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 Applicant’s Arguments/Remarks
Amendments and Remarks filed on 07/16/2026 have been fully considered and are addressed as follow:
Regarding the Claim Rejections Under 35 U.S.C. § 103: Applicants “Amendment and Remarks” have been fully considered. Applicant has amended the independent claim and these amendments have changed the scope of the original application and the Office has supplied new grounds for rejection attached below in the FINAL office action, and therefore the prior arguments are considered moot.
Claim Objections
Claim 1 is objected to because of the following informalities: “generating a road boundary estimation network to classify [[the]] sections of the roadway based on the road features and the lane groups”. The word “the” should be removed from before “sections of the roadway”. Appropriate correction is required.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-4, 8, 9, 10, 14, and 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over Rodrigues (US PGPub 2023/0221136) in view of Vladimerou (US PGPub 2015/0367778 A1).
With respect to claim 1: Rodrigues teaches a method comprising:
receiving satellite data and probe data of an autonomous vehicle traveling on a roadway [Rodrigues ¶ 0025 and Fig. 1 elements 110 and 120];
extracting road features from the satellite data [Rodrigues ¶ 0026, "space map pipeline unit 134 determines locations of roadways based on the spatial imagery"];
generating a road boundary estimation network to classify the sections of the roadway based on the road features and the lane groups [Rodrigues ¶ 0043, "lane network"]; and
based on the road boundary estimation network, generating a trajectory for the autonomous vehicle incorporating the classified road features and lane group [Rodrigues ¶ 0051 “The shapefiles are layered in order to determine vectors for traveling along a network of roadways. The shapefiles are usable in app such as navigation systems and autonomous driving for identifying directions of travel for vehicles.”];
autonomously controlling the autonomous vehicle in accordance with the generated trajectory [Rodrigues ¶ 0051].
Rodrigues does not teach determining lane transitions or creations in the roadway based on the probe data, wherein lane transitions or creations are detected based on a changing width of one or more affected lanes within a respective lane group; and wherein a section of the roadway is classified as a start or end of a lane transition or lane creation based on the changing width;
However, in a related field of invention, Vladimerou does teach determining lane transitions or creations in the roadway based on the probe data [Vladimerou ¶ 0029 “FIG. 2 illustrates further details of the lane detection procedure S104. At S200, images from the vehicle-mounted camera are processed to detect lane markers on the left and right sides of the vehicle.”], wherein lane transitions or creations are detected based on a changing width of one or more affected lanes within a respective lane group [Vladimerou ¶ 0002 “A lane width increase can be computed to detect a lane split or lane merge based on differences between the look-ahead and near lane widths.”]; and wherein a section of the roadway is classified as a start or end of a lane transition or lane creation based on the changing width [Vladimerou ¶ 0002 “A lane width increase can be computed to detect a lane split or lane merge based on differences between the look-ahead and near lane widths.” And Figures 5A-5D];
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine the roadmap generation system where a lane network is generated based on object and feature detection such as lane lines as taught by Rodrigues with determining lane transitions or creations based on a changing width as taught by Vladimerou in order to improve the accuracy and detail of the lane network.
With respect to claim 2: Rodrigues and Vladimerou teach the method of claim 1. Rodrigues further teaches wherein the road boundary estimation network is generated using a CNN network [Rodrigues ¶ 0056].
With respect to claim 3: Rodrigues and Vladimerou teach the method of claim 1. Rodrigues further teaches wherein generating the road boundary estimation network comprises featurizing the probe data [Rodrigues ¶ 0028].
With respect to claim 4: Rodrigues and Vladimerou teach the method of claim 1. Rodrigues further teaches wherein the probe data is featurized by extracting a plurality of road boundary key points from the probe data [Rodrigues ¶ 0028].
With respect to claim 8: Rodrigues and Vladimerou teach the method of claim 1. Rodrigues further teaches wherein each lane group comprises a left and right road boundary [Rodrigues ¶ 0098 and Fig. 9B element 930].
With respect to claim 9: Rodrigues teaches A vehicle control system, comprising:
One or more processors [Rodrigues ¶ 0099 and Fig. 10 element 1002]; and
a memory coupled to the one or more processors to store instructions, which when executed by the one or more processors, cause the one or more processors to [Rodrigues ¶ 0099 Fig. 10 element 1004]:
receive satellite data and probe data of an autonomous vehicle traveling on a roadway [Rodrigues ¶ 0025 and Fig. 1 elements 110 and 120];
extract road features from the satellite data [Rodrigues ¶ 0026, "space map pipeline unit 134 determines locations of roadways based on the spatial imagery"];
extract a plurality of road boundary key points from the probe data [Rodrigues ¶ 0028];
generate a road boundary estimation network to classify sections of the roadway based on the road features and the plurality of road boundary key points [Rodrigues ¶ 0043, "lane network"]; and
based on the road boundary estimation network, generating a trajectory for the autonomous vehicle incorporating the classified road features and lane groups; and [Rodrigues ¶ 0051 “The shapefiles are layered in order to determine vectors for traveling along a network of roadways. The shapefiles are usable in app such as navigation systems and autonomous driving for identifying directions of travel for vehicles.”];
autonomously controlling the autonomous vehicle in accordance with the generated trajectory [Rodrigues ¶ 0051].
Rodrigues does not teach determine lane transitions or creations for section of the roadway, wherein lane transitions or creations are detected based on a changing width of one or more affected lanes within a respective lane group, and further wherein a section of the roadway is classified as a start or end of a lane transition or lane creation based on the changing width.
However, in a related field of invention, Vladimerou does teach determine lane transitions or creations for section of the roadway, wherein lane transitions or creations are detected based on a changing width of one or more affected lanes within a respective lane group, and further wherein a section of the roadway is classified as a start or end of a lane transition or lane creation based on the changing width [Vladimerou ¶ 0002 “A lane width increase can be computed to detect a lane split or lane merge based on differences between the look-ahead and near lane widths.” And Figures 5A-5D].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine the roadmap generation system where a lane network is generated based on object and feature detection such as lane lines as taught by Rodrigues with determining lane transitions or creations based on a changing width as taught by Vladimerou in order to improve the accuracy and detail of the lane network.
With respect to claim 10: Rodrigues and Vladimerou teach the vehicle control system of claim 9. Rodrigues further teaches wherein the road boundary estimation network is generated using a CNN network [Rodrigues ¶ 0056].
With respect to claim 14: Rodrigues and Vladimerou teach the vehicle control system of claim 9. Rodrigues further teaches wherein each lane group comprises a left and right road boundary [Rodrigues ¶ 0098 and Fig. 9B element 930].
With respect to claim 21: Rodrigues and Vladimerou teach the method of claim 1. Vladimerou further teaches wherein a lane transition comprises a lane of the roadway narrowing until the lane merges with an adjacent lane, and wherein a lane creation comprises a lane of the roadway widening until an additional lane is created on the roadway [Vladimerou ¶ 0002 “A lane width increase can be computed to detect a lane split or lane merge based on differences between the look-ahead and near lane widths.” And Figures 5A-5D Lane split = lane creation and lane merge = lane transition].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine the roadmap generation system where a lane network is generated based on object and feature detection such as lane lines as taught by Rodrigues with determining lane transitions or creations based on a changing width as taught by Vladimerou in order to improve the accuracy and detail of the lane network.
With respect to claim 22: Rodrigues and Vladimerou teach the vehicle control system of claim 9. Vladimerou further teaches wherein a lane transition comprises a lane of the roadway narrowing until the lane merges with an adjacent lane, and wherein a lane creation comprises a lane of the roadway widening until an additional lane is created on the roadway [Vladimerou ¶ 0002 “A lane width increase can be computed to detect a lane split or lane merge based on differences between the look-ahead and near lane widths.” And Figures 5A-5D Lane split = lane creation and lane merge = lane transition].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine the roadmap generation system where a lane network is generated based on object and feature detection such as lane lines as taught by Rodrigues with determining lane transitions or creations based on a changing width as taught by Vladimerou in order to improve the accuracy and detail of the lane network.
Claim 5 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Rodrigues in view of Vladimerou and in further view of Chen (US PGPub 2016/0167582).
With respect to claim 5: Rodrigues and Vladimerou teach the method of claim 4. Rodrigues and Vladimerou do not teach wherein the plurality of road boundary key points generates a histogram indicating probabilities of lane boundaries across the plurality of road boundary key points.
However, in a related field of invention, Chen does teach wherein the plurality of road boundary key points generates a histogram indicating probabilities of lane boundaries across the plurality of road boundary key points [Chen ¶ 0052-0053].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine the roadmap generation system as taught by Rodrigues and Vladimerou with using a histogram indicating probabilities as taught in Chen in order to show the distribution of data and reveal patterns in the data which can correlate to road lanes [Chen ¶ 0052] and be used to create more accurate roadmaps.
With respect to claim 11: Rodrigues and Vladimerou teach the vehicle control system of claim 9. Rodrigues and Vladimerou do not teach wherein the plurality of road boundary key points generates a histogram indicating probabilities of lane boundaries across the plurality of road boundary key points.
However, in a related field of invention, Chen does teach wherein the plurality of road boundary key points generates a histogram indicating probabilities of lane boundaries across the plurality of road boundary key points [Chen ¶ 0052-0053].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine the roadmap generation system as taught by Rodrigues and Vladimerou with using a histogram indicating probabilities as taught in Chen in order to show the distribution of data and reveal patterns in the data which can correlate to road lanes [Chen ¶ 0052] and be used to create more accurate roadmaps.
Claims 6, 7, 12, 13, 15-17, 19, 20, and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Rodrigues in view of Vladimerou and in further view of Giurgiu (US PGPub 2020/0398856).
With respect to claim 6: Rodrigues and Vladimerou teach the method of claim 1. Rodrigues and Vladimerou do not teach wherein the satellite data and the probe data are discretized into lateral slices of the roadway.
However, in a related field of invention, Giurgiu does teach wherein the satellite data and the probe data are discretized into lateral slices of the roadway [Giurgiu ¶ 0056].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine the roadmap generation system as taught by Rodrigues and Vladimerou with discretized data into lateral slices as taught in Giurgiu in order to allow a system for mapping road lanes to process discrete, manageable chunks of data.
With respect to claim 7: Rodriguesm, Vladimerou, and Giurgiu teach the method of claim 6. Rodrigues and Vladimerou as modified by Giurgiu does not explicitly teach wherein each lateral slice comprises five meters of the roadway.
However, Rodrigues and Vladimerou as modified by Giurgiu at least suggests the idea of wherein each lateral slice comprises five meters of the roadway [Giurgiu ¶ 0056]. Further, the “mere scaling up” or “limitations relating to the size” or “recitation of relative dimensions” are generally not patentably distinguishable from a prior art device with both functioning in the same manner. See MPEP 2144.04 IV. It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to achieve such dimensions in order to process discrete and manageable chunks of data.
With respect to claim 12: Rodrigues and Vladimerou teach the vehicle control system of claim 9. Rodrigues and Vladimerou does not teach wherein the satellite data and the probe data are discretized into lateral slices of the roadway.
However, in a related field of invention, Giurgiu does teach wherein the satellite data and the probe data are discretized into lateral slices of the roadway [Giurgiu ¶ 0056].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine the roadmap generation system as taught by Rodrigues and Vladimerou with discretized data into lateral slices as taught in Giurgiu in order to allow a system for mapping road lanes to process discrete, manageable chunks of data.
With respect to claim 13: Rodrigues, Vladimerou, and Giurgiu teach the vehicle control system of claim 12. Rodrigues as modified by Giurgiu does not explicitly teach wherein each lateral slice comprises five meters of the roadway.
However, Rodrigues as modified by Vladimerou and Giurgiu at least suggests the idea of wherein each lateral slice comprises five meters of the roadway [Giurgiu ¶ 0056]. Further, the “mere scaling up” or “limitations relating to the size” or “recitation of relative dimensions” are generally not patentably distinguishable from a prior art device with both functioning in the same manner. See MPEP 2144.04 IV. It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to achieve such dimensions in order to process discrete and manageable chunks of data.
With respect to claim 15: Rodrigues teaches a non-transitory machine-readable medium having instructions stored therein, which when executed by one or more processors, cause the one or more processors to [Rodrigues ¶ 0099 and 0101 and Fig. 10 element 1004]:
receive satellite data and probe data of an autonomous vehicle traveling on a roadway [Rodrigues ¶ 0025 and Fig. 1 elements 110 and 120];
determine a plurality of road features for each lateral slice [Rodrigues ¶ 0026, "space map pipeline unit 134 determines locations of roadways based on the spatial imagery"];
generate a road boundary estimation network to classify the lateral slices based on the plurality of road features and the lane groups [Rodrigues ¶ 0043, "lane network"];
based on the road boundary estimation network, generating a trajectory for the autonomous vehicle incorporating the classified road features and lane groups; and [Rodrigues ¶ 0051 “The shapefiles are layered in order to determine vectors for traveling along a network of roadways. The shapefiles are usable in app such as navigation systems and autonomous driving for identifying directions of travel for vehicles.”];
autonomously controlling the autonomous vehicle in accordance with the generated trajectory [Rodrigues ¶ 0051].
Rodrigues does not teach determine lane transitions or creations in the roadway based on the probe data, wherein lane transitions or creations are detected based on a changing width of one or more affected lanes within a respective lane group and wherein a section of the roadway is classified as a start or end of a lane transition or lane creation based on the changing width.
However, in a related field of invention, Vladimerou does teach determine lane transitions or creations in the roadway based on the probe data, wherein lane transitions or creations are detected based on a changing width of one or more affected lanes within a respective lane group and wherein a section of the roadway is classified as a start or end of a lane transition or lane creation based on the changing width [Vladimerou ¶ 0002 “A lane width increase can be computed to detect a lane split or lane merge based on differences between the look-ahead and near lane widths.” And Figures 5A-5D].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine the roadmap generation system where a lane network is generated based on object and feature detection such as lane lines as taught by Rodrigues with determining lane transitions or creations based on a changing width as taught by Vladimerou in order to improve the accuracy and detail of the lane network.
Rodrigues and Vladimerou do not teach discretize the satellite data and the probe data into lateral slices of the roadway.
However, in a related field of invention, Giurgiu does teach discretize the satellite data and the probe data into lateral slices of the roadway [Giurgiu ¶ 0056];
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine the roadmap generation system as taught by Rodrigues and Vladimerou with discretized data into lateral slices as taught in Giurgiu in order to allow a system for generating roadmaps to process discrete, manageable chunks of data.
With respect to claim 16: Rodrigues, Vladimerou, and Giurgiu teach the non-transitory machine-readable medium of claim 15. Rodrigues further teaches wherein the road boundary estimation network is generated using a CNN network [Rodrigues ¶ 0056]. The motivation in the rejection for claim 15 applies here.
With respect to claim 17: Rodrigues, Vladimerou, and Giurgiu teach the non-transitory machine-readable medium of claim 15. Rodrigues further teaches wherein determining the plurality of road features comprises extracting a plurality of road boundary key points from the probe data [Rodrigues ¶ 0028]. The motivation in the rejection for claim 15 applies here.
With respect to claim 19: Rodrigues, Vladimerou, and Giurgiu teach the non-transitory machine-readable medium of claim 15. Rodrigues and Vladimerou as modified by Giurgiu does not explicitly teach wherein each lateral slice comprises five meters of the roadway.
However, Rodrigues and Vladimerou as modified by Giurgiu at least suggests the idea of wherein each lateral slice comprises five meters of the roadway [Giurgiu ¶ 0056]. Further, the “mere scaling up” or “limitations relating to the size” or “recitation of relative dimensions” are generally not patentably distinguishable from a prior art device with both functioning in the same manner. See MPEP 2144.04 IV. It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to achieve such dimensions in order to process discrete and manageable chunks of data.
With respect to claim 20: Rodrigues, Vladimerou, and Giurgiu teach the non-transitory machine-readable medium of claim 15. Rodrigues further teaches wherein each lane group comprises a left and right road boundary [Rodrigues ¶ 0098 and Fig. 9B element 930]. The motivation in the rejection for claim 15 applies here.
With respect to claim 23: Rodrigues, Vladimerou, and Giurgiu teach the non-transitory machine-readable medium of claim 15. Vladimerou further teaches wherein a lane transition comprises a lane of the roadway narrowing until the lane merges with an adjacent lane, and wherein a lane creation comprises a lane of the roadway widening until an additional lane is created on the roadway [Vladimerou ¶ 0002 “A lane width increase can be computed to detect a lane split or lane merge based on differences between the look-ahead and near lane widths.” And Figures 5A-5D Lane split = lane creation and lane merge = lane transition].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine the roadmap generation system where a lane network is generated based on object and feature detection such as lane lines as taught by Rodrigues with determining lane transitions or creations based on a changing width as taught by Vladimerou in order to improve the accuracy and detail of the lane network.
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Rodrigues in view of Vladimerou in view of Giurgiu and in further view of Chen.
With respect to claim 18: Rodrigues, Vladimerou, and Giurgiu teach the non-transitory machine-readable medium of claim 17. Rodrigues, Vladimerou, and Giurgiu do not teach wherein the plurality of road boundary key points generates a histogram indicating probabilities of lane boundaries across the plurality of road boundary key points.
However, in a related field of invention, Chen does teach wherein the plurality of road boundary key points generates a histogram indicating probabilities of lane boundaries across the plurality of road boundary key points [Chen ¶ 0052-0053].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to combine the roadmap generation system as taught by Rodrigues, Vladimerou, and Giurgiu with using a histogram indicating probabilities as taught in Chen in order to show the distribution of data and reveal patterns in the data which can correlate to road lanes [Chen ¶ 0052] and be used to create more accurate roadmaps.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/J.E.R./Examiner, Art Unit 3666
/SCOTT A BROWNE/Supervisory Patent Examiner, Art Unit 3666
