Office Action Predictor
Last updated: April 16, 2026
Application No. 19/315,113

Controlling Vehicles in Response to Users of Other Vehicles

Non-Final OA §102
Filed
Aug 29, 2025
Examiner
LOUIE, WAE LENNY
Art Unit
3661
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Unknown
OA Round
1 (Non-Final)
85%
Grant Probability
Favorable
1-2
OA Rounds
2y 10m
To Grant
93%
With Interview

Examiner Intelligence

Grants 85% — above average
85%
Career Allow Rate
670 granted / 790 resolved
+32.8% vs TC avg
Moderate +8% lift
Without
With
+8.3%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
18 currently pending
Career history
808
Total Applications
across all art units

Statute-Specific Performance

§101
10.4%
-29.6% vs TC avg
§103
47.3%
+7.3% vs TC avg
§102
25.1%
-14.9% vs TC avg
§112
10.9%
-29.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 790 resolved cases

Office Action

§102
E 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 . Claim Rejections - 35 USC § 102 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. Claim(s) 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Micks et al. (2017/0124407). Regarding applicant claim 1, Micks discloses a non-transitory computer readable medium storing computer implementable instructions that when executed by at least one processor cause the at least one processor to perform operations for controlling vehicles in response to users of other vehicles, the operations comprising: obtaining one or more images captured using one or more image sensors from an environment of a first vehicle ([0012] “sensors and sensing devices; employing deep neural networks trained to estimate the direction of a driver’s gaze and recognize key gestures made by drivers”); analyzing the one or more images to detect a second vehicle ([0013] “locate vehicles within a current 360 degree frame of sensor data”); analyzing the one or more images to determine a state of a user associated with the second vehicle ([0012] “sensors and sensing devices; employing deep neural networks trained to estimate the direction of a driver’s gaze and recognize key gestures made by drivers”); and causing the first vehicle to initiate an action responding to the second vehicle based on the determined state of the user associated with the second vehicle ([0013] “use the resulting estimates for driver body language to interpret driver intent in terms of predicted motion of the other vehicles”; [0038] “determine when to wait or proceed at an intersection, when to change lanes, when to leave space for another vehicle to change lanes”). Regarding applicant claim 2, Micks discloses wherein the operations further comprise: in response to a first determined state of the user associated with the second vehicle, causing the first vehicle to initiate the action responding to the second vehicle; and in response to a second determined state of the user associated with the second vehicle, forgoing causing the first vehicle to initiate the action ([0013] “use the resulting estimates for driver body language to interpret driver intent in terms of predicted motion of the other vehicles”; [0038] “determine when to wait or proceed at an intersection, when to change lanes, when to leave space for another vehicle to change lanes”). Regarding applicant claim 3, Micks discloses wherein the action comprises at least one of signaling, changing a speed of the first vehicle, changing a motion direction of the first vehicle, driving in reverse, or generating an audible warning ([0038] “automated driving assistance system may determine a path and speed to drive based on information or perception data”; [0042] “based on the inferred intent, the vehicle may slow down, speed up, and/or turn to avoid a potential collision”). Regarding applicant claim 4, Micks discloses wherein the action is selected based on the determined state of the user associated with the second vehicle ([0040] “driver intent component”). 5. The non-transitory computer readable medium of claim 1, wherein the second vehicle is a garbage truck, and the user is a waste collector. Regarding applicant claim 6, Micks discloses wherein the determined state of the user associated with the second vehicle is embarking the second vehicle ([0040] “driver intent component”; [0053] “exiting a roadway, parking a vehicle, exiting a parking spot or the like”). Regarding applicant claim 7, Micks discloses wherein the determined state of the user associated with the second vehicle is disembarking the second vehicle ([0053] “exiting a roadway, parking a vehicle, exiting a parking spot or the like”). Regarding applicant claim 8, Micks discloses wherein the determined state of the user associated with the second vehicle is being in the second vehicle ([0053] “exiting a roadway, parking a vehicle, exiting a parking spot or the like”). Regarding applicant claim 9, Micks discloses wherein the operations further comprise analyzing the one or more images to determine that a person located in a vicinity of the second vehicle is speaking with the user to thereby determine the state of the user associated with the second vehicle ([0041] “detecting the face of the driver”). Regarding applicant claim 10, Micks discloses wherein the determined state of the user associated with the second vehicle is based on an orientation of at least part of the user ([0041] “detecting the face of the driver”; [0023] “driver intent… based on a gesture, a gaze direction, a head orientation, or any other body language of the driver of the different vehicle”). Regarding applicant claim 11, Micks discloses wherein the determined state of the user associated with the second vehicle is based on a distance of at least part of the user from at least a part of the second vehicle ([0026]-[0027]). Regarding applicant claim 12, Micks discloses wherein the determined state of the user associated with the second vehicle is based on a motion of at least part of the user ([0041] “detecting the face of the driver”; [0023] “driver intent… based on a gesture, a gaze direction, a head orientation, or any other body language of the driver of the different vehicle”). Regarding applicant claim 13, Micks discloses wherein the operations further comprise: determining a motion of the second vehicle; and further basing the causing the first vehicle to initiate the action on the determined motion of the second vehicle [0024] “vehicle control system”; [0038] “vehicle control actuators to drive a path on a road, parking lot”). Regarding applicant claim 14, Micks discloses wherein the operations further comprise: determining that the second vehicle is signaling; and further basing the causing the first vehicle to initiate the action on the determination that the second vehicle is signaling ([0034] “receive signals from one or more other data or signal sources”). Regarding applicant claim 15, Micks discloses wherein the operations further comprise: determining that the second vehicle is in a lane of the first vehicle; and further basing the causing the first vehicle to initiate the action on the determination that the second vehicle is in the lane of the first vehicle ([0038] “change lanes, when to leave space for another vehicle”; [0051] “lane merge”). Regarding applicant claim 16, Micks discloses wherein the operations further comprise: determining that the second vehicle is in a planned path of the first vehicle; and further basing the causing the first vehicle to initiate the action on the determination that the second vehicle is in the planned path of the first vehicle ([0057] “determine a driving path to avoid collision with the other vehicles in case they perform the predicted driving maneuvers”). Regarding applicant claim 17, Micks discloses wherein the operations further comprise using an artificial neural network to analyze the one or more images to determine the state of a user associated with the second vehicle ([0012] “deep neural networks”). Regarding applicant claim 18, Micks discloses wherein the state of the user associated with the second vehicle is further based on information received using a communication device from the second vehicle ([0034] “vehicle-to-vehicle V2V communications… may receive information from other vehicles about their locations, traffic, accidents, road conditions”). Regarding applicant claim 19, Micks discloses a system for controlling vehicles in response to users of other vehicles, the system comprising: at least one processing unit configured to perform operations, the operations comprise ([0021]): obtaining one or more images captured using one or more image sensors from an environment of a first vehicle ([0012] “sensors and sensing devices; employing deep neural networks trained to estimate the direction of a driver’s gaze and recognize key gestures made by drivers”); analyzing the one or more images to detect a second vehicle ([0013] “locate vehicles within a current 360 degree frame of sensor data”); analyzing the one or more images to determine a state of a user associated with the second vehicle ([0012] “sensors and sensing devices; employing deep neural networks trained to estimate the direction of a driver’s gaze and recognize key gestures made by drivers”); and causing the first vehicle to initiate an action responding to the second vehicle based on the determined state of the user associated with the second vehicle ([0013] “use the resulting estimates for driver body language to interpret driver intent in terms of predicted motion of the other vehicles”; [0038] “determine when to wait or proceed at an intersection, when to change lanes, when to leave space for another vehicle to change lanes”). Regarding applicant claim 20, Micks discloses a method for controlling vehicles in response to users of other vehicles, the method comprising: obtaining one or more images captured using one or more image sensors from an environment of a first vehicle ([0012] “sensors and sensing devices; employing deep neural networks trained to estimate the direction of a driver’s gaze and recognize key gestures made by drivers”); analyzing the one or more images to detect a second vehicle ([0013] “locate vehicles within a current 360 degree frame of sensor data”); analyzing the one or more images to determine a state of a user associated with the second vehicle ([0012] “sensors and sensing devices; employing deep neural networks trained to estimate the direction of a driver’s gaze and recognize key gestures made by drivers”); and causing the first vehicle to initiate an action responding to the second vehicle based on the determined state of the user associated with the second vehicle ([0013] “use the resulting estimates for driver body language to interpret driver intent in terms of predicted motion of the other vehicles”; [0038] “determine when to wait or proceed at an intersection, when to change lanes, when to leave space for another vehicle to change lanes”). Any inquiry concerning this communication or earlier communications from the examiner should be directed to WAE LENNY LOUIE whose telephone number is (571)272-5195. The examiner can normally be reached M-F 6AM-3PM. 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, PETER D NOLAN can be reached at 571-270-7016. 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. /W.L.L/Examiner, Art Unit 3661 /PETER D NOLAN/Supervisory Patent Examiner, Art Unit 3661
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Prosecution Timeline

Aug 29, 2025
Application Filed
Jan 10, 2026
Non-Final Rejection — §102
Mar 16, 2026
Response Filed

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
85%
Grant Probability
93%
With Interview (+8.3%)
2y 10m
Median Time to Grant
Low
PTA Risk
Based on 790 resolved cases by this examiner. Grant probability derived from career allow rate.

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