Prosecution Insights
Last updated: August 18, 2026
Application No. 18/161,954

BUILDING AND TRAINING A LANELET CLASSIFICATION SYSTEM FOR AN AUTONOMOUS VEHICLE

Non-Final OA §101
Filed
Jan 31, 2023
Examiner
PAIGE, TYLER D
Art Unit
3664
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
GM Global Technology Operations LLC
OA Round
2 (Non-Final)
91%
Grant Probability
Favorable
2-3
OA Rounds
0m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 91% — above average
91%
Career Allowance Rate
1180 granted / 1292 resolved
+39.3% vs TC avg
Moderate +8% lift
Without
With
+8.4%
Interview Lift
resolved cases with interview
Fast prosecutor
1y 10m
Avg Prosecution
31 currently pending
Career history
1316
Total Applications
across all art units

Statute-Specific Performance

§101
16.3%
-23.7% vs TC avg
§103
31.8%
-8.2% vs TC avg
§102
23.3%
-16.7% vs TC avg
§112
16.7%
-23.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1292 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 . This office action is in response to an amendment/argument submitted on 04/07/2026. The applicant amends claims 1, 9, 10, and 19 are amended. This is a second Non – Final Rejection. 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 – 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea of mathematical operation without significantly more. The claims are evaluated with respect to the MPEP and the 2019 Subject Matter Guidance. Example 41 of the guidance is used as a reference for analysis. Step 1 The claims recite A lanelet classification system for an autonomous vehicle, the lanelet classification system, the claims are directed to one of the four statutory categories and therefore passes Step 1. Claim 1 is listed below with the abstract idea identified and the pre/ post solution activity identified. Step 2A Prong I Claim 1 A lanelet classification system for an autonomous vehicle, the lanelet classification system comprising: one or more controllers including a classifier having a neural network that classifies lanelets of a lane graph structure based on one or more lane attributes, the one or more controllers executing instructions to build the neural network by: (pre solution activity) determining a higher dimension feature for a plurality of local lanelets and a subject lanelet, wherein a spatial relationship exists between the subject lanelet and the local lanelets, wherein the lanelets of the lane graph structure are based on perception data and map data indicating road-level information for autonomous driving, and each lanelet represents a single interconnectable lane segment and is classified based on one or more lane attributes, and wherein the lane attributes represent one or more permitted maneuvers associated with a subject lanelet; (mathematical operation) computing an attention score for each of the local lanelets based on the higher dimension feature, wherein the attention score indicates a weight value that the subject lanelet has on a particular local lanelet; (mathematical operation) determining a normalized shared attention mechanism applicable to all of the local lanelets based on the attention score; (mathematical operation) computing a transformed feature vector of the local lanelet based on the higher dimension feature and the normalized shared attention mechanism; (mathematical operation) and fusing the transformed feature vector for each of the local lanelet together to determine a single fused feature vector, wherein the single fused feature vector is input to build a subsequent layer of the neural network. (Post solution activity) With respect to the MPEP, the inventive concept is evaluated with respect to the MPEP 2106.07 and is determined is a mathematical operation used to identify lanelet markings connected to a road. With respect to MPEP 2106.04(a)(2)(I), the features of the independent claims 9 and 19 and dependent claims 2 – 8, 10 – 18, and 20 are mathematical operations used to apply to a nueral network. It isn’t clear what the neural network is trained to do without identifying any structure that collects data. With respect to the 2019 Guidance, example 41 is the threshold for the review of the claims. In the example there is a specific correlation to the operations and how they are applied to the operation of the invention. In this case, the operations do not have a correlation with the how the lanelets are identified and determined. Therefore, the claims fail Step 2A Prong I. Step 2A Prong II This judicial exception is not integrated into a practical application because the claims fail to satisfy the requirements of MPEP 2106.04(d)(1-2). The claims do not identify a new or improved manner of identifying a lanelet. A camera, lidar, or radar may perform the same operation. The claims fail to identify any structure collecting the data. With respect to the 2019 Guidance, the claim identifies how the data is collected. In addition, the claims do not identify how the mathematical operations are correlated to performing identification. Therefore, the lack of the identifying the lanelet and thus fails Step 2A Prong II. Step 2B The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims fail to satisfy the MPEP 2106.05(a-h) and the 2019 Guidance. With respect to the MPEP, the claims fail to show how the invention is new in the area of technology with how the mathematical operations identify a lanelet. The 2019 Guidance isn’t satisfied because the mathematical operation isn’t correlated to how it is an improvement in the area of technology. Therefore, the claims fail Step 2B. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to TYLER D PAIGE whose telephone number is (571)270-5425. The examiner can normally be reached M-F 7:00am - 6:00pm (mst). 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, Kito Robinson can be reached at 5712703921. 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. /TYLER D PAIGE/Primary Examiner, Art Unit 3664
Read full office action

Prosecution Timeline

Jan 31, 2023
Application Filed
Jan 28, 2026
Non-Final Rejection mailed — §101
Apr 07, 2026
Response Filed
Apr 07, 2026
Examiner Interview Summary
Apr 07, 2026
Applicant Interview (Telephonic)
Jun 16, 2026
Non-Final Rejection mailed — §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

2-3
Expected OA Rounds
91%
Grant Probability
99%
With Interview (+8.4%)
1y 10m (~0m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 1292 resolved cases by this examiner. Grant probability derived from career allowance rate.

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