Prosecution Insights
Last updated: August 18, 2026
Application No. 18/387,350

Vehicle Data Managing Server, Platform Managing Server and Service Server, and Service Providing System Associated with Autonomous Driving Platform

Final Rejection §103
Filed
Nov 06, 2023
Priority
Jan 10, 2023 — RE 10-2023-0003684 +2 more
Examiner
KHATIB, RAMI
Art Unit
3669
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
LG Energy Solution Ltd.
OA Round
4 (Final)
77%
Grant Probability
Favorable
5-6
OA Rounds
1m
Est. Remaining
91%
With Interview

Examiner Intelligence

Grants 77% — above average
77%
Career Allowance Rate
682 granted / 884 resolved
+25.1% vs TC avg
Moderate +14% lift
Without
With
+13.8%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
36 currently pending
Career history
915
Total Applications
across all art units

Statute-Specific Performance

§101
15.2%
-24.8% vs TC avg
§103
38.0%
-2.0% vs TC avg
§102
19.8%
-20.2% vs TC avg
§112
24.7%
-15.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 884 resolved cases

Office Action

§103
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 . This office action is in response to applicant’s arguments/remarks and amendments filed on 07/16/2026. Claims 1, 3, 5, 10, 12, and 14 have been amended. No Claims have been cancelled. No Claims have been newly added. Accordingly, claims 1-18 are currently pending. Response to Arguments Applicant’s arguments, see applicant’s arguments/remarks, filed on 07/16/2026, with respect to the rejection(s) of claim(s) 1-3, 5-12, and 14-18 under 35 U.S.C. 103 as being obvious over You and Haga have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of You and Nishida US 2021/0286920 A1 provided in IDS filed on 11/06/2023, (hence Nishida). 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. This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention. Claim(s) 1-3, 5-6, 8-12, 14-15, and 17-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over You US 2023/0303091 A1 (hence You) in view of Nishida US 2021/0286920 A1 (hence Nishida). In re claims 1 and 10, You discloses techniques for controlling electric vehicles (Abstract) and teaches the following: a platform managing server having stored thereon autonomous driving software that is configured to operate an autonomous driving simulation in a generated virtual environment, wherein the autonomous driving simulation simulates autonomous driving of a vehicle (Fig.1, #105, #116, #120-#124 and Paragraphs 0031, 0034 “the processing platform 105 can comprise multiple networked processing devices, such as a plurality of servers”, and 0035); a vehicle data managing server separate from the platform managing server and configured to: acquire vehicle data including driving data related to driving of the vehicle and battery data related to a state of a battery of the vehicle (Fig.1, #108, and Paragraph 0033); and a service server configured to manage energy management software for one or more energy management services (Fig.1, #112, #114, Paragraph 0034 “the processing platform 105 can comprise multiple networked processing devices, such as a plurality of servers”, Fig.2, Paragraph 0095, Fig.9, and Paragraphs 0183 and 0213), wherein the platform managing server is further configured to: receive the vehicle data from the vehicle data managing server (Paragraph 0034 and Paragraph 0068); transmit the received vehicle data and a request for updated energy management software to the service server (Fig.3, Paragraphs 0136-0137, ); receive the updated energy management software from the service server (Paragraphs 0237-0242); and perform an update to autonomous driving software of the autonomous driving simulation based on the updated energy management software received from the service server (Fig.9, and Paragraphs 0183 and 0211-0213), and operate the autonomous driving simulation using the updated autonomous driving software based on the received vehicle data, and wherein the service server is configured to: receive the vehicle data from the platform managing server (Fig.3, and Paragraphs 0136-0137); determine a degree of degradation of the battery of the vehicle based on the vehicle data (Paragraph 0137 “battery capacity loss”, and Paragraphs 0159-0163 “fading model”); generate the updated energy management software based on the vehicle data (Paragraph 0171); and transmit the updated energy management software to the platform managing server (Paragraphs 0237-0242) However, You discloses the scheduling optimizer and the electric vehicle simulator as part of the processing platform (Fig.1) according to a first embodiment and doesn’t explicitly teach the following: a service server separate from the platform managing server and the vehicle data managing server wherein each of the platform managing server, the vehicle data managing server, and the service server are remote from the vehicle Nevertheless, You discloses in another embodiment, the optimization system comprises an optimizer, and the simulation system comprises a simulator and both, the optimization system or optimizer and the simulation system or simulator may be onsite or located in a remote central management system (Paragraphs 0242-0243) and teaches the following: a service server separate from the platform managing server and the vehicle data managing server It would have been obvious to one having ordinary skills in the art at the time the invention was filed to have modified the You reference to include a service server attached or separate from the platform managing server and the vehicle data managing server, as taught by You’s second embodiment, as a matter of design choice, since the applicant has not disclosed that having all servers separate solves any stated problem or is for any particular purpose and it appears that the invention would perform equally well with the servers being attached or separate (You, alternative embodiment, Paragraphs 0243-0245). Nevertheless, Nishida discloses a simulation apparatus capable of simulating the performance of a vehicle according to the battery to be mounted (Abstract) and teaches the following: wherein each of the platform managing server, the vehicle data managing server, and the service server are remote from the vehicle (Fig.1, #100, #200, and Paragraph Paragraphs 0021-0022) It would have been obvious to one having ordinary skills in the art at the time the invention was filed to have modified the You reference to include a market battery database and a market vehicle database, as taught by Nishida, with a reasonable expectation of success, in order to provide a simulation apparatus capable of simulating the performance of a vehicle according to the battery to be mounted (Nishida, Paragraph 0005). In re claims 2 and 11, You teaches the following: wherein the one or more energy management services includes at least one of a service for providing a diagnosis result obtained by diagnosing the state of the battery of the vehicle, a service for providing a life analysis result of the battery of the vehicle, or a service for providing a usage guide of the battery of the vehicle (Fig.2, and Paragraph 0095) In re claims 3 and 12, You teaches the following: wherein the platform managing server includes a hardware module supporting the autonomous driving of the vehicle (Fig.1, and Paragraph 0028) In re claims 5 and 14, You teaches the following: wherein the platform managing server is further configured to transmit the request for updated energy management software based on at least one of (i) a determination by the vehicle data managing server to update the autonomous driving software or (ii) detected replacement of the battery of the vehicle (Paragraphs 0040, 0073, and 0075) In re claims 6 and 15, You teaches the following: wherein the platform managing server is configured to transfer the vehicle data received from the vehicle data managing server to the service server in response to (i) an update request for the energy management software or (ii) a determination that the vehicle data matches one or more of the energy management services (Paragraphs 0038-0039) In re claims 8 and 17, You teaches the following: wherein the platform managing server is configured to transmit the updated autonomous driving software to the vehicle data managing server (Fig.1, #112, Fig.2, Paragraph 0095, Fig.9, and Paragraphs 0183 and 0213) In re claims 9 and 18, You teaches the following: wherein the vehicle data managing server is configured to transmit the updated autonomous driving software to the vehicle wirelessly (Fig.1, #104) Claim(s) 4 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over You and Nishida, and further in view of Gupta et al US 10,196,086 B2 (hence Gupta). In re claims 4 and 13, You discloses the claimed invention including a processor, a sensor module, and a power management module (Fig.1, #101 and Paragraph 0033) but doesn’t explicitly teach the following: a camera module Nevertheless, Gupta discloses trajectory control for autonomous vehicles (Abstract) and teaches the following: a camera module (Fig. 1, #110, and Col.3, Lines 35-55) It would have been obvious to one having ordinary skills in the art at the time the invention was filed to have modified the You reference to include a camera, as taught by Gupta, with a reasonable expectation of success, in order to capture images outside of the vehicle (Gupta, Col.4, Lines 53-61). Claim(s) 7 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over You and Nishida, and further in view of Haga JP 2021124419 A (the examiner has provided an English translation on 03/16/2026, and relying upon, hence Haga) In re claims 7 and 16, You discloses the claimed invention as recited above but doesn’t explicitly teach the following: wherein the service server is configured to: update the energy management software using the vehicle data received from the platform managing server by inputting the vehicle data into an artificial intelligence model and diagnosing the degree of degradation of the battery using the artificial intelligence model Nevertheless, Haga discloses a battery deterioration determination device for determining deterioration of a battery (Abstract) and teaches the following: wherein the service server is configured to: update the energy management software using the vehicle data received from the platform managing server by inputting the vehicle data into an artificial intelligence model and diagnosing the degree of degradation of the battery using the artificial intelligence model (Paragraph 0023) It would have been obvious to one having ordinary skills in the art at the time the invention was filed to have modified the You reference to include determining the deterioration of the battery using an AI model, as taught by Haga, with a reasonable expectation of success, in order to improve the deterioration probability as compared with the case of using a single first calculation model (Haga, Paragraph 0012). 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 RAMI KHATIB whose telephone number is (571)270-1165. The examiner can normally be reached M-F: 9:00am-5:30pm. 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, Erin M Piateski can be reached at 571-270 7429. 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. /RAMI KHATIB/Primary Examiner, Art Unit 3669
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Prosecution Timeline

Show 7 earlier events
Dec 30, 2025
Request for Continued Examination
Feb 11, 2026
Response after Non-Final Action
Mar 16, 2026
Non-Final Rejection mailed — §103
Jun 09, 2026
Interview Requested
Jun 15, 2026
Applicant Interview (Telephonic)
Jun 16, 2026
Examiner Interview Summary
Jul 16, 2026
Response Filed
Jul 30, 2026
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

5-6
Expected OA Rounds
77%
Grant Probability
91%
With Interview (+13.8%)
2y 10m (~1m remaining)
Median Time to Grant
High
PTA Risk
Based on 884 resolved cases by this examiner. Grant probability derived from career allowance rate.

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