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 Objections
Claims 1, 5, 8, 12, 15, and 19 objected to because of the following informalities:
Claim 1 line 6, claim 8 line 9, and claim 15 line 12 read "the receive data" which appears to be a conjugation error and should read "the received data" to improve clarity.
Claim 5 line 1, claim 12 line 1, and claim 19 line 1 read "sensors comprises of" which appears to be a conjugation error and should read "sensors are comprised of" to improve clarity.
Claim 1 line 3, claim 8 line 5, and claim 15 line 8 read "training a model… further comprising" which appears to be a continuity error since the model has not been detailed comprising anything previously, so this should read "training a model… comprising" to improve clarity and consistency.
Claim 1 line 1 and claim 8 line 1 read "allowing vehicle" which appears to be a typographical error and should read "allowing a vehicle" to improve clarity.
Claim 15 line 1 read "autonomous vehicles", but examiner believes this may be intended to read "an autonomous vehicle" in light of amendments to claims 1 and 8 using parallel language.
Claim 1 line 5, claim 8 line 7, and claim 15 line 10 (provided suggested correction e is utilized) read "a vehicle" which appears to be a continuity error since the vehicle already has antecedent basis in the claim and therefore should read "the vehicle" to improve clarity.
Appropriate correction is required.
Claim Interpretation
The “computer readable storage media” (hereinafter CRM) used to store program instructions in claims 8 and 15 is broadly claimed and being interpreted in light of paragraph 0069 of the specification:
“Program instructions and data (e.g., software and data x10) used to practice embodiments of the present invention may be stored in persistent storage 505 and in memory 502 for execution by one or more of the respective processor(s) 501 via cache 503. In an embodiment, persistent storage 505 includes a magnetic hard disk drive. Alternatively, or in addition to a magnetic hard disk drive, persistent storage 505 can include a solid state hard drive, a semiconductor storage device, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, or any other computer readable storage media that is capable of storing program instructions or digital information.”
Since the applicant has adequately limited the CRM within the specification to only non-transitory CRM, it is unreasonable to interpret the CRM as, for example, transitory signals that may result in rejection under 101 as signals per se. Therefore, CRM will be broadly and reasonably interpreted as any non-transitory CRM.
“Autonomous vehicle” is being interpreted by the definition known in art as a vehicle having an autonomous driving mode (see "AUTONOMOUS VEHICLE DEFINITIONS" by the California DMV for evidence of this definition). Therefore, “autonomous vehicle” is interpreted as including a manned or unmanned, fully-autonomous or semi-autonomous vehicle (commonly referred to as levels 3-5 of driving autonomation in the art).
“Model” is being interpreted as a machine learning model.
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 an abstract idea without significantly more. The claim(s) recite(s) identifying instructions and determining a path based on received sensor data and identified instructions.
The limitation recited above, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic components. That is, other than reciting a processor, a CRM, virtual devices, a vehicle, and sensors, nothing in the claim element precludes the steps from practically being performed in the mind. For example, a person can easily see a traffic directing robot, determine if the traffic directing robot is being operated by a policeman by observation of a displayed badge number or movement pattern, interpret the robot’s gestures mentally as traffic instructions, and determine a path forward keeping in mind the robot’s instructions and any GPS map data. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the "Mental Processes" grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application because the processor, CRM, virtual devices, vehicles, and sensors is/are recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components, vehicles, and devices. Mere instructions to apply an exception using a generic element cannot provide an inventive concept. The training, testing, and deploying of the model is recited at a high generality such that they amount to no more than mere instructions to apply machine learning methods to the abstract idea and generally link the abstract idea to a realm of machine learning (see Claim Interpretation above). Mere instructions to apply an exception cannot provide an inventive concept. Furthermore, the deployment step is inherently broad and can encompass an insignificant extra solution activity of transmitting said model to the vehicles for use. The claims also recite receiving instructions and sensor data which (when not considered as an observation step of the mental process) constitute as insignificant extra pre-solution activities of mere data gathering. Mere data gathering cannot provide an inventive concept. The maneuvering step of the claims can potentially be interpreted in a manner to integrate the abstract idea into a practical application by physically controlling vehicles; however, under broadest reasonable interpretation, all interpretations must be considered. Consider paragraph 0055 of the specification:
“In another embodiment, the present invention can be implemented in non-autonomous vehicle with a slight variation. For example, a vehicle equipped with a vision/camera system to help detect road hazards can be utilized to help a distracted human driver be aware of a traffic event requiring attention to virtual and/or live personnel to redirect traffic. The distracted human driver can be notified by their vehicle through the vehicle’s sound system and/or on-screen display. The human driver would have to apply the necessary control (e.g., brake, turn, etc.) based on the received notification.” (Emphasis added.)
It is therefore clear that the maneuvering step may not only be vehicle control but may also be interpreted as a mere notification to the driver to perform a vehicular operation. The claim interpretation of “autonomous vehicle” above also allows for the vehicle to be semi-autonomous and therefore the method may be performed when an autonomous driving mode is powered off (i.e. the vehicle is in a non-autonomous mode) utilizing the notification as detailed in paragraph 0055 cited above. Notification in this manner is naught but insignificant extra post solution activity of mere display. Mere display cannot form an inventive concept.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the processor, CRM, virtual devices, vehicles, sensors, training, and testing steps are generically recited as detailed above. A conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, and conventional activity in the field. The limitation of receiving instructions and receiving sensor data is a well-understood, routine, and conventional activity because Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015) and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93 indicated that the storage and retrieval of data from memory is a well-understood, routine, and conventional function. See MPEP 2106.05(d)(II). The limitation of displaying a notification to a driver is a well-understood, routine, and conventional activity because Interval Licensing LLC v. AOL, Inc., 896 F.3d 1335, 1344-45, 127 USPQ2d 1553, 1559-60 (Fed. Cir. 2018) indicated that the display of data without any limitations specifying how to achieve the result is a well-understood, routine, and conventional function. See MPEP 2106.05(a)(II). The limitation of transmitting data is a well-understood, routine, and conventional activity because buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) indicated that the transmission and reception of data over a network is a well-understood, routine, and conventional function. See MPEP 2106(d)(II). Hence, the claims are not patent eligible.
Dependent claim(s) 2-7, 9-14, and 16-20 do(es) not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of the dependent claim(s) is/are directed towards further aspects of the abstract idea, further generic elements, and further insignificant extra solution activities.
Claims 3, 10, and 17 provide additional insignificant extra pre solution activities of data transmission as the virtual devices are remotely controlled by virtual users (i.e. at least control data is transmitted from the virtual user to the virtual device) and mere display as instructions from users are merely displayed on the virtual devices. Mere display and mere transmission of data have been shown as well understood, routine, and convention functions as detailed above.
Claims 2, 4, 6, 9, 11, 13, 16, and 18 only detail further aspects of the abstract idea.
Claims 5, 12, and 19 only detail further additional generic elements.
Claims 7, 14, and 20 only detail further aspects of the abstract idea. The recitation that hand gestures are interpreted with AV models is but mere recitation that the abstract idea is performed by a computer. The recitation of an abstract idea applied to a computer does not prohibit the idea from being performed mentally as detailed in MPEP 2106.04(a)(2)(III)(C) and the court cases cited therein.
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.
Claim(s) 1-5, 7-12, and 14-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gupta US 20240286638 A1 (hereinafter Gupta) in view of "Controlling Traffic with Humanoid Social Robot" by Ghaffar (hereinafter Ghaffar; a copy has been provided by the applicant which the examiner relies upon) and "Robot Behavior-Based User Authentication for Motion-Controlled Robotic Systems" by Huang et al. (hereinafter Huang).
Regarding claims 1, 8, and 15; Gupta teaches a computer system for allowing a vehicle (Abstract “vehicle”) to follow traffic instructions from a virtual device, the computer system comprising:
one or more computer processors (paragraph 0031 "processor");
a computer program product comprising:
one or more computer readable storage media (paragraph 0031 "memory") and program instructions stored on the one or more computer readable storage media (paragraph 0031 "For example, the memory 126 may store software instructions 128 that when executed by the processor 122 causes the control device 350 to perform one or more functions described herein"), the program instructions comprising a computer-implemented method comprising:
training a model with a dataset to recognize a traffic signal (paragraphs 0041 "The hand signal detection machine learning module 140 may be trained by a training dataset 146"; paragraph 0036 "The object detection machine learning modules 132 may be trained by a training dataset 141"), further comprising:
validating the model (paragraph 0041 "The hand signal detection machine learning module 140 may be trained, tested, and refined"; "The object detection machine learning modules 132 may be trained, tested, and refined"); and
deploying the model by integrating into a software system of a vehicle, (paragraph 0042 discloses the hand signal detection machine learning module working in a vehicle indicating it has been "deployed"; paragraph 0035 discloses the object detection machine learning module working in a vehicle indicating it has been "deployed"; also see paragraph 0007 wherein the hand signal detection machine learning module is indicated as "pre-trained" before use and see Figure 2 regarding utilizing the deployed, trained machine learning modules), wherein the vehicle is an autonomous vehicle (Abstract "autonomous vehicle");
receiving, by the vehicle, instructions from traffic controllers (Figure 2 204 "determine that the sensor data comprises an indication of a person altering a traffic flow using a hand signal"; also see Figure 2 212 "communicate the sensor data, the hand signal interpretation, and a query message to an oversight server, where the query message requests to verify the hand signal interpretation");
identifying, by the vehicle, the instructions (Figure 2 206 "determine an interpretation of the hand signal"; also see Figure 2 214 "receive a first message that indicates the hand signal interpretation is verified");
receiving, by the vehicle, data from onboard sensors (Figure 2 202 "access sensor data that provides information about a road ahead of an autonomous vehicle"; Figure 3 346 shows the sensor are on the vehicle);
determining, by the vehicle, a vehicle path based on the received data and the instructions (Figure 2 216 "determine a proposed trajectory according to the determined hand signal interpretation"; see also Figure 2 218-220 wherein an object is detected and an additional waiting step is added before navigating according to the proposed trajectory); and
maneuvering the vehicle based on the vehicle path (Figure 2 222 "navigate the autonomous vehicle according to the proposed trajectory").
Gupta does not teach receiving instructions from virtual devices.
Ghaffar teaches virtual devices (Abstract discloses traffic police robots that direct traffic like an ordinary police officer with gestures as shown in Figure 7).
It would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have modified Gupta to incorporate the teachings of Ghaffar such that human traffic controllers of Gupta can be replace with the virtual devices of Ghaffar such that the method of recognizing traffic controlling gestures of any traffic controller and controlling a vehicle thereto as detailed in Gupta can be utilized by interpreting the gestures of the robot of Ghaffar. This modification would be made with a reasonable expectation of success to reduce stress caused by a high number of hours worked by police officers directing traffic and reduce risk of accidents caused by human officers as disclosed in Ghaffar (Abstract).
Gupta does not teach validating that the virtual devices are authorized for use.
Huang teaches validating that the virtual devices are authorized for use (Abstract discloses verifying that a user is authorized to operate a motion based robot).
It would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have further modified Gupta to incorporate the teachings of Huang such that detected traffic controllers as taught by Gupta as modified by Ghaffar can be validated according to their motion behaviors. This modification would be made with a reasonable expectation of success to prevent impersonation attacks as disclosed in Huang (Abstract).
Regarding claims 2, 9, and 16; Gupta teaches all of claims 1, 8, and 15 as detailed above. Gupta further teaches that the vehicle path comprises a new path for the vehicle to travel instead of an initial path by following the instructions (Figure 2 222 "navigate the autonomous vehicle according to the proposed trajectory"; see also Figure 1 where vehicle 302 changes from an initial traveling lane to a new traveling lane based on hand signal determination).
Regarding claims 3, 10, and 17; Gupta teaches all of claims 1, 8, and 15 as detailed above.
Gupta does not teach that the virtual devices are remotely controlled by virtual users and the instructions are displayed on the virtual devices as a series of hand gestures.
Ghaffar further teaches that the virtual devices are remotely controlled by virtual users (section I paragraph 5 discloses robots can utilize a "wizard of oz" method where the robots are remotely controlled) and the instructions are displayed on the virtual devices as a series of hand gestures (Figure 7 shows a plurality of hand gestures that a traffic controlling robot can make).
It would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have further modified Gupta to incorporate the further teachings of Ghaffar such that human traffic controllers of Gupta can be replace with the remotely controlled virtual devices of Ghaffar such that the method of recognizing traffic controlling gestures of any traffic controller and controlling a vehicle thereto as detailed in Gupta can be utilized by interpreting the gestures of the robot of Ghaffar. This modification would be made with a reasonable expectation of success to reduce stress caused by a high number of hours worked by police officers directing traffic and reduce risk of accidents caused by human officers as disclosed in Gupta (Abstract).
Regarding claims 4, 11, and 18; Gupta teaches all of claims 1, 8, and 15 as detailed above. Gupta further teaches that the instructions consist of traffic instructions (Figure 2 210 ensures that a hand signal indicates traffic instructions such that steps 212-222 are only provided when hand gesture instructions consist of traffic instructions).
Regarding claims 5, 12 and 19; Gupta teaches all of claims 1, 8, and 15 as detailed above. Gupta further teaches that the onboard sensors are comprised of radar (paragraph 0030 "radar sensor"), sonar (paragraph 0030 "ultrasonic sensor system"), camera (paragraph 0030 "video camera" and "infrared camera"), microphone (paragraph 0030 "microphone array") and GPS (paragraph 0102 "Global Positioning System (GPS) transceiver").
Regarding claims 7, 14, and 20; Gupta teaches all of claims 3, 10, and 17 as detailed above. Gupta further teaches identifying the hand gestures based on the model; and determining traffic instructions based on the identified hand gestures (paragraph 0007 "The disclosed system may determine the interpretation of the hand signal using a hand signal detection machine learning module that is pre-trained to predict interpretations of various hand signals from sensor data"; see also paragraph 0025).
Claim(s) 6 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gupta, Ghaffar, and Huang as applied to claims 1 and 8 above, and further in view of Peng et al. CN 108860643 A (hereinafter Peng; a translated copy has been provided which the examiner relies upon).
Regarding claims 6 and 13, Gupta teaches all of claims 1 and 8 as detailed above.
Gupta does not teach receiving a digital identity of a virtual user that is authorized to use the virtual devices
Huang further teaches receiving a digital identity of a virtual user that is authorized to use the virtual devices (Abstract discloses verifying that a user is authorized to operate a motion based robot by analyzing the user's motion behavior compared to a behavior profile; examiner considers the user’s motion behavior equivalent to a "digital identity").
It would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have further modified Gupta to incorporate the further teachings of Huang such that detected traffic controllers of Gupta as modified by Ghaffar can be validated according to their motion behaviors. This modification would be made with a reasonable expectation of success to prevent impersonation attacks as disclosed in Huang (Abstract).
Gupta does not teach cross referencing a vehicle database to make sure the vehicle can accept the instructions from the virtual devices.
Peng teaches cross referencing a vehicle database to make sure the vehicle can accept the instructions from the virtual devices (translated paragraphs 0063-0064 discloses a vehicle obtains environmental information, including gestures made in attempt to move or relocate a vehicle, wherein this information is compared to a database to verify if the vehicle can be moved by the command or not).
It would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have further modified Gupta to incorporate the teachings of Peng such that when a command is received according to Gupta, a vehicle can cross reference the command to a database to validate the command to make sure the vehicle can perform the command as taught by Peng. This modification would be made with a reasonable expectation of success to prevent following malicious, incorrect, dangerous, or disingenuous instructions by performing validation beforehand to make sure the instruction can be followed/accepted.
Response to Amendment
Claim amendments filed 1/23/2026 have been received and fully considered and overcome the claim 6 and claim 13 objections and 112(b) rejections of record detailed in the Office Action dated 10/28/2026. These/this objections and rejections have/has been withdrawn. Examiner notes that in remarks filed 1/23/2026, see page 11, applicant points out that claims 1 and 5 were all amended to overcome the objections of record, however, the claim amendments do not reflect this alleged correction. Therefore, the objections are maintained.
Specification, drawing, and abstract amendments filed 1/23/2026 have been received and fully considered and overcome the specification, drawing, and abstract objections of record detailed in the Office Action dated 10/28/25. These/this objections have/has been withdrawn.
Response to Arguments
Applicant's arguments, see pages 12-15, filed 1/23/2026 have been fully considered but they are not persuasive.
On pages 12-14, applicant claims that the approach being a computer program product implemented by a computer for training a vehicle to accept hand gestures implements the abstract idea into a practical application. The recitation of an abstract idea applied to a computer does not prohibit the idea from being performed mentally as detailed in MPEP 2106.04(a)(2)(III)(C) and the court cases cited therein. Furthermore, the training steps are generically recited such that they are further generically linked “apply it” steps. More detailed training steps would be required to be significantly more than the abstract idea. As recited, any and all methods of training the vehicle are acceptable hence the abstract idea is merely generically recited as being applied by a trained vehicle and further generically linked to machine learning.
On pages 14-15, applicant argues that the recitation of “autonomous vehicle” is sufficient to incorporate the abstract idea into a practical application. Since an autonomous vehicle is only required to have an autonomous operating mode (see Claim Interpretation above) and is not clearly recited in the claim as operating in the autonomous mode to perform the maneuvering step (see amended 101 rejection above), this is not sufficient. Examiner recommends amending “maneuvering” to “autonomously maneuvering” as previously discussed in the interview performed on 1/21/2026 to adequately overcome the 101 rejection using the applicant’s rationale.
On page 15, applicant further argues the generically recited training as being an implementation into a practical application. As recited above, this is generically recited and not sufficient. Further detail would be required.
On page 15, applicant further argues that the claimed invention is an improvement without any further evidence. An argument for improvement without supporting evidence cannot be considered as persuasive.
On page 15, applicant further argues that the claim amendments overcome the 101 rejection. As the previous arguments were mostly directed towards the amended claims regardless, the rebuttals above still apply. Therefore, the 101 rejection is maintained.
Applicant’s arguments, see pages 16-17, filed 1/23/2026, with respect to the rejection(s) of claim(s) 1, 8, and 15 under 103 have been fully considered and are persuasive. Applicant further argues that the model training, validating, and deployment steps are not taught within the prior art of record without any supporting evidence thereto. As these limitations were previously rejected with art in the Office Action dated 10/28/2025 and applicant does not provide evidence as to why these limitations are not taught in the previously relied upon prior art, examiner does not consider this portion of the argument persuasive. Regardless, the 103 of 10/28/ has been withdrawn due to the amended “validating that the virtual devices are authorized for use” step. However, upon further consideration, a new ground(s) of rejection is made in view of Gupta in view of Ghaffar and Huang.
Documents Considered but not Relied Upon
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
"Access Control to Robotic Systems Based on Biometric: The Generalized Model and its Practical Implementation" by Abu-Jassar et al. discloses performing a biometric and password authentication of a robot user to ensure the user is authorized to control the robot.
"Robotic Vehicle Control by Hand Gestures of Authorized Users" by Divya et al. discloses performing facial recognition to validate if a user is authorized to control a robot.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 Ashley Tiffany Schoech whose telephone number is (571)272-2937. The examiner can normally be reached 4:45 am - 3:15 pm PT Monday - Thursday.
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/A.T.S./Examiner, Art Unit 3669
/Erin M Piateski/Supervisory Patent Examiner, Art Unit 3669
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