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 .
Claim Objections
Claim 21 is object being dependent on rejected independent claim 1.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claim(s) 1-18, 20-21 are rejected under 35 U.S.C. 103 as being unpatentable over Yang et al (2018/0189578) and further in view of Shashua et al 2017/0336793).
2. As per claims 1,11, Yang disclosed a system comprising:
one or more processors; and
a memory storing instructions that, when executed by the one or more processors, cause the system to perform [The instructions 4424 (e.g., software) may also reside, completely or at least partially, within the main memory 4404 or within the processor 4402 (e.g., within a processor's cache memory) during execution thereof by the computer system 4400, the main memory 4404 and the processor 4402 also constituting machine-readable media. The instructions 4424 (e.g., software) may be transmitted or received over a network 4426 via the network interface device 4420] (Paragraph 0229):
obtaining data from a plurality of sources, wherein the plurality of sources comprise any of low resolution map data, historical data of an ego-vehicle position, and landmark data [Embodiments generate HD maps containing spatial geometric information about the roads on which an autonomous vehicle can travel. Accordingly, the generated HD maps include the information necessary for an autonomous vehicle navigating safely without human intervention. Instead of collecting data for the HD maps using an expensive and time consuming mapping fleet process including vehicles outfitted with high resolution sensors, embodiments of the invention use data from the lower resolution sensors of the self-driving vehicles themselves as they drive around through their environments] (Paragraph .0054);
generating one or more candidate segments indicative of potential lane boundaries, the candidate segments comprising any of a first candidate segment generated from the low resolution map data, a second candidate segment generated from the historical data of the ego-vehicle position, and a third candidate segment generated from the landmark data; validating the generated one or more candidate segments [An autonomous vehicle is a vehicle capable of sensing its environment and navigating without human input. Autonomous vehicles may also be referred to herein as “driverless car,” “self-driving car,” or “robotic car.” An HD map refers to a map storing data with very high precision, typically 5-10 cm. Embodiments generate HD maps containing spatial geometric information about the roads on which an autonomous vehicle can travel. Accordingly, the generated HD maps include the information necessary for an autonomous vehicle navigating safely without human intervention. Instead of collecting data for the HD maps using an expensive and time consuming mapping fleet process including vehicles outfitted with high resolution sensors, embodiments of the invention use data from the lower resolution sensors of the self-driving vehicles themselves as they drive around through their environments.] (Paragraph. 0054);
aligning the validated and generated one or more candidate segments [The precise coordinates of the sign are needed so an autonomous vehicle (AV) may accurately predict where the sign will be located in its sensor data so that it can validate the map's prediction of the world, detect changes to the world and locate itself with respect to the map] (Paragraph. 0106);
wherein the segment is used to compute a navigation path for the ego-vehicle to operate the ego-vehicle within the lane boundary defined by the segment [ In one embodiment, lane cuts are automatically generated. When lane cuts are automatically generated, lane cuts are not derived from raw image pixels or lidar points (e.g., lane boundaries and navigable boundaries may be derived from these features), but from lower level features such as lane lines and navigable boundaries. Having feature vectors instead of higher level features as input greatly reduces the complexity of detecting changes in road topology. However, the quality of input features has a greater impact on the quality of detected lane cuts as opposed to other automation tasks (e.g., lane lines, traffic signs that use raw image pixels or lidar points). If input lane line features are not well aligned to the road, have missing segments] (Paragraph. 0216).
However, Yang did not explicitly disclose constructing a segment by stitching together the aligned, validated, and generated candidate segments, wherein constructing the segment comprises shifting the first candidate segment or the third candidate segment with respect to the second candidate segment is overlapping with the second candidate segment and a second section of the first candidate segment or the third candidate segment is nonoverlapping with respect to the second candidate segment, the segment defining a lane boundary.
In the same field of endeavor Shashua disclosed, “determine at least a first autonomous navigational response for the vehicle based on analysis of the first navigational map, when the current location of the vehicle lies on the first navigational map; receive a second navigational map associated with a second road segment different from the second road segment, the first road segment and the second road segment overlapping one another at an overlap segment; determine at least a second autonomous navigational response for the vehicle based on analysis of the second navigational map when the current location of the vehicle lies on the second navigational map; and determine at least a third autonomous navigational response for the vehicle based on at least one of the first navigational map and the second navigational map when the current location of the vehicle lies in the overlap segment (Paragraph. 0054) and The vehicle path may be represented using a set of points expressed in coordinates (x, z), and the distance d.sub.i between two points in the set of points may fall in the range of 1 to 5 meters. In one embodiment, processing unit 110 may construct the initial vehicle path using two polynomials, such as left and right road polynomials. Processing unit 110 may calculate the geometric midpoint between the two polynomials and offset each point included in the resultant vehicle path by a predetermined offset (e.g., a smart lane offset), if any (an offset of zero may correspond to travel in the middle of a lane). The offset may be in a direction perpendicular to a segment between any two points in the vehicle path. In, another embodiment, processing unit 110 may use one polynomial and an estimated lane width to offset each point of the vehicle path by half the estimated lane width plus a predetermined offset (e.g., a smart lane offset) (Paragraph. 0347).
It would have been obvious to one having ordinary skill in the art before the effective filing date was made to have incorporated determine at least a first autonomous navigational response for the vehicle based on analysis of the first navigational map, when the current location of the vehicle lies on the first navigational map; receive a second navigational map associated with a second road segment different from the second road segment, the first road segment and the second road segment overlapping one another at an overlap segment; determine at least a second autonomous navigational response for the vehicle based on analysis of the second navigational map when the current location of the vehicle lies on the second navigational map; and determine at least a third autonomous navigational response for the vehicle based on at least one of the first navigational map and the second navigational map when the current location of the vehicle lies in the overlap segment and The vehicle path may be represented using a set of points expressed in coordinates (x, z), and the distance d.sub.i between two points in the set of points may fall in the range of 1 to 5 meters. In one embodiment, processing unit 110 may construct the initial vehicle path using two polynomials, such as left and right road polynomials. Processing unit 110 may calculate the geometric midpoint between the two polynomials and offset each point included in the resultant vehicle path by a predetermined offset (e.g., a smart lane offset), if any (an offset of zero may correspond to travel in the middle of a lane). The offset may be in a direction perpendicular to a segment between any two points in the vehicle path. In, another embodiment, processing unit 110 may use one polynomial and an estimated lane width to offset each point of the vehicle path by half the estimated lane width plus a predetermined offset (e.g., a smart lane offset) as taught by Shashua in the method and system of Yang to increase the efficiency of the precision mapping of the lanes.
3. As per claims 2,12 Yang-Shashua disclosed wherein the validating of the generated one or more candidate segments comprises filtering out or removing any first candidate segment in which a radius of curvature (Shashua, Paragraph. 0469), occurring anywhere within the first candidate segment, is lower than a first threshold radius of curvature (Shashua, Paragraph. 0335). Claims 2 and 12 has the same motivation to claim 1.
4. As per claims 3,13 Yang-Shashua disclosed wherein the generating of the one or more candidate segments comprises defining the generated one or more candidate segments in terms of a relationship between a longitudinal position and a latitudinal position (Shashua, Paragraph. 0381). Claims 3 and 13 have the same motivation as to claim 1.
5. As per claims 4,14 Yang-Shashua disclosed wherein the validating of the generated one or more candidate segments comprises determining any first candidate segment that has a concave down portion and a concave up portion, in which radii of curvature within both the concave down portion and the concave up portion are less than a second threshold radius of curvature (Shashua, Paragraph. 0353); and filtering out or removing the concave down portion and the concave up portion (Shashua, Paragraph. 0778). Claims 4 and 14 have the same motivation as to claim 1.
6. As per claims 5,15 Yang-Shashua disclosed wherein the generating of the one or more candidate segments comprises: logging, within a log, one or more entries corresponding to historical positions traversed by the ego-vehicle, the historical positions defined according to a latitude and a longitude; and generating the second candidate segment based on the logged one or more entries (Yang, Paragraph. 0173).
7. As per claims 6,16 Yang-Shashua disclosed wherein the generating of the one or more candidate segment further comprises selectively removing an entry in the log based on a timestamp corresponding to the entry or based on an amount of change in a position compared to a preceding entry (Yang, Paragraph. 0080).
8. As per claims 7,17 Yang-Shashua disclosed wherein the validating of the generated one or more candidate segments comprises validating the first candidate segment and the second candidate segment against each other based on lateral distances between corresponding pairs of points of the first candidate segment and the second candidate segment (Yang, Paragraph. 0353).
9. As per claims 8,18 Yang-Shashua disclosed wherein the validating of the generated one or more candidate segments comprises validating the third candidate segment based on a quality of the third candidate segment, the quality being determined based on a length, a degree of smoothness and a frequency of oscillations of the third candidate segment (Shashua, Paragraph. 0054). Claims 8 and 18 have the same motivation as to claim 1.
10. As per claim 9 Yang-Shashua disclosed wherein the constructing of the segment comprises constructing portions of the segment based on a highest ranked validated candidate segment that is available within each of the portions (Shashua, Paragraph. 0324), the highest ranked validated candidate segment being selected from the validated first candidate segment, the validated second candidate segment, and the validated third candidate segment (Shashua, Paragraph. 0885). Claim 9 has the same motivation as to claim 1.
11. As per claims 10,20 Yang-Shashua disclosed wherein the instructions further cause the one or more processors to perform computing a navigation path for the ego vehicle based on a restriction of the ego- vehicle operating within boundaries defined by the constructed segment and actuating the ego- vehicle based on the navigation path (Yang, Paragraph. 0186 & 216).
Response to Arguments
12. Applicant's arguments filed 02/13/2026 have been fully considered but they are not persuasive. Response to applicant’s argument as follows.
Applicant argued that prior art did not disclose, “constructing a segment by stitching together the aligned, validated, and generated candidate segments, wherein constructing the segment comprises shifting the first candidate segment or the third candidate segment with respect to the second candidate segment is overlapping with the second candidate segment and a second section of the first candidate segment or the third candidate segment is nonoverlapping with respect to the second candidate segment, the segment defining a lane bound
As to applicant’s argument Shashua disclosed, “determine at least a first autonomous navigational response for the vehicle based on analysis of the first navigational map, when the current location of the vehicle lies on the first navigational map; receive a second navigational map associated with a second road segment different from the second road segment, the first road segment and the second road segment overlapping one another at an overlap segment; determine at least a second autonomous navigational response for the vehicle based on analysis of the second navigational map when the current location of the vehicle lies on the second navigational map; and determine at least a third autonomous navigational response for the vehicle based on at least one of the first navigational map and the second navigational map when the current location of the vehicle lies in the overlap segment (Paragraph. 0054) and The vehicle path may be represented using a set of points expressed in coordinates (x, z), and the distance d.sub.i between two points in the set of points may fall in the range of 1 to 5 meters. In one embodiment, processing unit 110 may construct the initial vehicle path using two polynomials, such as left and right road polynomials. Processing unit 110 may calculate the geometric midpoint between the two polynomials and offset each point included in the resultant vehicle path by a predetermined offset (e.g., a smart lane offset), if any (an offset of zero may correspond to travel in the middle of a lane). The offset may be in a direction perpendicular to a segment between any two points in the vehicle path. In, another embodiment, processing unit 110 may use one polynomial and an estimated lane width to offset each point of the vehicle path by half the estimated lane width plus a predetermined offset (e.g., a smart lane offset) (Paragraph. 0347)
Conclusion
13. 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.
14. Any inquiry concerning this communication or earlier communication from the
examiner should be directed to Adnan Mirza whose telephone number is (571)-272-3885.
15. The examiner can normally be reached on Monday to Friday during normal
business hours. If attempts to reach the examiner by telephone are unsuccessful, the
examiner’s supervisor, Faris Almatrahi can be reached on (313)-446-4821.
16. Information regarding the status of an application may be obtained from the
Patent Application Information Retrieval (PAIR) system. Status information for published
applications may be obtained from either Private PAIR or Public PAIR. Status
information for un published applications is available through Private PAIR only. For
more information about the PAIR system, see http://pair-direct.uspto.gov. Should you
have questions on access to the Private PAIR system, contact the Electronic Business
Center (EBC) at (866)-217-9197 (toll-free).
/ADNAN M MIRZA/Primary Examiner, Art Unit 3667