Prosecution Insights
Last updated: April 19, 2026
Application No. 17/445,036

METHOD, APPARATUS, AND COMPUTER PROGRAM PRODUCT FOR PREDICTING ELECTRIC VEHICLE CHARGE POINT UTILIZATION

Final Rejection §101
Filed
Aug 13, 2021
Examiner
HERNANDEZ, MANUEL J
Art Unit
2859
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Here Global B V
OA Round
7 (Final)
51%
Grant Probability
Moderate
8-9
OA Rounds
3y 8m
To Grant
96%
With Interview

Examiner Intelligence

Grants 51% of resolved cases
51%
Career Allow Rate
335 granted / 658 resolved
-17.1% vs TC avg
Strong +45% interview lift
Without
With
+45.4%
Interview Lift
resolved cases with interview
Typical timeline
3y 8m
Avg Prosecution
76 currently pending
Career history
734
Total Applications
across all art units

Statute-Specific Performance

§101
4.0%
-36.0% vs TC avg
§103
54.1%
+14.1% vs TC avg
§102
23.7%
-16.3% vs TC avg
§112
17.0%
-23.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 658 resolved cases

Office Action

§101
DETAILED 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 filed 10/23/2025 have been fully considered but they are not persuasive. In response to arguments on pages 10-11 regarding the internal memorandum on August 4, 2025, it is respectfully submitted that the claims do not “encompass AI in a way that cannot be practically performed in the human mind”, as the claims do not include any recitations that could be interpreted as artificial intelligence. The recited “machine learning model” is disclosed in paragraph 0064 of the specification as originally filed, and is interpreted as a mathematical function. Therefore, since independent claims 1, 9, and 17 recite mathematical calculations, the discussion in example 39 would not apply. In response to arguments on pages 11-14 regarding the PTAB decision for application 16/664,452, it is respectfully submitted that the instant claims are materially different from those in application 16/664,452, and more closely resemble claim 1 of US Patent 11,386,367 discussed in the CAFC decision for case 2023-2437 (“RECENTIVE ANALYTICS, INC. v. FOX CORP”) (see pages 3-4). In response to arguments that the machine learning model is trained on a “large amount of data” that cannot be performed practically in the human mind or with the use of pen and paper, please see page 15 of the CAFC decision, which states as follows: Whether the issue is raised at step one or step two, the increased speed and efficiency resulting from use of computers (with no improved computer techniques) do not themselves create eligibility. See, e.g., Trinity Info Media, LLC v. Covalent, Inc., 72 F.4th 1355, 1363 (Fed. Cir. 2023) (rejecting argument that “humans could not mentally engage in the ‘same claimed process’ because they could not perform ‘nanosecond comparisons’ and aggregate ‘result values with huge numbers of polls and members’”) Therefore, even if the claims are interpreted as utilizing a “large amount of data”, this is not sufficient to create eligibility. It is maintained that the claims are ineligible under 35 USC 101. Claim Objections Claims 1 and 23 are objected to because of the following informalities: In claim 1, line 10, “the road segments or links” should be changed to --road segments or links--. In claim 23, line 1, “the road segment” should be changed to --the road segment data--. Appropriate correction is required. Claim Rejections - 35 USC § 101 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. Claims 1-7, 9-15, 17, and 21-25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without reciting additional elements that integrate the judicial exception into a practical application. Moreover, the claims do not appear to recite additional elements that amount to significantly more than the judicial exception. Claim 1 recites determining a predicted utilization of an EV charge point at a candidate location and recommended charge point attributes, and thus recites an abstract idea. The recited steps which “receive”, “identify”, “determine”, and “train” are directed to mental choices or evaluations and mathematical calculations that are part of the abstract idea. It is noted that the “machine learning model” is not described in the claims, and may be interpreted as encompassing mathematical calculations. The claim does not recite a practical application or use of the “predicted utilization” or the “recommended charge point attributes”. The additional elements include a processor, a memory, generating a representation of a map for display on a user interface, and providing for visual distinction of the plurality of candidate locations. The additional elements of a processor and a memory are merely generic components (e.g., recited at a high level of generality) which are not considered a practical application, but are used to perform the mental process. The additional elements of generating a representation of a map for display on a user interface and providing for visual distinction of the plurality of candidate locations amount to the displaying of information, which is well-known and is considered insignificant extra-solution activity. Thus, the claim as a whole does not recite any additional elements which integrate the recited judicial exception into a practical application. Finally, the claim does not include additional elements that are significantly more than the judicial exception, as the additional elements of a processor and a memory are merely generic components (e.g., recited at a high level of generality); and the additional elements of generating a representation of a map for display on a user interface and providing for visual distinction of the plurality of candidate locations are well-known and are considered insignificant extra-solution activity, and are not significantly more. Claims 2-7 and 21-25 do not appear to make the claims eligible for reasons similar to those noted above and are therefore also rejected under 35 USC 101. It is noted that the steps of claim 25 can be considered insignificant extra-solution activity, and are therefore not a practical application or significantly more. Claim 9 recites determining a predicted utilization of an EV charge point at a candidate location and recommended charge point attributes, and thus recites an abstract idea. The recited steps which “receive”, “determine”, and “process” are directed to mental choices or evaluations and mathematical calculations that are part of the abstract idea. It is noted that the “machine learning model” is not described in the claims, and may be interpreted as encompassing mathematical calculations. The claim does not recite a practical application or use of the “predicted utilization” or the “recommended charge point attributes”. The additional elements include a storage medium, generating a representation of a map for display on a user interface, and providing for visual distinction of the plurality of candidate locations. The additional element of a storage medium is merely a generic component (e.g., recited at a high level of generality) which is not considered a practical application, but is used to perform the mental process. The additional elements of generating a representation of a map for display on a user interface and providing for visual distinction of the plurality of candidate locations amount to the displaying of information, which is well-known and is considered insignificant extra-solution activity. Thus, the claim as a whole does not recite any additional elements which integrate the recited judicial exception into a practical application. Finally, the claim does not include additional elements that are significantly more than the judicial exception, as the additional element of a storage medium is merely a generic component (e.g., recited at a high level of generality); and the additional elements of generating a representation of a map for display on a user interface and providing for visual distinction of the plurality of candidate locations are well-known and are considered insignificant extra-solution activity, and are not significantly more. Claims 10-15 do not appear to make the claims eligible for reasons similar to those noted above and are therefore also rejected under 35 USC 101. Claim 17 recites a method configured to generate a representation of a map including a plurality of candidate locations based on a predicted utilization of an EV charge point at the plurality of candidate locations, and thus recites an abstract idea. The recited steps of “receiving”, “determining”, “processing”, and “generating” are directed to mental choices or evaluations and mathematical calculations that are part of the abstract idea. It is noted that the “machine learning model” is not described in the claims, and may be interpreted as encompassing mathematical calculations. The claim does not recite a practical application or use of the “predicted utilization” or the “recommended charge point attributes”. The additional elements of generating a representation of a map for display on a user interface and providing for visual distinction of the plurality of candidate locations amount to the displaying of information, which is well-known and is considered insignificant extra-solution activity. Thus, the claim as a whole does not recite any additional elements which integrate the recited judicial exception into a practical application. Finally, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception, as the additional elements of generating a representation of a map for display on a user interface and providing for visual distinction of the plurality of candidate locations are well-known and are considered insignificant extra-solution activity, and are not significantly more. Allowable Subject Matter Claims 1-7, 9-15, 17, and 21-25 are allowed (subject to 101 rejection). The following is a statement of reasons for the indication of allowable subject matter: Regarding claim 1, the prior art teaches an apparatus as described in the office action with mail date 6/17/2024 but fails to disclose causing the apparatus to “receive probe data which includes historical locations and charge levels for electric vehicles proximate the locations of the existing EV charge points” and “train a machine learning model on the static map features, the probe data, and the charge point attributes for the locations of the existing EV charge points and the utilization of the existing EV charge points; receive a candidate location, probe data associated with the candidate location, and static map features associated with the candidate location; determine, based on the machine learning model using the candidate location, the probe data associated with the candidate location, and the static map features associated with the candidate location, a predicted utilization of an EV charge point at the candidate location and recommended charge point attributes”. It would not have been obvious to modify the prior art to arrive at the claimed invention. Claims 2-7 and 21-25 are dependent from claim 1 and are therefore allowable for the same reasons as independent claim 1. Regarding claim 9, the prior art teaches a computer program product as described in the office action with mail date 6/17/2024 but fails to disclose program code instructions configured to “receive probe data associated with the candidate location which includes historical locations and charge levels for electric vehicles proximate the candidate location; process the candidate location, the probe data associated with the candidate location, and static map features of the candidate location using a machine learning model”. It would not have been obvious to modify the prior art to arrive at the claimed invention. Claims 10-15 are dependent from claim 9 and are therefore allowable for the same reasons as independent claim 9. Regarding claim 17, the prior art teaches a method as described in the office action with mail date 6/17/2024 but fails to disclose the method comprises “receiving probe data associated with the plurality of candidate locations which includes historical locations and charge levels for electric vehicles proximate the plurality of candidate locations; processing the plurality of candidate locations, the probe data associated with the plurality of candidate locations, and the static map features using a machine learning model”. It would not have been obvious to modify the prior art to arrive at the claimed invention. Furthermore, none of the prior art of record, taken alone or in combination, teaches or suggests these claim features. 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. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MANUEL HERNANDEZ whose telephone number is (571)270-7916. The examiner can normally be reached Monday-Friday 9a-5p ET. 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, Taelor Kim can be reached at (571) 270-7166. 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. /Manuel Hernandez/Examiner, Art Unit 2859 3/2/2026 /TAELOR KIM/Supervisory Patent Examiner, Art Unit 2859
Read full office action

Prosecution Timeline

Aug 13, 2021
Application Filed
Jun 12, 2023
Non-Final Rejection — §101
Aug 29, 2023
Response Filed
Nov 24, 2023
Non-Final Rejection — §101
Feb 27, 2024
Response Filed
Jun 05, 2024
Final Rejection — §101
Aug 29, 2024
Response after Non-Final Action
Sep 23, 2024
Response after Non-Final Action
Sep 30, 2024
Request for Continued Examination
Oct 08, 2024
Response after Non-Final Action
Oct 23, 2024
Non-Final Rejection — §101
Jan 28, 2025
Response Filed
Feb 18, 2025
Final Rejection — §101
Mar 18, 2025
Interview Requested
Mar 24, 2025
Examiner Interview Summary
Mar 24, 2025
Applicant Interview (Telephonic)
Apr 25, 2025
Response after Non-Final Action
Jun 24, 2025
Request for Continued Examination
Jun 25, 2025
Response after Non-Final Action
Jul 29, 2025
Non-Final Rejection — §101
Oct 23, 2025
Response Filed
Feb 25, 2026
Final Rejection — §101 (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

8-9
Expected OA Rounds
51%
Grant Probability
96%
With Interview (+45.4%)
3y 8m
Median Time to Grant
High
PTA Risk
Based on 658 resolved cases by this examiner. Grant probability derived from career allow rate.

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