Prosecution Insights
Last updated: April 19, 2026
Application No. 19/015,900

INFORMATION PROCESSING APPARATUS

Non-Final OA §102
Filed
Jan 10, 2025
Examiner
CHALHOUB, JEFFREY ROBERT
Art Unit
3663
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Toyota Jidosha Kabushiki Kaisha
OA Round
1 (Non-Final)
66%
Grant Probability
Favorable
1-2
OA Rounds
2y 10m
To Grant
99%
With Interview

Examiner Intelligence

Grants 66% — above average
66%
Career Allow Rate
97 granted / 146 resolved
+14.4% vs TC avg
Strong +53% interview lift
Without
With
+52.7%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
18 currently pending
Career history
164
Total Applications
across all art units

Statute-Specific Performance

§101
25.0%
-15.0% vs TC avg
§103
48.8%
+8.8% vs TC avg
§102
11.4%
-28.6% vs TC avg
§112
14.0%
-26.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 146 resolved cases

Office Action

§102
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 . Status of Claims This action is in reply to the Application Number 19/015,900 filed on 01/10/2025. Claims 1-5 are currently pending and have been examined. This action is made NON-FINAL. The examiner would like to note that this application is now being handled by examiner Jeffrey Chalhoub. Information Disclosure Statement The information disclosure statement (IDS) submitted on January 10th, 2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Drawings The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they do not include the following reference sign(s) mentioned in the description: “31”. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance. Claim Rejections - 35 USC § 102 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claims 1-5 are rejected under 35 U.S.C. 102 as being unpatentable over Ganjineh (U.S. Pub. No. 2020/0098135 A1). Regarding Claim 1: Ganjineh teaches: An information processing apparatus comprising a controller, the controller being configured to execute: acquiring first map data including position information of roads; acquiring probe data including a set of position information of a first mobile body positioned on a road;, (See (Ganjineh: Summary of the Invention – 20th-27th, 44th-52nd, and 133rd paragraphs)) training a machine learning model using the probe data as input data and the first map data as ground truth data;, (See (Ganjineh: Summary of the Invention – 58th and 68th paragraphs and Detailed Description of the Preferred Embodiments – 209th paragraph)) and converting second probe data including a set of position information of a second mobile body, into a road graph including position information of the roads, using the trained machine learning model., (See (Ganjineh: Summary of the Invention – 28th, 67th, and 122nd-127th paragraphs and Detailed Description of the Preferred Embodiments – 169th-181st and 214th paragraphs)) Regarding Claim 2: Ganjineh, as shown in the rejection above, discloses the limitations of claim 1. Ganjineh further teaches: The information processing apparatus according to claim 1, wherein the controller causes the machine learning model to, (See (Ganjineh: Summary of the Invention – 58th, 68th, and 133rd paragraphs and Detailed Description of the Preferred Embodiments – 209th paragraph)) […] learn a relative positional relationship between the set of position information of the first mobile body and an actual road., (See (Ganjineh: Summary of the Invention – 20th-27th and 44th-52nd paragraphs)) Regarding Claim 3: Ganjineh, as shown in the rejection above, discloses the limitations of claim 1. Ganjineh further teaches: The information processing apparatus according to claim 1, wherein the first map data includes position information of centerline of the roads,, (See (Ganjineh: Summary of the Invention – 45th-47th paragraphs and Detailed Description of the Preferred Embodiments – 154th paragraph)) […] and the controller trains the machine learning model using the position information of the centerline of the roads included in the first map data, as the ground truth data., (See (Ganjineh: Summary of the Invention – 26th, 58th, 68th, and 133rd paragraphs and Detailed Description of the Preferred Embodiments – 209th paragraph)) Regarding Claim 4: Ganjineh, as shown in the rejection above, discloses the limitations of claim 3. Ganjineh further teaches: The information processing apparatus according to claim 3, wherein the controller inputs set of position information included in the second probe data into, (See (Ganjineh: Summary of the Invention – 28th, 67th, 122nd-127th, and 133rd paragraphs and Detailed Description of the Preferred Embodiments – 169th-181st and 214th paragraphs)) […] trained machine learning model and obtains a set of position information of the centerline of corresponding road, as an estimation result., (See (Ganjineh: Summary of the Invention – 45th-47th, 58th, and 68th-70th paragraphs and Detailed Description of the Preferred Embodiments – 154th, 209th, 227th, and 254th paragraphs)) Regarding Claim 5: Ganjineh, as shown in the rejection above, discloses the limitations of claim 1. Ganjineh further teaches: The information processing apparatus according to claim 1, wherein the probe data further includes data regarding position of road boundaries and/or lane boundaries,, (See (Ganjineh: Summary of the Invention – 45th and 98th-115th paragraphs and Detailed Description of the Preferred Embodiments – 234th-236th paragraphs)) […] and the controller further includes the data in the input data to train the machine learning model., (See (Ganjineh: Summary of the Invention – 58th, 68th, and 133rd paragraphs and Detailed Description of the Preferred Embodiments – 209th paragraph)) Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jeffrey Chalhoub whose telephone number is (571) 272-9754. The examiner can normally be reached Mon-Fri 8:30-5:30. 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, Angela Ortiz can be reached on (571) 272-1206. 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. /J.R.C./Examiner, Art Unit 3663 /ANGELA Y ORTIZ/Supervisory Patent Examiner, Art Unit 3663
Read full office action

Prosecution Timeline

Jan 10, 2025
Application Filed
Feb 28, 2026
Non-Final Rejection — §102 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12600377
Cooperative Vehicle Infrastructure Information Processing Method and Apparatus, and Terminal Device
2y 5m to grant Granted Apr 14, 2026
Patent 12594835
SYSTEM FOR CONTROLLING VEHICLE DISPLAY BASED ON OCCUPANT'S GAZE
2y 5m to grant Granted Apr 07, 2026
Patent 12573305
ARTIFICIALLY INTELLIGENT SKYWAY
2y 5m to grant Granted Mar 10, 2026
Patent 12559131
METHOD OF A CONTROL CENTER FOR OPERATING AN AUTOMATED VEHICLE AND AUTOMATED VEHICLE
2y 5m to grant Granted Feb 24, 2026
Patent 12534086
VEHICLE AND COMPUTER PROGRAM
2y 5m to grant Granted Jan 27, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

1-2
Expected OA Rounds
66%
Grant Probability
99%
With Interview (+52.7%)
2y 10m
Median Time to Grant
Low
PTA Risk
Based on 146 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month