane lines defining one or more lanes on the road based on the LIDAR point cloud data; based on at least the detected set of lane lines, generating, by the controller, a polynomial curve corresponding to a center of a lane in which the vehicle is traveling; and controlling, by the controller, steering of the vehicle based on the polynomial curve to keep the vehicle centered within the lane.
receiving, by a controller of the vehicle and from a light detection and ranging (LIDAR) system of the vehicle, LIDAR point cloud data, wherein the LIDAR system is configured to (i) emit light pulses towards raised pavement markers on a road along which the vehicle is traveling and (ii) receive light pulses reflected by the raised pavement markers that collectively form the LIDAR point cloud data;
detecting, by the controller, a set of lane lines defining one or more lanes on the road based on the LIDAR point cloud data;
based on at least the detected set of lane lines, generating, by the controller, a polynomial curve corresponding to a center of a lane in which the vehicle is traveling; and
controlling, by the controller, steering of the vehicle based on the polynomial curve to keep the vehicle centered within the lane.
The method of claim 9 , further comprising receiving, by the controller and from a set of e-horizon systems of the vehicle, e-horizon information including at least map-based data of a portion of the road in front of the vehicle.
The method of claim 10 , further comprising: receiving, by the controller and from a camera system of the vehicle, lane information for the road based on an analysis by the camera system of images captured by the camera system; and receiving, by the controller and from the camera system, confidence scores for he lane information for the road.
receiving, by the controller and from a camera system of the vehicle, lane information for the road based on an analysis by the camera system of images captured by the camera system; and
receiving, by the controller and from the camera system, confidence scores for he lane information for the road.
The method of claim 11 , wherein when the lane information indicates no lane markers are present or the confidence scores for the lane information fail to satisfy a confidence score threshold, the method further comprises generating, by the controller, a blended polynomial curve based on a blending of the detected set of lane lines and the e-horizon information.
The method of claim 12 , further comprising: controlling, by the controller, the steering of the vehicle based on the blended polynomial curve for a calibratable period to keep the vehicle centered within the lane; and outputting, by the controller, a notification to the driver that lane markings are unavailable and the driver will need to takeover steering of the vehicle after the calibratable period.
controlling, by the controller, the steering of the vehicle based on the blended polynomial curve for a calibratable period to keep the vehicle centered within the lane; and
outputting, by the controller, a notification to the driver that lane markings are unavailable and the driver will need to takeover steering of the vehicle after the calibratable period.
The method of claim 13 , wherein: when the driver takes over steering of the vehicle after the calibratable period, lane centering of the vehicle disengages; and when the driver does not take over steering of the vehicle after the calibratable period, the method further comprises performing, by the controller, a minimum risk maneuver (MRM) including (i) generating an MRM blended polynomial curve based on at least a blending of the detected set of lane lines and the e-horizon information and (ii) controlling steering of the vehicle based on the MRM polynomial curve to keep the vehicle safely centered within the lane or safely pulled over on a side of the road.
when the driver does not take over steering of the vehicle after the calibratable period, the method further comprises performing, by the controller, a minimum risk maneuver (MRM) including (i) generating an MRM blended polynomial curve based on at least a blending of the detected set of lane lines and the e-horizon information and (ii) controlling steering of the vehicle based on the MRM polynomial curve to keep the vehicle safely centered within the lane or safely pulled over on a side of the road.
The method of claim 11 , wherein when the confidence scores for the lane information satisfy a confidence score threshold, the method further comprises generating, by the controller, a blended polynomial curve based on a blending of the detected set of lane lines, the e-horizon information, and the lane information, and controlling, by the controller, the steering of the vehicle based on the blended polynomial curve to keep the vehicle centered within the lane.
The method of claim 9 , wherein generating, by the controller, the polynomial curve is based further on vehicle state data including at least one of vehicle speed, pitch, and yaw.
A lane centering system for a vehicle, the lane centering system comprising; a light detection and ranging (LIDAR) means for (i) emitting light pulses towards raised pavement markers on a road along which the vehicle is traveling and (ii) receiving light pulses reflected by the raised pavement markers that collectively form LIDAR point cloud data; and control means for: detecting a set of lane lines defining one or more lanes on the road based on the LIDAR point cloud data; based on at least the detected set of lane lines, generating a polynomial curve corresponding to a center of a lane in which the vehicle is traveling; and controlling steering of the vehicle based on the polynomial curve to keep the vehicle centered within the lane.
a light detection and ranging (LIDAR) means for (i) emitting light pulses towards raised pavement markers on a road along which the vehicle is traveling and (ii) receiving light pulses reflected by the raised pavement markers that collectively form LIDAR point cloud data; and
control means for: detecting a set of lane lines defining one or more lanes on the road based on the LIDAR point cloud data; based on at least the detected set of lane lines, generating a polynomial curve corresponding to a center of a lane in which the vehicle is traveling; and controlling steering of the vehicle based on the polynomial curve to keep the vehicle centered within the lane.
detecting a set of lane lines defining one or more lanes on the road based on the LIDAR point cloud data;
based on at least the detected set of lane lines, generating a polynomial curve corresponding to a center of a lane in which the vehicle is traveling; and
controlling steering of the vehicle based on the polynomial curve to keep the vehicle centered within the lane.
The lane centering system of claim 17 , wherein the control means receives, from a set of e-horizon means of the vehicle, e-horizon information including map-based data of a portion of the road in front of the vehicle.
The lane centering system of claim 18 , wherein the control means: receives, from a camera means of the vehicle, lane information for the road based on an analysis by the camera system of images captured by the camera means; and receives, from the camera means, confidence scores for the lane information for the road.
receives, from a camera means of the vehicle, lane information for the road based on an analysis by the camera system of images captured by the camera means; and
receives, from the camera means, confidence scores for the lane information for the road.
The lane centering system of claim 3 , wherein when the lane information indicates no lane markers are present or the confidence scores for the lane information fail to satisfy a confidence score threshold, the control means: generates a blended polynomial curve based on a blending of the detected set of lane lines and the e-horizon information; controls the steering of the vehicle based on the blended polynomial curve for a calibratable period to keep the vehicle centered within the lane; and outputs a notification to the driver that lane markings are unavailable and the driver will need to takeover steering of the vehicle after the calibratable period.
generates a blended polynomial curve based on a blending of the detected set of lane lines and the e-horizon information;
controls the steering of the vehicle based on the blended polynomial curve for a calibratable period to keep the vehicle centered within the lane; and
outputs a notification to the driver that lane markings are unavailable and the driver will need to takeover steering of the vehicle after the calibratable period.