Prosecution Insights
Last updated: October 02, 2026
Application No. 18/908,506

IMPROVED RACING SIMULATION USING FORCE FEEDBACK AT STEERING WHEEL

Final Rejection §101§103
Filed
Oct 07, 2024
Examiner
GRANT, MICHAEL CHRISTOPHER
Art Unit
3715
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Lenovo (United States) Inc.
OA Round
2 (Final)
22%
Grant Probability
At Risk
3-4
OA Rounds
1y 9m
Est. Remaining
29%
With Interview

Examiner Intelligence

Grants only 22% of cases
22%
Career Allowance Rate
168 granted / 772 resolved
-48.2% vs TC avg
Moderate +7% lift
Without
With
+7.4%
Interview Lift
resolved cases with interview
Typical timeline
3y 9m
Avg Prosecution
57 currently pending
Career history
848
Total Applications
across all art units

Statute-Specific Performance

§101
29.7%
-10.3% vs TC avg
§103
33.9%
-6.1% vs TC avg
§102
11.6%
-28.4% vs TC avg
§112
19.9%
-20.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 772 resolved cases

Office Action

§101 §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 . Applicant’s amendments dated 7/10/26 are hereby entered. 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, 14-16, 19 and 21-35 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1, 14-16, 19 and 21-35 are directed to an abstract idea without significantly more. The claims recite a mental process that can be performed by a human being, the rules of a game, and/or training/employing a generic machine learning model in a particular technological environment. In regard to Claims 1, 16, and 19, the following limitations can be performed as a mental process by a human being in terms of claiming collecting data, analyzing that data, and providing outputs based on that analysis which has been held by the CAFC to be an abstract idea in decisions such as, e.g., Electric Power Group, University of Florida Research Foundation, and Yousician v Ubisoft (non-precedential); and/or claim the rules of a game which has been identified by the CAFC as being an abstract ides in decisions such as, e.g., Savvy Dog Systems v. Pennsylvania Coin (non-precedential; 2023-1073; 3/21/24), in terms of the Applicant claiming: [a] method, comprising: facilitating a racing simulation […]; and as part of facilitating the racing simulation, […] adapt[ing] […] feedback […] as the racing simulation transpires, the […[ feedback being adapted during execution of the simulation based on one or more variable inputs associated with the racing simulation. In regard to Claims 1, 16, and 19, Applicant also claims training/employing a generic machine learning technique in a particular environment which has been held by the CAFC in, e.g., Recentive Analytics to be an abstract idea. In regard to the dependent claims, they also claim an abstract idea to the extent that they merely claim further limitations that likewise could be performed as a mental process by a human being, and/or the rules of a game, and/or training/employing a generic machine learning technique in a particular environment. Furthermore, this judicial exception is not integrated into a practical application because to the extent that additional elements are claimed either alone or in combination such as, e.g., a processor system and computer readable storage medium accessible to the processor system and comprising instructions embodying Applicant’s abstract idea and executable by the processor system, a steering wheel input device, an electronic headset, training/employing a machine learning model, these are merely claimed to add insignificant extra-solution activity to the judicial exception (e.g., data gathering), to embody the abstract idea on a general purpose computer, and/or do no more than generally link the use of a judicial exception to a particular technological environment or field of use. In this regard, see MPEP 2106.04(d)(I) in regard to “courts have also identified limitations that did not integrate a judicial exception into a practical application…” Furthermore, the claims do not include additional elements that taken individually, and also taken as an ordered combination, are sufficient to amount to significantly more than the judicial exception because to the extent that, e.g., a processor system and computer readable storage medium accessible to the processor system and comprising instructions embodying Applicant’s abstract idea and executable by the processor system, a steering wheel input device, an electronic headset, training/employing a machine learning model, these are well-understood, routine, and conventional elements and are claimed for the well-understood, routine, and conventional functions of collecting and processing data and/or providing an analysis/outputs based on that processing. To the extent that an apparatus is claimed as an additional element said apparatus fails to qualify as a “particular machine” to the extent that it is claimed generally, merely implements the steps of Applicant’s claimed method, and is claimed merely for purposes of extra-solution activity or field of use. See MPEP 2106.05(b). As evidence that these additional elements are well-understood, routine, and conventional, Applicant’s specification discloses the support for these elements in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a). See, e.g., F1 and F3-F4 in Applicant’s PGPUB and text regarding same; also see, e.g., p56-57 and p84-85 regarding training/employing a machine learning model. Claim Rejections - 35 USC § 103 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. Claims 1, 14-16, 19, 21, 25, 29, 32, and 34-35 are rejected under 35 U.S.C. 103 as being unpatentable over PGPUB US 20070149284 A1 by Plavetich et al (“Plavetich”), in view of PGPUB US 20230117814 A1 by Moore et al (“Moore”). In regard to Claim 1, Plavetich teaches a device, comprising: a processor system; and storage accessible to the processor system and comprising instructions executable by the processor system to: facilitate a racing simulation; (see, e.g., F4); as part of facilitating the racing simulation, […] adapt force feedback at a steering wheel input device in real time as the racing simulation transpires, the force feedback being adapted in real time based on one or more variable inputs associated with the racing simulation (see, e.g., p14). Furthermore, to the extent that Playetich may fail to specifically teach the remaining claimed limitations, however, in an analogous reference Moore teaches employing machine learning in order to provide haptic feedback in a simulation (see, e.g., p42); Furthermore, the combination of the cited prior art would have been obvious to one of ordinary skill in the art at the time of filing because the cited prior art includes each element claimed, although not necessarily in a single prior art reference, with the only difference between the claimed invention and the cited prior art being the lack of actual combination of the elements in a single prior art reference; one of ordinary skill in the art could have combined the elements as claimed by known methods, and that in combination, each element merely performs the same function as it does separately; and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Specifically, it would have been obvious to have employed the teachings of Moore as part of the device otherwise taught by Playetich, and to have employed an ML model to help determine the force feedback to the steering wheel, in order to provide more realistic feedback. In regard to Claim 14, Plavetich teaches these limitations. See, e.g., F3. In regard to Claims 21, 25, and 29, Moore teaches employing real world data and simulator inputs to train the machine learning model (see, e.g., p42); Furthermore, the combination of the cited prior art would have been obvious to one of ordinary skill in the art at the time of filing because the cited prior art includes each element claimed, although not necessarily in a single prior art reference, with the only difference between the claimed invention and the cited prior art being the lack of actual combination of the elements in a single prior art reference; one of ordinary skill in the art could have combined the elements as claimed by known methods, and that in combination, each element merely performs the same function as it does separately; and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Specifically, it would have been obvious to have employed the teachings of Moore as part of the device otherwise taught by Playetich, and to have employed real world driving data and simulator inputs to train the ML model, in order to make the model perform more realistically. In regard to Claim 16, see rejection of Claim 1. In regard to Claim 32, see rejection of Claim 21. In regard to Claim 19, see rejection of Claim 1. In regard to Claim 34-35, see rejection of Claim 21. Claims 22-24 are rejected under 35 U.S.C. 103 as being unpatentable over Plavetich, in view of Moore, in view of official notice. In regard to Claims 22-24, the Examiner takes OFFICIAL NOTICE that such data were old and well-known at the time of Applicant’s filing its invention. As such it would have been obvious to one of ordinary skill in the art at the time of filing to employed the claimed data within the invention of the cited prior art so as to have the ML model perform as realistically as possible. Claims 26-28 are rejected under 35 U.S.C. 103 as being unpatentable over Plavetich, in view of Moore, in view of official notice. In regard to Claims 22-24, the Examiner takes OFFICIAL NOTICE that such inputs to a driving simulator were old and well-known at the time of Applicant’s filing its invention. As such it would have been obvious to one of ordinary skill in the art at the time of filing to employed the claimed inputs within the invention of the cited prior art so as to have the ML model perform as realistically as possible. Claims 30-31 and 33 are rejected under 35 U.S.C. 103 as being unpatentable over Plavetich, in view of Moore, in view of official notice. In regard to Claim 30, while Moore teaches employing various ML modeling techniques (see, e.g., p58), it may fail to teach the specifically claimed technique, however, the Examiner takes OFFICIAL NOTICE that such ML modeling techiques were old and well-known at the time of Applicant’s filing its invention. As such it would have been obvious to one of ordinary skill in the art at the time of filing to employed them within the invention of the cited prior art so as to have the ML model perform as realistically as possible. Response to Arguments Applicant argues on page 8 of its Remarks in regard to the rejections made under 35 USC 101: PNG media_image1.png 154 700 media_image1.png Greyscale Applicant’s argument is not persuasive as the 101 rejection made supra identifies precisely which limitations are considered to be the abstract idea, identifies what type of abstract ideas are alleged to be claimed, as well as identifies legal authority in support of those allegations. Applicant also argues on page 8 of its Remarks in regard to the rejections made under 35 USC 101: PNG media_image2.png 522 686 media_image2.png Greyscale Applicant’s argument is not persuasive. See MPEP 2106.07(A)(III) (emphasis added): Examiners should not assert that an additional element (or combination of elements) is well-understood, routine, or conventional unless the examiner finds, and expressly supports the rejection in writing with one or more of the following: (A) A citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates the well-understood, routine, conventional nature of the additional element(s). A specification demonstrates the well-understood, routine, conventional nature of additional elements when it describes the additional elements as well-understood or routine or conventional (or an equivalent term), as a commercially available product, or in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. 112(a). A finding that an element is well-understood, routine, or conventional cannot be based only on the fact that the specification is silent with respect to describing such element. Applicant also argues on page 9 of its Remarks in regard to the rejections made under 35 USC 101: PNG media_image3.png 302 692 media_image3.png Greyscale Applicant’s argument is not persuasive because as stated in the 101 rejection the dependent claims also claim an abstract idea to the extent that they merely claim further limitations that likewise could be performed as a mental process by a human being, and/or the rules of a game, and/or training/employing a generic machine learning technique. Applicant has, thereby, been provided with an adequate basis for the rejections. For these reasons the 101 rejections are maintained. 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 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 mailing date of this final action. Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Mike Grant whose telephone number is 571-270-1545. The Examiner can normally be reached on Monday through Friday between 8:00 a.m. and 5:00 p.m., except on the first Friday of each bi-week. If attempts to reach the Examiner by telephone are unsuccessful, the Examiner's Supervisory Primary Examiner, Peter Vasat can be reached at 571-270-7625. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. 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 unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /MICHAEL C GRANT/Primary Examiner, Art Unit 3715
Read full office action

Prosecution Timeline

Oct 07, 2024
Application Filed
May 08, 2026
Non-Final Rejection mailed — §101, §103
Jul 10, 2026
Response Filed
Jul 29, 2026
Final Rejection mailed — §101, §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

3-4
Expected OA Rounds
22%
Grant Probability
29%
With Interview (+7.4%)
3y 9m (~1y 9m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 772 resolved cases by this examiner. Grant probability derived from career allowance rate.

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