Prosecution Insights
Last updated: July 17, 2026
Application No. 19/058,894

System for Generating Scene Context Data Using a Reference Graph

Non-Final OA §103
Filed
Feb 20, 2025
Priority
Jun 30, 2022 — continuation of 12/258,040
Examiner
RINK, RYAN J
Art Unit
3619
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Zoox Inc.
OA Round
1 (Non-Final)
78%
Grant Probability
Favorable
1-2
OA Rounds
1y 0m
Est. Remaining
89%
With Interview

Examiner Intelligence

Grants 78% — above average
78%
Career Allowance Rate
378 granted / 483 resolved
+26.3% vs TC avg
Moderate +11% lift
Without
With
+10.9%
Interview Lift
resolved cases with interview
Typical timeline
2y 5m
Avg Prosecution
14 currently pending
Career history
501
Total Applications
across all art units

Statute-Specific Performance

§101
2.0%
-38.0% vs TC avg
§103
74.7%
+34.7% vs TC avg
§102
5.2%
-34.8% vs TC avg
§112
12.5%
-27.5% vs TC avg
Black line = Tech Center average estimate • Based on career data from 483 resolved cases

Office Action

§103
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 . DETAILED ACTION This is a non-final Office Action on the merits. Claims 2-21 are currently pending and are addressed below. Information Disclosure Statement The information disclosure statement (IDS) submitted on 03/12/2025 is being considered by the examiner. Double Patenting The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13. The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer. Claims 2, 4-10, 12-21 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 12/258,040. Although the claims at issue are not identical, they are not patentably distinct from each other because the patented claims comprise substantially similar scope, comprising all pending claim limitations, thereby anticipating the pending claims. 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 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 of this title, 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. Claims 2, 3, 5, 6, 8-10, 11, and 13-21 are rejected under 35 U.S.C. 103 as being unpatentable over Murashkin et al. (US 2020/0377105) in view of Weng (US 2023/0394823). Regarding claim 2: Murashkin teaches one or more non-transitory computer-readable media storing instructions (memory 130) that, when executed, cause one or more processors to perform operations comprising: receiving sensor data associated with a physical environment, the physical environment comprising an object (see at least ¶0066); determining, based at least in part on a reference graph and the sensor data, current scene context data associated with the object (receiving sensor data, see at least ¶0036, Fig. 8 S802), wherein: the reference graph comprises a node associated with a feature vector (grid representing the area based on a set of feature vectors, see at least ¶0036, ¶0153-0175, Fig. 5, Fig. 8, S808), and the current scene context data is generated using a machine-learned model and the feature vector environment (velocity mask indicative of a velocity of object, set of dynamic objects in the environment see at least ¶0020, 0036, Fig. 8, S810, S812); determining, based at least in part on the current scene context data and the reference graph, future scene context data associated with the object (predicting future location and velocity of dynamic objects, see at least ¶0019, ¶0032-0036); associating the current scene context data and the future scene context data (context data, including current and future positions and velocities are associated with particular objects, and therefore with each other); and controlling an autonomous vehicle based at least in part on the future scene context data (determining control procedure, see at least ¶0020, 0036, Fig. 8, S816). Murashkin is silent as to using an attention-based machine learning model. Weng teaches a system and method of trajectory prediction for an autonomous vehicle, including utilizing a n attention-based machine learning model for predicting trajectory of objects in an environment (see at least ¶0061-0064). It would have been obvious to one of ordinary skill in the art before the time of filing of the invention to modify the system and method of controlling an autonomous vehicle based on a machine learning model predicting trajectories as taught by Murashkin with the technique of utilizing an attention-based machine learning model for predicting trajectories as taught by Weng in order to provide the expected result of an efficient model for trajectory prediction by focusing on relevant details over extraneous data. Regarding claim 3: Murashkin teaches the limitations as in claim 2 above. Weng further teaches wherein the object is the autonomous vehicle (see at least ¶0060). Regarding claim 5: Murashkin further teaches determining, based at least in part on the sensor data, state data associated with the object (occupancy mask, indicative of presence of object);; determining the current scene context data further based at least in part on the state data environment (velocity mask indicative of a velocity of object, set of dynamic objects in the environment see at least ¶0020, 0036, Fig. 8, S810, S812); determining, based at least in part on the current scene context data, future state data (predicting future location and velocity of dynamic objects, see at least ¶0019, ¶0032-0036); and determining the future scene context data based at least in part on the future state data and the reference graph (predicting future location and velocity of dynamic objects, see at least ¶0019, ¶0032-0036). Regarding claim 6: Murashkin further teaches wherein determining the future scene context data further comprises: determining, based at least in part on the current scene context data, a subset of the reference graph comprising two or more nodes of the reference graph (generating a tensor including a grid representing the area based on a set of feature vectors, see at least ¶0036, ¶0153-0175, Fig. 5, Fig. 8, S808, occupancy mask, indicative of presence of object); and determining the future scene context data based at least in part on feature vectors associated with individual ones of the two or more nodes (corrected tensor representation based on vehicle movement, see at least ¶0021-0025). Regarding claim 8: Murashkin further teaches wherein the two or more nodes represent a discrete portion of the physical environment (see at least Fig. 5). Regarding claim 9: Murashkin further teaches wherein determining the future scene context data further comprises: determining, based at least in part on the current scene context data and a route of the autonomous vehicle, a future position of the object relative to the physical environment (see at least ¶0033-0036); determining, based at least in part on the future position, a subset of the reference graph comprising two or more nodes of the reference graph (see at least ¶0033-0038); and determining the future scene context data based at least in part on an individual feature vector associated with individual ones of the two or more nodes (see at least ¶0033-0038). Regarding claims 10, 11, 13-21, the combination of Murashkin and Weng teaches a system and method as above. Allowable Subject Matter Claims 3, 7, 12, and 15 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Any inquiry concerning this communication or earlier communications from the examiner should be directed to RYAN J RINK whose telephone number is (571)272-4863. The examiner can normally be reached M-F 8-5. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Anna Momper can be reached on (571) 270-5788. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /Ryan Rink/ Primary Examiner, Art Unit 3619
Read full office action

Prosecution Timeline

Feb 20, 2025
Application Filed
Jun 23, 2026
Non-Final Rejection mailed — §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
78%
Grant Probability
89%
With Interview (+10.9%)
2y 5m (~1y 0m remaining)
Median Time to Grant
Low
PTA Risk
Based on 483 resolved cases by this examiner. Grant probability derived from career allowance rate.

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