DETAILED ACTION
This is a response to applicant’s submissions filed on 9/3/2025. Claims 1-5, 7-14 and 16-19 are pending.
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 .
Response to Arguments
Applicant’s arguments filed on 9/3/2025 regarding rejections under 35 U.S.C. § 102 and 35 U.S.C. § 103 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Applicant's arguments filed on 9/3/2025 regarding rejections under 35 U.S.C. § 101 have been fully considered but they are not persuasive.
In response to applicant’s argument that contamination to AV components, damage to AV components, and malfunctions of AV components cannot be fully appreciated or assessed through a mere mental process (applicant’s remarks; p. 13), the examiner respectfully disagrees. Paragraph 72 discloses the AV components include the vehicle body, windshield, lights, doors, etc. A person can mentally identify that a vehicle is dirty, dented, or has nonfunctioning lights. See rejection below.
In response to applicant’s argument that a human being cannot mentally perform a comparison of a million-point LIDAR scan against a stored digital twin to detect a new chassis deformation or mentally process high-frequency sensor data to identify a newly obstructed sensor (applicant’s remarks; p. 13), the examiner respectfully disagrees. The claims do not require LIDAR data, a stored digital twin, or high-frequency sensor data. Under their broadest reasonable interpretation, independent claims 1, 11 and 17 include the abstract idea of a person identifying a new dent in a vehicle by comparing two images. Further, as shown in the image below from page 4 of the research paper titled “3D point cloud analysis for detection and characterization of defects on airplane exterior surface”, a person is able to visually identify defects in a LIDAR point cloud and could therefore compare LIDAR scans for degradations. See rejection below.
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In response to applicant’s argument that the specific step of comparing sensor data from the one or more sensors of the first vehicle that captures an appearance of the second vehicle to a reference state is a concrete technological process that improves computer-controlled vehicle operation (applicant’s remarks; pp. 14-15), the examiner respectfully disagrees. Comparing sensor data is generically recited, is a well-understood, routine, and conventional computer function, and, as discussed above, can be performed in the human mind. See rejection below.
In response to applicant’s argument that detecting damage is a computationally intensive task involving the processing of sensor data to identify anomalies compared to a baseline that goes far beyond a generic computer function (applicant’s remarks; p. 15), the examiner respectfully disagrees. The claims are not limited to detecting damage, but merely identifying degradations by comparing appearance data, such as two vehicle images. Paragraphs 72-73 disclose identifying a degradation could be as simple as identifying a contaminant on a vehicle body by comparing its currently detected color to its known color. Comparing sensor data is generically recited, is a well-understood, routine, and conventional computer function, and, as discussed above, can be performed in the human mind. See rejection below.
In response to applicant’s argument that the claimed invention integrates a judicial exception into a practical application by detecting damage in real-time so the claimed invention can immediately take action, such as transmitting the information to the online system to recover the degraded AV or dispatch another AV to complete a task assigned to the degraded AV (applicant’s remarks; pp. 14-15), the examiner respectfully disagrees. The claims do not require real-time operation. Further, transmitting information to an online system is generically recited and amounts to merely transmitting data over a network which is recognized as a well‐understood, routine, and conventional computer function (see MPEP § 2106.05(d)(II)). See rejection below.
Drawings
The amendments to the drawings were received on 9/3/2025.
Specification
The amendments to the specification were received on 9/3/2025.
Claim Objections
Claims 5, 17 and 19 are objected to because of the following informalities:
In claims 5 and 19, line 7, “the fleet of vehicle” should read “the fleet of vehicles”. This appears to be a typographical error.
In claim 17, line 4, the second colon of the sentence should be removed, because using multiple colons in a single sentence to form nested lists is grammatically incorrect, which makes it confusing to determine the relationships between limitations.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 7-9 and 16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 7, line 3, the limitation “receiving information indicating the reference state” renders the claim indefinite because it is unclear how the information indicating the reference state is different from the reference state recited in claim 1, lines 10-11. Paragraph 121 discloses the information indicating the reference state of the second vehicle comprises information of a travelling route of the second vehicle, however, it is unclear how the degradation of claim 1 would be determined by comparing the appearance of the second vehicle to travelling route information. Paragraph 73 discloses additional data indicating one or more reference states of the peer AV includes specifications of the peer AV such as color, design, components, etc. Although no relationship is disclosed between the additional data indicating one or more reference states and the information of the reference state, for the purposes of examination, it will be assumed that they are the same data/information.
Regarding claim 8, line 3, the limitation “retrieving information of the reference state” renders the claim indefinite because it is unclear how the information of the reference state is different from the reference state recited in claim 1, lines 10-11. Paragraph 121 discloses the information indicating the reference state of the second vehicle comprises information of a travelling route of the second vehicle, however, it is unclear how the degradation of claim 1 would be determined by comparing the appearance of the second vehicle to travelling route information. Paragraph 73 discloses additional data indicating one or more reference states of the peer AV includes specifications of the peer AV such as color, design, components, etc. Although no relationship is disclosed between the additional data indicating one or more reference states and the information of the reference state, for the purposes of examination, it will be assumed that they are the same data/information.
Regarding claim 9, line 3, the limitation “the information indicating the reference state of the second vehicle” lacks sufficient antecedent basis rendering the claim indefinite. For the purposes of examination, it will be assumed that claim 9 is dependent on claim 7.
Regarding claim 16, lines 4 and 6, the limitations “receiving information indicating the reference state” and “retrieving information of the reference state” render the claim indefinite because it is unclear how the information of the reference state is different from the reference state recited in claim 11, lines 11-12. Paragraph 121 discloses the information indicating the reference state of the second vehicle comprises information of a travelling route of the second vehicle, however, it is unclear how the degradation of claim 1 would be determined by comparing the appearance of the second vehicle to travelling route information. Paragraph 73 discloses additional data indicating one or more reference states of the peer AV includes specifications of the peer AV such as color, design, components, etc. Although no relationship is disclosed between the additional data indicating one or more reference states and the information of the reference state, for the purposes of examination, it will be assumed that they are the same data/information.
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.
The determination of whether a claim recites patent ineligible subject matter is a two-step inquiry.
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), see MPEP § 2106.03, or
STEP 2: the claim recites a judicial exception, e.g., an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis: see MPEP § 2106.04
STEP 2A (PRONG ONE): Does the claim recite an abstract idea, law of nature, or natural phenomenon? see MPEP § 2106.04(II)(A)(1)
STEP 2A (PRONG TWO): Does the claim recite additional elements that integrate the judicial exception into a practical application? see MPEP § 2106.04(II)(A)(2)
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? see MPEP § 2106.05
Claims 1-5, 7-14 and 16-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
Claim 17 is directed to a computer system (i.e., a machine). Therefore, claim 17 is within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong One
Regarding Prong One of the Step 2A analysis, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes. see MPEP § 2106(A)(II)(1) and MPEP § 2106.04(a)-(c)
Independent claim 17 includes limitations that recite an abstract idea (emphasized below [with the category of abstract idea in brackets]) and will be used as a representative claim for the remainder of the analysis. Claim 17 recites:
A computer system, comprising:
a computer processor for executing computer program instructions;
and one or more non-transitory computer-readable media storing computer program instructions executable by the computer processor to perform operations comprising:
detecting, by a first vehicle, a second vehicle based on one or more sensors of the first vehicle,
determining whether the second vehicle is in a fleet of vehicles that includes the first vehicle [mental process/step],
after determining that the second vehicle is in the fleet of vehicles, detecting, by the first vehicle, whether there is a degradation in a state of the second vehicle, wherein the degradation is at least one of a physical damage, a sensor contamination, or a malfunction of a component of the second vehicle, and wherein detecting the degradation comprises comparing sensor data from the one or more sensors of the first vehicle that captures an appearance of the second vehicle to a reference state of the second vehicle [mental process/step], and
after detecting degradation in the state of the second vehicle, transmitting, by the first vehicle, information of the degradation in the state of the second vehicle to an online system managing the fleet of vehicles, the online system configured to address the degradation in the state of the second vehicle.
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, “determining whether the second vehicle is in a fleet of vehicles…” and “…detecting … whether there is a degradation…” in the context of this claim encompasses a person looking at collected data and forming a simple judgement. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong Two
Regarding Prong Two of the Step 2A analysis, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. see MPEP § 2106.04(II)(A)(2) and MPEP § 2106.04(d)(2). It must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” [with a description of the additional limitations in brackets], while the bolded portions continue to represent the “abstract idea”):
A computer system, comprising:
a computer processor for executing computer program instructions [generic computing component]; and
one or more non-transitory computer-readable media storing computer program instructions executable by the computer processor to perform operations [applying the abstract idea using generic computing components] comprising:
detecting, by a first vehicle, a second vehicle based on one or more sensors of the first vehicle [pre-solution activity (data gathering) using generic sensors],
determining whether the second vehicle is in a fleet of vehicles that includes the first vehicle,
after determining that the second vehicle is in the fleet of vehicles, detecting, by the first vehicle, whether there is a degradation in a state of the second vehicle, wherein the degradation is at least one of a physical damage, a sensor contamination, or a malfunction of a component of the second vehicle, and wherein detecting the degradation comprises comparing sensor data from the one or more sensors of the first vehicle that captures an appearance of the second vehicle to a reference state of the second vehicle, and
after detecting degradation in the state of the second vehicle, transmitting, by the first vehicle, information of the degradation in the state of the second vehicle to an online system managing the fleet of vehicles, the online system configured to address the degradation in the state of the second vehicle [insignificant post-solution activity (transmitting data)].
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitation(s) of “detecting … a second vehicle…” and “…transmitting … information…”, the examiner submits that the limitation(s) is/are insignificant extra-solution activities that merely use a computer (onboard computer of first vehicle) to perform the process. In particular, the detecting a second vehicle step is recited at a high level of generality (i.e., as a general means of gathering data on a nearby vehicle for use in the subsequent determining and detecting steps), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. The transmitting step is also recited at a high level of generality (i.e., as a general means of sending data to the fleet management system), and amounts to mere data transmitting, which is a form of insignificant extra-solution activity. The “computer processor”, “non-transitory computer-readable media”, and “first vehicle” is/are also recited at a high level of generality (a person of ordinary skill in the art will recognize that the first vehicle comprises generic computer components performing the generic computer function(s) of comparing data) such that it amounts to no more than mere instructions to apply the exception using a generic computer component.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception. see MPEP § 2106.05. Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the Revised Guidance, representative independent claim 17 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a first vehicle, computer processor, and computer-readable media to perform the “determining whether the second vehicle is in a fleet of vehicles…” and “…detecting … whether there is a degradation…” amounts to nothing more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Also discussed above with respect to integration of the abstract idea into a practical application, the examiner submits that the additional limitation(s) of “detecting … a second vehicle…” and “…transmitting … information…” is/are insignificant extra-solution activities. Hence, the claim is not patent eligible.
Claim(s) 1 and 11 is/are substantially the same subject matter as claim 17 except drawn to a method and one or more non-transitory computer-readable media (i.e., a process and machine, respectively) which falls under one of the statutory categories in step 1. Therefore, claim(s) 1 and 11 is/are rejected under step 2 for the same reasons above.
Dependent claim(s) 2-5, 7-10, 12-14, 16 and 18-19 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of the dependent claims are directed toward additional aspects of the judicial exception. Therefore, dependent claims 2-5, 7-10, 12-14, 16 and 18-19 are not patent eligible under the same rationale as provided for in the rejection of claim 17.
Therefore, claims 1-5, 7-14 and 16-19 is/are ineligible under 35 U.S.C 101.
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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 8, 10-11 and 16-17 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Veschikov et al. (US 2024/0395083), hereinafter Veschikov.
Regarding claims 1, 11 and 17, Veschikov discloses a computer system, comprising: a computer processor for executing computer program instructions (Veschikov; para. 30: one or more processors 52 may include any hardware device capable of executing instructions); and one or more non-transitory computer-readable media storing computer program instructions executable by the computer processor (Veschikov; para. 30: instructions may be stored in memory 56; para. 32: Memory 56 may include volatile memory such as static random-access memory (SRAM) or dynamic RAM (DRAM), or may include non-volatile memory such as flash memory, or other volatile or non-volatile memory.) to perform operations comprising: detecting, by a first vehicle, a second vehicle based on one or more sensors of the first vehicle, determining whether the second vehicle is in a fleet of vehicles that includes the first vehicle (Veschikov; para. 22: the observer vehicle, at block 41, determines if another vehicle is within sensor range and includes cooperative detection. For example, the observer vehicle may be vehicle 12 in FIG. 1. The determination may be made by using onboard sensors to detect and ID the other vehicle, which may be, e.g., vehicle 13; para. 12: Vehicles 12, 13, and 14 may be part of fleet of vehicles equipped for cooperative malfunction detection; para. 23: The presence of cooperative malfunction detection functionality in a vehicle may be visible to other vehicles either by special markers on the car itself or in broadcasted messages from the cars.), after determining that the second vehicle is in the fleet of vehicles, detecting, by the first vehicle, whether there is a degradation in a state of the second vehicle (Veschikov; para. 22: data is captured of the observed vehicle using onboard sensors, such as cameras and radar. At block 43, after data is captured, a malfunction detection algorithm is run on the captured data and a report is made of the findings of the malfunction detection algorithm), wherein the degradation is at least one of a physical damage, a sensor contamination, or a malfunction of a component of the second vehicle (Veschikov; para. 27: Many different issues can be detected by simple external monitoring of a car while it drives. Here is a list of some simple examples: detection of an external light that is brighter or dimmer than the other light; one of the external lights does not turn on when expected; smoke coming from the vehicle, e.g., from the exhaust pipe; wheels that wobble due to incorrectly balanced tires, incorrect inflation pressure, or loose or missing lug nuts; a car is leaning to one side due to, e.g., a broken shock absorber; liquid leaking from the car; overheating portions of the car detected using infra-red sensors; strong vibrations of some parts of the vehicle detected using radar, lidar, or video analysis; the exhaust pipes from the engine coming loose; and the license plate is unreadable because it is missing or dirty.), and wherein detecting the degradation comprises comparing sensor data from the one or more sensors of the first vehicle that captures an appearance of the second vehicle to a reference state of the second vehicle (Veschikov; para. 14: Each algorithm is tailored to analyze one or several specific features of a moving vehicle based on sensor data and generate reports if issues are detected. For example, a ML algorithm may be trained to know what a faulty headlight or tail light looks like.), and after detecting degradation in the state of the second vehicle, transmitting, by the first vehicle, information of the degradation in the state of the second vehicle to an online system managing the fleet of vehicles, the online system configured to address the degradation in the state of the second vehicle (Veschikov; para. 34: Transceiver 53 may transmit the reports using a transmitter (TX) and sensor information from the vehicle when it is performing an observer vehicle role … Transceiver 53 may also include a cellular transceiver for communicating with infrastructure in order to relay communications with another vehicle or with, for example, a car maintenance facility via the internet.; para. 25: sensor data from an infrared sensor indicates one portion of a car is slightly overheating. To acquire more understanding of the potential malfunction, sensor data related to the observation can be sent to an automobile maintenance facility or car dealership for further investigation).
Regarding claim 8, as best understood, Veschikov discloses detecting whether there is any degradation in the state of the second vehicle further comprises: retrieving information of the reference state of the second vehicle from a memory of the first vehicle (Veschikov; para. 30: Programs in cooperative malfunction detection circuit 54 may include machine learning algorithms that are trained to receive sensor inputs and generate a malfunction detection report. The malfunction detection report may be generated by ML algorithms running on a data processing system 50 on an observer vehicle); and determining the reference state of the second vehicle based on the information (Veschikov; para. 14: Each algorithm is tailored to analyze one or several specific features of a moving vehicle based on sensor data and generate reports if issues are detected. For example, a ML algorithm may be trained to know what a faulty headlight or tail light looks like.).
Regarding claim 10, Veschikov discloses the online system is configured to send a message (Veschikov; para. 34: Transceiver 53 may transmit the reports using a transmitter (TX) and sensor information from the vehicle when it is performing an observer vehicle role … Transceiver 53 may also include a cellular transceiver for communicating with infrastructure in order to relay communications with another vehicle) to a client device associated with a passenger of the second vehicle based on the degradation in the state of the second vehicle (Veschikov; para. 19: The driver can be alerted of the detected malfunction by displaying a message on the information display screen on the dash.).
Regarding claim 16, as best understood, Veschikov discloses detecting whether there is any degradation in the state of the second vehicle further comprises: receiving information indicating the reference state of the second vehicle from the online system; or retrieving information of the reference state of the second vehicle from a memory of the first vehicle (Veschikov; para. 30: Programs in cooperative malfunction detection circuit 54 may include machine learning algorithms that are trained to receive sensor inputs and generate a malfunction detection report. The malfunction detection report may be generated by ML algorithms running on a data processing system 50 on an observer vehicle; Veschikov; para. 14: Each algorithm is tailored to analyze one or several specific features of a moving vehicle based on sensor data and generate reports if issues are detected. For example, a ML algorithm may be trained to know what a faulty headlight or tail light looks like.).
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) 2-4, 12-13 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Veschikov in view of Vilnai (US 2015/0242855).
Regarding claims 2-3, 12-13 and 18, Veschikov discloses determining whether the second vehicle is in the fleet of vehicles comprises: inputting the sensor data from the one or more sensors into a machine learning model (Veschikov; para. 30: cooperative malfunction detection circuit 54 may include machine learning algorithms that are trained to receive sensor inputs).
Veschikov does not explicitly disclose the machine learning model outputting a determination whether the second vehicle is in the fleet of vehicles; determining whether a confidence of the training machine learning model for the determination is lower than a threshold; in response to determining that the confidence is lower than the threshold, sending, to the online system, a request for determining whether the second vehicle is in the fleet of vehicles; and determining whether the second vehicle is in the fleet of vehicles based on a response from the online system.
Vilnai, in a reasonably pertinent field of endeavor (smart fuel pumps), discloses a machine learning model outputting a determination whether a vehicle is in a fleet of vehicles (Vilnai; para. 288: Provided the aforesaid score of comparative analysis determined at step 564 exceeds a general predefined threshold for transaction or a specific threshold set for the particular vehicle registered to the service of automated purchase authorization of fuel transaction, authenticator 525 typically authenticates the transaction at step 570 and commands the control of fuel pump 535 to dispense the fuel. Upon authenticating the transaction at step 570, the image obtained by imaging device 502 and preselected at step 556 is preferably added to image database 515 at step 580 as a true positive reference, for identification of the particular vehicle registered to the service of automated purchase having the fuel nozzle inserted into the fuel inlet thereof, in authorization of any future fuel transactions; thereby extending the variability of the reference base for identification of the particular vehicle and enhancing the probability of true positive identifications in the future, by automatically performing accumulative machine learning over time.); determining whether a confidence of the training machine learning model for the determination is lower than a threshold (Vilnai; para. 287: Threshold configurator 520 thereafter determines at step 564 whether the aforesaid score of comparative analysis exceeds a general predefined threshold for transaction or a specific threshold set for the particular vehicle registered to the service of automated purchase authorization of fuel transaction.); in response to determining that the confidence is lower than the threshold, sending, to an online system, a request for determining whether the vehicle is in the fleet of vehicles (Vilnai; para. 289: If however the aforesaid score of comparative analysis determined at step 564 does not exceed a general predefined threshold for transaction or a specific threshold set for the particular vehicle registered to the service of automated purchase authorization of fuel transaction, authenticator 525 preferably sends the image to GUI 552 at step 568 to be displayed to a human operator for a supervised approval/denial at step 572.); and determining whether the vehicle is in the fleet of vehicles based on a response from the online system (Vilnai; para. 289: Provided that aforesaid human operator approves the transaction at step 572, authenticator 525 typically authenticates the transaction at step 570 and commands the control of fuel pump 535 to dispense the fuel.).
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, with a reasonable expectation of success, to have modified the machine learning algorithms executed by the processor of Veschikov to determine that a nearby vehicle is registered to a fleet, or request a determination from a remote party when the comparative analysis score is low, as disclosed by Vilnai, to yield the predictable result of accurately determining if the nearby vehicle is eligible to receive the malfunction detection service.
Regarding claim 4, Veschikov, as modified, discloses the request comprises information of one or more features of the second vehicle that are captured by the first vehicle (Vilnai; para. 156: Optionally, the built-in computer located inside camera 102 and/or independent computer 130 comprises software to carry out picture and video analysis. Optionally, the software first identifies the vehicle via a unique vehicle identifier located on the vehicle and, if unsuccessful in locating a unique vehicle identifier, follows an order of priorities in attempting to identify the vehicle. The order of priorities, in descending order of priority may, for example, include unique vehicle identifier, license plate number, vehicle model number, vehicle shape and vehicle shape patterns.), and the online system is configured to determine an identity of the second vehicle based on the one or more features of the second vehicle (Vilnai; para. 289: authenticator 525 preferably sends the image to GUI 552 at step 568 to be displayed to a human operator for a supervised approval/denial at step 572).
Claim(s) 5, 7, 9, 14 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Veschikov in view of Kanopka et al. (US 2023/0095099), hereinafter Kanopka.
Regarding claims 5, 14 and 19, Veschikov discloses the invention substantially as claimed as described above.
Although Veschikov discloses vehicle-to-vehicle communication using various wireless protocols (Veschikov; para. 9) and visually determining a cryptographic public key of the observed vehicle (Veschikov; para. 15), it is unclear if Veschikov explicitly discloses determining whether the second vehicle is in the fleet of vehicles comprises: sending, by the first vehicle to the second vehicle, a request for establishing wireless communication, wherein the wireless communication is based on an encrypted communication protocol; and after the wireless communication is established, determining that the second vehicle is in the fleet of vehicle.
Kanopka, in the same field of endeavor (cooperative vehicle services), discloses determining whether a second vehicle is in a fleet of vehicles comprises: sending, by a first vehicle to the second vehicle, a request for establishing wireless communication, wherein the wireless communication is based on an encrypted communication protocol (Kanopka; para. 170: first vehicle 502a (here, the vehicle initiating the LoS communications link) emits an encrypted handshake to the friendly vehicle … the handshake procedure begins the process for setting up the vehicles for communication … the handshake procedure provides the first vehicle 502a with information about the second vehicle 502b, such as vehicle identification information and other information, which the first vehicle will transmit to the command center); and after the wireless communication is established, determining that the second vehicle is in the fleet of vehicle (Kanopka; para. 171: The first vehicle 502a can receive encrypted handshake information from the second vehicle 502b. The first vehicle 502a can send the encrypted handshake information associated with both the first vehicle 502a and the second vehicle 502b to the command center via network 112 for validation (724). The command center 540 can validate the handshake information (726). For example, if both vehicles are authorized to communicate with each other via the LoS communication link and the command center is authorized to communicate with both of the vehicles, then the command center 540 can validate the handshake.).
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, with a reasonable expectation of success, to determine that a nearby vehicle belongs to the same fleet of vehicles by sending an encrypted handshake, as disclosed by Kanopka, in the processor of Veschikov to yield the predictable result of accurately and securely determining if the nearby vehicle is eligible to receive the malfunction detection service.
Regarding claim 7, as best understood, Veschikov discloses the invention substantially as claimed as described above.
Veschikov does not explicitly disclose detecting whether there is any degradation in the state of the second vehicle further comprises: receiving information indicating the reference state of the second vehicle from the online system; and determining the reference state of the second vehicle based on the information.
Kanopka discloses detecting whether there is any degradation in a state of a vehicle comprises: receiving information indicating a reference state of the vehicle from an online system; and determining the reference state of the second vehicle based on the information (Kanopka; para. 222: receiving, using the radio communication system, information from the remote command center; para. 223: the information comprises one or more of information representing a trajectory associated with the first vehicle, information representing a user experience of a user in the first vehicle, information representing vehicle diagnostics of the first vehicle, information representing a state of the first vehicle, or caravan form factor information representing a position of one vehicle relative to another vehicle.).
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, with a reasonable expectation of success, to determine a trajectory and/or state of a nearby vehicle by receiving information from a remote command center, as disclosed by Kanopka, in the processor of Veschikov, to yield the predictable result of accurately identifying vehicle damage and/or malfunctions when external observations alone may be insufficient and/or ambiguous (e.g., see Veschikov; para. 28).
Regarding claim 9, Veschikov discloses the invention substantially as claimed as described above.
Veschikov does not explicitly disclose the state of the second vehicle comprises a location of the second vehicle, the information indicating the reference state of the second vehicle comprises information of a travelling route of the second vehicle, and detecting whether there is any degradation in the state of the second vehicle further comprises determining whether the second vehicle deviates from the travelling route based on the location of the second vehicle.
Kanopka discloses the state of a vehicle comprises a location of the vehicle, information indicating a reference state of the vehicle comprises information of a travelling route of the vehicle (Kanopka; para. 222: receiving, using the radio communication system, information from the remote command center; para. 223: the information comprises one or more of information representing a trajectory associated with the first vehicle, information representing a user experience of a user in the first vehicle, information representing vehicle diagnostics of the first vehicle, information representing a state of the first vehicle, or caravan form factor information representing a position of one vehicle relative to another vehicle.), and detecting whether there is any degradation in a state of the vehicle comprises determining whether the vehicle deviates from the travelling route based on the location of the second vehicle (Kanopka; para. 210: the first vehicle can detect that a second vehicle is moving out of a predetermined radius from the first vehicle [while traveling a shared route]).
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, with a reasonable expectation of success, to determine that a nearby vehicle has deviated from a shared travel route, as disclosed by Kanopka, in the processor of Veschikov, with the motivation of determining if the vehicles will follow the same path for enough time to perform the malfunction analysis and send a report, thereby enabling the vehicles to modify the amount of data they transmit based on how long they will be in communications range (Veschikov; para. 21).
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.
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/JOSEPH THOMPSON/Examiner, Art Unit 3665
/Erin D Bishop/Supervisory Patent Examiner, Art Unit 3665