DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This office action is in response to applicant’s arguments/remarks and amendments filed on 06/29/2026. Claims 1, 3-5, and 10-15 have been amended. Claims 2, 8-9, and 16-18 have been cancelled. Claims 21-22 have been newly added. Accordingly, claims 1, 3-7, 10-15, and 19-22 are currently pending.
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.
Claim 5 is 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.
Claim 5 recites the limitation "the information processing device" in line 2. There is insufficient antecedent basis for this limitation in the claim.
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, 4-7, and 19-21 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Suzuki et al US 2023/0045416 A1 (hence Suzuki).
In re claims 1, 19, and 20, Suzuki discloses an information processing device, an information processing method, and an information processing program that generates basis information indicating a basis for an output of the model after the input information is input to the model based on state information indicating a state of the model after the input of the input information to the model (Abstract) and teaches the following:
An information processing device comprising a memory and a first processor (Abstract) configured to:
acquire a plurality of pieces of information related to a vehicle (Fig.3, #141, and Paragraph 0046 “an image sensor 141”);
infer a plurality of index values from the plurality of pieces of information (Paragraphs 0047-0048 “The moving body device 100 performs the recognition process based on the image IM1 captured by the image sensor 141”, “the model M1 outputs information indicating a type (class) of an object included in an image and information indicating a position (region) thereof in response to the input of the image”, and “the model M1 is a multilayer neural network, and has a structure such as a deep neural network of four or more layers, a so-called deep neural network (deep learning)”) using deep learning through multivariate analysis according to an integral method (Paragraph 0048 “the model M1 is a multilayer neural network, and has a structure such as a deep neural network of four or more layers, a so-called deep neural network (deep learning)”, Fig.6, and Paragraphs 0163-0164);
and execute driving control of the vehicle on the basis of the plurality of index values (Paragraph 0062 “the moving body device 100 controls the automatic driving based on the action plan information indicating the route PP11”)
In re claim 4, Suzuki teaches the following:
set a travel strategy until the vehicle reaches a destination, wherein the travel strategy includes at least one theoretical value of an optimal route to the destination, a driving speed, a tilt, or braking, update the travel strategy on the basis of a difference between the plurality of index values and the theoretical value (Paragraph 0251 “the route planning unit 261 sets a route from a current position to a designated destination based on a global map”, and “the route planning unit 261 appropriately changes the route based on a situation such as congestion, an accident, a traffic restriction, and construction, a physical condition of the driver, and the like”)
In re claim 5, Suzuki teaches the following:
wherein the information processing device includes at least one of: a vehicle lower sensor that is provided in a lower portion of the vehicle and is capable of detecting a temperature, a material, and a tilt of a traveling ground; a temperature sensor capable of detecting a temperature of a ground on which the vehicle travels; a material sensor capable of detecting a material of the ground; or an inclination sensor capable of detecting an inclination of the ground (Paragraph 0065 “sensor information such as a speed, an acceleration, an ambient outside temperature, a road surface situation (wetting by rain, freezing, or the like) of the moving body device 100”)
In re claim 6, Suzuki teaches the following:
wherein the plurality of index values include a first index value related to a first distance including a required stop distance required for the vehicle to stop without colliding with an obstacle in a traveling direction of the vehicle between the obstacle and the vehicle (Paragraphs 0127 “a distance measuring sensor”, 0158 “a distance between an object to be measured and the distance measuring sensor”, and 0238 “an emergency avoidance unit 271 of the operation control unit 235”), the driving control includes traveling speed control, and the traveling speed control is control of a traveling speed of the vehicle, and is executed on the basis of the first index value (Paragraph 0236 “constant speed travel”)
In re claim 7, Suzuki teaches the following:
wherein the traveling speed control includes control for causing the vehicle to travel at a maximum speed at which the vehicle does not collide with the obstacle, and information regarding the maximum speed is calculated on the basis of the first index value (Paragraphs 0062 “the moving body device 100 plans a route PP11 to proceed to the right side of the proceeding direction in order to avoid a collision with the object OB11 located on the left side of the proceeding direction” and 0139)
In re claim 21, Suzuki teaches the following:
wherein the plurality of pieces of information comprises information on at least one of: an air resistance, a road resistance, a road material, or a slip coefficient of a traveling environment of the vehicle (Paragraph 0065 “it is also possible to provide various types of information recorded by the sensor unit 14, for example, sensor information such as a speed, an acceleration, an ambient outside temperature, a road surface situation (wetting by rain, freezing, or the like) of the moving body device 100”)
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) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Suzuki.
In re claim 3, Suzuki discloses the claimed invention as recited above including a deep neural network of four or more layers, a so-called deep neural network (deep learning) (Paragraph 0048) but doesn’t explicitly teach the following:
wherein the first processor is further configured to acquire the plurality of pieces of information in units of nanoseconds, and execute inference of the plurality of index values and driving control of the vehicle in units of nanoseconds by using the plurality of pieces of information acquired in units of nanoseconds
It would have been obvious to one having ordinary skill in the art at the time the invention was made to push deep learning inference speed into nanoseconds regime since nanosecond-level measurements are increasingly common in high-performance and specialized deep learning AI, and it has been held that discovering an optimum value of a result effective variable involves only routine skill in the art. In re Boesch, 617 F.2d 272,265 USPQ 215 (CCPA 1980).
Claim(s) 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Suzuki in view of Guan et al US 2021/0011961 A1 (hence Guan).
In re claim 22, Suzuki discloses the claimed invention as recited above but doesn’t explicitly teach the following:
wherein the integral method comprises obtaining an integral value by time-integrating a delta value of a function representing a behavior of each parameter of a plurality of physical parameters corresponding to the plurality of pieces of information
Nevertheless, Guan discloses an operations service platform that, in real-time, detects and monitors trends, topics, and data sources, and based on that information, provides recommendations in support of content management activities (Abstract and Paragraph 0002) and teaches the following:
wherein the integral method comprises obtaining an integral value by time-integrating a delta value of a function representing a behavior of each parameter of a plurality of physical parameters corresponding to the plurality of pieces of information (Paragraph 0011)
It would have been obvious to one having ordinary skills in the art at the time the invention was filed to have modified the Suzuki reference to include integrating real-time trend surveillance using statistical keyword-based scoring and machine-learning topic modeling classification algorithms that present content reviewers with information and trends useful to handling content monitoring and decisioning in their assigned content backlogs, as taught by Guan, with a reasonable expectation of success, in order for advising content reviewers during content managing activities, and for managing and updating recommendations for the content reviewers (Guan, Paragraph 0002).
Allowable Subject Matter
Claims 10-15 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Response to Arguments
Applicant's arguments filed on 06/29/2026 have been fully considered but they are not persuasive.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., the integral method comprises obtaining an integral value by time-integrating a delta value of a function representing a behavior of each parameter of a plurality of physical parameters corresponding to the plurality of pieces of information, wherein the plurality of pieces of information comprises information on at least one of: an air resistance, a road resistance, a road material, or a slip coefficient of a traveling environment of the vehicle), as disclosed in Paragraphs 0035-0041 are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). The limitation using deep learning through multivariate analysis according to an integral method, as disclosed in claim 1, is recited at a high level of generality, and using a deep neural network of four or more layers to outputs information indicating an object included in an image and a position thereof in response to the input of the image, as recited in Paragraphs 0047-0048 would read on it. If applicant wants the examiner to interpret said limitation in view of Paragraphs 0035-0041, the examiner recommends changing it to “infer a plurality of index values from the plurality of pieces of information using deep learning through multivariate analysis according to an integral method, wherein the integral method comprises obtaining an integral value by time-integrating a delta value of a function representing a behavior of each parameter of a plurality of physical parameters corresponding to the plurality of pieces of information, and wherein the plurality of pieces of information comprises information on at least one of: an air resistance, a road resistance, a road material, or a slip coefficient of a traveling environment of the vehicle”.
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 RAMI KHATIB whose telephone number is (571)270-1165. The examiner can normally be reached M-F: 9:00am-5:30pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Erin M Piateski can be reached at 571-270 7429. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RAMI KHATIB/Primary Examiner, Art Unit 3669
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