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 action is responsive to the amendment and Applicant’s Interview Summary both filed on 02/06/2026:
Claims 1-20 have been examined.
Claims 1, 3, 6, 8, 10, 13-14, 16 and 19 have been amended by Applicant.
Legend: “Under BRI” = “under broadest reasonable interpretation;”
“[Prior Art/Analogous/Non-Analogous Art Reference] discloses through the invention” means “See/read entire document;” Paragraph [No..] = e.g., Para [0005] = paragraph 5; P = page, e.g., p4 = page 4; C = column, e.g. c3 = column 3;
L = line, e.g., l25 = line 25; l25-36 = lines 25 through 36.
Response to Applicant’s Interview Summary
1. Examiner respectfully disagrees with the Applicant’s Interview Summary filed on 02/06/2026 and kindly provides clarification to some misunderstanding/statements presented in the Applicant’s Interview Summary:
1.1 Applicant states in their Interview Summary that “… Examiner objected to the language "distribute/ing". However, discussion of "operating multiple instances of the auto-curation predictive computational models in a distributed computing environment" did not raise the same objection.”
The Examiner respectfully disagrees with this statement, and kindly presents that the discussion of "operating multiple instances of the auto-curation predictive computational models in a distributed computing environment" has never taken place during the Applicant-Initiated Interview held on 02/26/2026; the discussion of "operating multiple instances of the auto-curation predictive computational models in a distributed computing environment" has never been introduced or brought up as a topic for discussion in the Applicant’s Interview Agenda from 02/06/2026.
1.2 Applicant further states in their Interview Summary that “… Examiner argued that "when a computer gets involved as an additional element it becomes insignificant extra-solution activity" and that "improvement must be into something physical, such as a vehicle."”
The Examiner respectfully disagrees with these statements, and kindly presents, for clarification purposes, that the Examiner argued that "when a computer gets involved, it is considered as a well-understood, routine additional element that takes up a claimed well-understood, routine insignificant activity or abstract idea to a high level of generality, NOT that “it becomes insignificant extra-solution activity," as presented in the Applicant’s Interview Summary.
The Examiner further argued that "a practical application in the claim(s) must be into something physical, such as controlling, or operating, or navigating a vehicle,” NOT that "improvement must be into something physical, such as a vehicle," as presented in the Applicant’s Interview Summary.
1.3 Applicant further states in their Interview Summary that “[a]pplicant argued that technological improvements to software and systems represents a practical application providing patentable subject matter, but Examiner countered that where the improvement is in the computer it remains insignificant extra-solution activity.”
The Examiner respectfully disagrees with these statements, and kindly presents, for clarification purposes, that the Examiner argued back that "… where the improvement is in the computer it still remains as a well-understood, routine additional element that takes up a claimed well-understood, routine insignificant activity or abstract idea to a high level of generality,” NOT that “improvement in the computer remains insignificant extra-solution activity," as presented in the Applicant’s Interview Summary.
Response to Amendment
Claim Objections
1. Applicant’s amendments have overcome the claim 19 objections to from the previous Office Action.
2. Claim 14 objected to because of the following informalities: it is recommended to rewrite the first limitation/feature of claim 14 as the following: “… iteratively determining a set of map segments based on map data by :…,” for consistency with claims 1 and 8. Appropriate correction is required.
Claim Rejections - 35 USC § 112
1. Applicant’s amendments have partially overcome some of the 112(a) or 112, 1st paragraph rejections and the 112(b) or 112, 2nd paragraph rejections to claims 1-20 from the previous Office Action.
2. The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
2.1 Claims 1-20 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the enablement requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention.
2.1.1 Claims 1, 8 and 14, as currently amended, recite the limitation/feature “operate(ing) multiple instances of auto-curation predictive computational models across a distributed computing environment to update the map segments with auto-curated map data,” which is not described or supported in the specification in such a way as to enable one skilled in the art to make and/or use the invention. The specification, as originally filed or as published, provides support for the following: “… command module 230 may then adjust such segments to equalize auto-curation time, such as where the auto-curation predictive model will be implemented in multiple instances in a distributed computing environment,” in Para [0036, 0050], at least as published; “… instructions include instructions to receive map data; use an auto-curation predictive model to update the map data with auto-curated data; and use a manual-curation time predictive model to estimate a manual-curation time and generate a manual-curation heat map based on the map data,” in Para [0005], at least as published; “… command module 230 may use an auto-curation predictive model to update the map data with auto-curated data. For example, an auto-curative model trained to mimic human curation through a generative adversarial network or other approaches may be used to update the map data with auto-curated data,” in Para [0049], at least as published; “… obstacle map(s) 118 may be updated to reflect changes within a mapped area,” in Para [0059], at least as published, BUT, HOWEVER, the specification is silent about any “operate(ing) multiple instances of auto-curation predictive computational models across a distributed computing environment to update the map segments with auto-curated map data;” OR “updating the map segments.” Clarification is required.
Applicant is kindly requested to provide information on where exactly, in the specification, a support for the claimed “operate(ing) multiple instances of auto-curation predictive computational models across a distributed computing environment to update the map segments with auto-curated map data map data” can be found.
For the purpose of this examination, in view of the specification, and under BRI, the claimed “operate(ing) multiple instances of auto-curation predictive computational models across a distributed computing environment to update the map segments with auto-curated map data,” is not given a patentable weight, and hence, the Examiner will interpret this limitation/feature similar to how it was interpreted during previous examining, in view of the specification (Emphasis added), as “use an auto-curation predictive model to update the map data with auto-curated data,” per Para [0049] of the specification, at least as published.
2.1.2 Claims 2-7, 9-13 and 15-20 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), 1st paragraph, because of their dependencies on rejected independent claims, and for failing to cure the deficiencies listed above.
3. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
3.1 Claims 1-20 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
3.1.1 Claims 1, 8 and 14, as currently amended, recite the limitation/feature “operate(ing) multiple instances of auto-curation predictive computational models across a distributed computing environment to update the map segments with auto-curated map data,” which is unclear what it is, what they are, or how this is being performed/executed/made/performed, etc., which renders the claims indefinite. Clarification is required.
Additionally, this limitation/feature “operate(ing) multiple instances of auto-curation predictive computational models across a distributed computing environment to update the map segments with auto-curated map data” is not described or supported in the specification, which renders the claims indefinite. Clarification is required.
For the purpose of this examination, in view of the specification, and under BRI, the claimed “operate(ing) multiple instances of auto-curation predictive computational models across a distributed computing environment to update the map segments with auto-curated map data,” is not given a patentable weight, and hence, the Examiner will interpret this limitation/feature similar to how it was interpreted during previous examining, in view of the specification (Emphasis added), as “use an auto-curation predictive model to update the map data with auto-curated data,” per Para [0049] of the specification, at least as published.
3.1.2 Claims 2-7, 9-13 and 15-20 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, because of their dependencies on rejected independent claims, and for failing to cure the deficiencies listed above.
Claim Rejections – 35 USC § 101
1.1 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
1.1.1 Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
Claim 1 is directed to a system (i.e., machine, manufacture). Claim 8 is directed to a non-transitory computer-readable medium including instructions (i.e., machine, manufacture). Claim 14 is directed to a method (i.e., a process). Therefore, claims 1, 8 and 14 are within the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claim 14 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. Claim 14 recites:
14 (as currently amended) A method, comprising:
iteratively determining a set of map segments based on map data by:
(i) applying an auto-curation time predictive computational model comprising a neural network trained on auto-curation completion times for uncurated maps to obtain an auto-curation time estimate for each map segment;
(ii) adjusting boundaries of the map segments when any auto-curation time estimate does not satisfy a predefined optimization criterion; and
(iii) repeating steps (i) and (ii) until all auto-curation time estimates satisfy the predefined optimization criterion;
operating multiple instances of auto-curation predictive computational models across a distributed computing environment to update the map segments with auto-curated map data; and
assembling an auto-curated map based on the updated map segments.
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, “determining;” “applying … [model];” “adjusting;” “estimating…;” “satisfying criterion;” “operating … [model];” in the context of this claim, encompass a person (driver/operator/user/human, etc.) looking at data collected (from detectors, sensors) and forming simple observation, evaluation, judgment, decision, outcome, opinion. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
14 (as currently amended) A method, comprising:
iteratively determining a set of map segments based on map data by:
(i) applying an auto-curation time predictive computational model comprising a neural network trained on auto-curation completion times for uncurated maps to obtain an auto-curation time estimate for each map segment;
(ii) adjusting boundaries of the map segments when any auto-curation time estimate does not satisfy a predefined optimization criterion; and
(iii) repeating steps (i) and (ii) until all auto-curation time estimates satisfy the predefined optimization criterion;
operating multiple instances of auto-curation predictive computational models across a distributed computing environment to update the map segments with auto-curated map data; and
assembling an auto-curated map based on the updated map segments.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of “repeating steps;” “assembling map,” the examiner submits that these limitations are insignificant extra-solution activities that amount to mere pre solution repeating data receiving, data gathering and post-solution assembling map that merely use a computer (vehicle 100 that includes a map curation management system 170, computational model(s)) to perform the process; AND in particular, the generating map step is recited at a high level of generality (i.e. as a general means of informing/presenting about difference in data from updating, estimating steps), and amounts to mere post solution informing/presenting/mapping, which is a form of insignificant extra-solution activity. Lastly, the “vehicle 100 that includes a map curation management system 170” merely describes how to generally “apply” the otherwise mental judgements in a generic or general purpose vehicle control environment. The vehicle map curation management system is recited at a high level of generality (computational model(s)) and merely automates the updating, estimating steps.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the 2019 PEG, representative independent claim 14 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a “vehicle that includes a map curation management system” to perform the “applying model…;” “obtaining time estimates;” ”operating models;” “assembling map,” amounts to nothing more than applying the exception using a generic computer component. Generally applying an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of receiving data, generating a map, the examiner submits that these limitations are insignificant extra-solution activities.
Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The additional limitations of “receiving/gathering data,” “generating a map” are well-understood, routine, and conventional activities because the background recites that the sensors/detectors are all conventional sensors/detectors mounted on the vehicle, and the specification does not provide any indication that the vehicle 100 that includes a map curation management system 170 is anything other than a conventional computer within a vehicle. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner. The additional limitation of “generating a map” is a well-understood, routine, and conventional activity because the Federal Circuit in Trading Techs. Int’l v. IBG LLC, 921 F.3d 1084, 1093 (Fed. Cir. 2019), and Intellectual Ventures I LLC v. Erie Indemnity Co., 850 F.3d 1315, 1331 (Fed. Cir. 2017), for example, indicated that the mere presenting/showing/displaying of data is a well understood, routine, and conventional function. Hence, the claim is not patent eligible.
Dependent claims 2-7, 9-13 and 15-20 do not recite any further limitations that cause the claims to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application. It is unclear what the claimed limitations/features, in dependent claims 2-7, 9-13 and 15-20, are directed to in order to, or what or how they contribute/improve/influence/affect/innovate vehicle control, or operation, or use, or handling, or navigation, etc. Therefore, dependent claims 2-7, 9-13 and 15-20 are not patent eligible under the same rationale as provided for in the rejection of independent claims 1,8 and 14.
Therefore, claims 1-20 are ineligible under 35 USC §101.
1.1.2 Dependent claims 6, 13 and 19, however, if properly introduced, appear to recite further limitations that might cause the claims to be patent eligible. The Examiner finds that the limitations of dependent claims that are directed toward to “route instructions that cause the vehicle to autonomously implement the correction route,” if properly introduced, might appear to integrate the judicial exception into a practical application. Therefore, dependent claims 6, 13 and 19, if properly introduced, might appear to be patent eligible.
Allowable Subject Matter
1. Claims 1, 8 and 14 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), 1st paragraph, 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, and 35 U.S.C. 101 set forth in this Office action.
2. Claims 2-7, 9-13 and 15-20 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), 1st paragraph, 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, and 35 U.S.C. 101 set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
RELEVANT PRIOR ART THAT WAS CITED BUT NOT APPLIED
The following relevant prior art references that were found, by the Examiner while performing initial and/or additional search, cited but not applied:
MALEWICZ (US20190259082) – (see entire MALEWICZ document, particularly abstract – teaching searching or comparing sites; a real estate search-or-compare method based on commute durations; the method that efficiently processes public transportation and real estate property data to compute the durations of travel between the real estate properties and the vehicle stops; these durations stored; a request framework introduced that allows to express a wide range of search-or-compare requests; during request processing, the method that identifies parts of the commute paths that depend on any real estate property; because durations for these parts were precomputed and stored, the method that determines commute durations to every real estate property in a scalable manner; as a result, the method that rapidly responds to requests within the real estate market of one of the largest metropolitan areas in existence today; searching or comparing based on a monetary cost, transportation using private cars, and sites other than real estate properties).
Response to Arguments
1. In regards to the 112 rejections, Applicant’s arguments with respect to claims 1-20 have been considered but are moot in view of the new ground(s) of rejection.
2. In regards to the 101 rejections, Applicant's arguments filed 02/06/2026 have been fully considered but they are not persuasive. In response to the Applicant's argument, on pages 14-17 of 21, that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “a specific, non-conventional technological solution, utilizing a neural network trained on auto-curation completion times for uncurated maps to obtain auto-curation time estimates for uncurated map segments, to a documented technical problem in map curation: inefficient map curation workloads that hinder autonomous vehicle deployment;” “an improvement in a computer, a technology, or a technical field by managing map curation efficiently, and, more particularly, to managing curation workloads based on determinations of resource requirements for map curation, through the use of trained neural networks;” “improving map curation efficiency for autonomous vehicles through predictive computational models and distributed processing;” “concrete technological process for managing high definition map data derived from vehicle sensor probes which is essential for safe AV navigation) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
3. In response to the Applicant's argument, on pages 16-20 of 21, that “… argument presented in the Office Action clearly fails to meet this standard with respect to Step 2A, Prong 1 of the 2019 PEG, as it provides no explanation whatsoever of the meaningful technical limitations of applying an auto-curation time predictive computational model to obtain an auto-curation time estimate for each map segment (within an iterative framework); distributing the map segments to auto-curation predictive computational models operating in parallel to update the map segments with auto-curated map data; and assembling an auto-curated map based on the updated map segments;” that “[t]his is not merely a mental process performable in the human mind or on paper;” that “[a] human could not practically iterate over a vast amount of probe trace data (e.g., point clouds from multiple vehicles) at a scale required for real-world autonomous vehicle mapping, nor process map segments across multiple model instances in a distributed system,” BUT, HOWEVER, Applicant does not provide any evidence for an explanation about WHY OR HOW argument presented in the Office Action clearly fails to meet this standard with respect to Step 2A, Prong 1 of the 2019 PEG, as it provides no explanation whatsoever of the meaningful technical limitations of applying an auto-curation time predictive computational model to obtain an auto-curation time estimate for each map segment (within an iterative framework); distributing the map segments to auto-curation predictive computational models operating in parallel to update the map segments with auto-curated map data; and assembling an auto-curated map based on the updated map segments; OR WHY OR HOW this is not merely a mental process performable in the human mind or on paper; OR WHY OR HOW a human could not practically iterate over a vast amount of probe trace data (e.g., point clouds from multiple vehicles) at a scale required for real-world autonomous vehicle mapping, nor process map segments across multiple model instances in a distributed system.
The Examiner respectfully disagrees and kindly draws Applicant’s attention at pages 6-10 of the instant office action above, where it is discussed and presented, in details, that “the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation (Emphasis added), the claim covers performance of the limitation in the human mind. For example, “determining…;” “adjusting…;” “updating;” “estimating…;” “satisfying criterion,” in the context of this claim, encompass a person (driver/operator/user/human, etc.) looking at data collected (from detectors, sensors) and forming simple observation, evaluation, judgment, opinion. Accordingly, the claim recites at least one abstract idea;” and that “… it is unclear what the claimed limitations/features are directed to in order to, or what or how they contribute/improve/influence/affect/innovate vehicle control, or operation, or use, or handling, or navigation, etc.” Therefore, it is believed that the rejections should be maintained.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Primary Examiner YURI KAN, P.E., whose phone number is 571-270-3978. The examiner can normally be reached on Monday-Friday.
If attempts to reach the examiner by phone are unsuccessful, you may contact the examiner's supervisor, Mr. Jelani Smith, who can be reached on 571-270-3969. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/YURI KAN, P.E./ Primary Examiner, Art Unit 3662