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 action is in response to the amendments filed on 12/22/2025, in which claims 1-20 are pending and addressed below.
Response to Amendment
Applicant has amended the drawings to overcome the drawing objections. Accordingly, the drawing objections have been withdrawn.
Applicant has amended the specification to overcome the specification objections. Accordingly, the specification objections have been withdrawn.
Applicant has amended the claims to add sufficient structure. Accordingly, the claims are no longer subject to interpretation under 35 U.S.C. 112(f).
Applicant has amended the claims to overcome the 35 U.S.C. 101 rejections. Accordingly, the 35 U.S.C. 101 rejections have been withdrawn.
Response to Arguments
Applicant’s arguments with respect to claims 1-20 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.
Claim Rejections - 35 USC § 103
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-2, 9-12, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Hoshina et al., U.S. Patent Application Publication No. 2021/0197856 A1 (hereinafter Hoshina), in view of Kumavat et al., U.S. Patent Application Publication No. 2023/0192139 A1 (hereinafter Kumavat).
Regarding claim 1, Hoshina teaches an ego-machine comprising a plurality of processors (Hoshina Fig. 1) to:
generate a representation of one or more detected human features based at least on executing at least a portion of an operator or occupant monitoring system of the ego-machine on a first set of the plurality of processors (see at least Hoshina [0023]: “An image data acquiring unit 11 acquires, from the camera 2, image data indicating an image captured by the camera 2 (hereinafter, simply referred to as “captured image”). The image data acquiring unit 11 outputs the acquired image data to an image recognition unit 13.”; [0014]: “FIG. 7A is an explanatory diagram illustrating an example of a captured image and a face area. FIG. 7B is an explanatory diagram illustrating another example of a captured image and a face area. FIG. 7C is an explanatory diagram illustrating another example of a captured image and a face area. FIG. 7D is an explanatory diagram illustrating another example of a captured image and a face area.”);
generate a representation of one or more identified faults of the operator or occupant monitoring system based at least on executing one or more validity checks on the one or more detected human features on a second set of the plurality of processors (see at least Hoshina [0032]: “Next, the image recognition unit 13 executes a process of determining the success or failure of the detection. In a case where the detection is successful, the image recognition unit 13 executes the process of calculating the reliability R of the detection result, and executes the process of determining whether the reliability R is large or small. Hereinafter, these processes are collectively referred to as the “face area detecting process”. The threshold value setting unit 14 sets, before the face area detecting process is executed, a threshold value for the detection (hereinafter referred to as a “detection threshold value”) Th1, a threshold value for determination of success or failure (hereinafter referred to as a “success or failure determination threshold value”) Th2, and a threshold value to be compared with the reliability R (hereinafter referred to as a “reliability determination threshold value”) Th3.”);
and control, using the second set of the plurality of processors, one or more operations of the ego-machine based at least on representation of the one or more identified faults (see at least Hoshina [0114]: “In particular, even in a case where it is not determined whether or not the vehicle 1 is in the immediately-before-transition state, that is, in a case where it is unknown whether or not the vehicle 1 is in the immediately-before-transition state and it is unknown when the vehicle 1 will be switched from the autonomous driving mode to the manual driving mode, it is possible to assume that the vehicle 1 is in the immediately-before-transition state if the vehicle 1 is set to the autonomous driving mode, and to thereby prevent detection failures of an abnormal state. As a result, it is possible to switch from the autonomous driving mode to the manual driving mode at any time when the switching is required, thereby making it possible not to miss an abnormal state.”; [0099]: “Moreover, the autonomous driving control device 3 may switch the driving mode of the vehicle 1 by an operation input to an operation input device (not illustrated) in the vehicle 1. The operation input device includes, for example, a touch panel or a hardware switch.”; under broadest reasonable interpretation controlling operation includes switching a driving mode of an autonomous vehicle).
Hoshina fails to expressly disclose a second set of processors rated at a higher safety or reliability level than a first set of processors. However, Kumavat teaches
the second set being rated at a higher safety or reliability level than the first set (see at least Kumavat [0084]: “In a first variation (e.g., as shown in FIG. 4), a watchdog controller (e.g., safety-critical, ASIL D-rated ECU, automotive grade ECU, etc.) with high reliability and availability (e.g., reliable communication, minimal processing tasks, etc.) is implemented as a separate ECU relative to the other ECUs and functions to perform safety-critical functions such as fault monitoring, fault management, diagnostics, executing fallback actions (MRCs), and guaranteeing operation of the AV to a safe state.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the system disclosed by Hoshina with the higher safety or reliability level taught by Kumavat with reasonable expectation of success. Kumavat is directed towards the related field of addressing failure in an autonomous vehicle. Therefore, one of ordinary skill in the art would be motivated to modify Hoshina with Kumavat to improve safety (see at least Kumavat [0014]: “In a first variation, the technology confers the benefit of enabling an autonomous vehicle to be fail-operational in a way which is safe and optimally targeted to the particular failure, through a multi-layered redundant architecture for hardware and software subsystems of the vehicle.”).
Regarding claim 2, Hoshina in view of Kumavat teach all elements of the ego-machine according to claim 1 as explained above. Hoshina further teaches
wherein the one or more operations comprise controlling, using the second set of the plurality of processors, one or more autonomous driving features of the ego-machine based at least on the one or more validity checks (see at least Hoshina [0114]: “In particular, even in a case where it is not determined whether or not the vehicle 1 is in the immediately-before-transition state, that is, in a case where it is unknown whether or not the vehicle 1 is in the immediately-before-transition state and it is unknown when the vehicle 1 will be switched from the autonomous driving mode to the manual driving mode, it is possible to assume that the vehicle 1 is in the immediately-before-transition state if the vehicle 1 is set to the autonomous driving mode, and to thereby prevent detection failures of an abnormal state. As a result, it is possible to switch from the autonomous driving mode to the manual driving mode at any time when the switching is required, thereby making it possible not to miss an abnormal state.”; [0022]: “An autonomous driving control device 3 executes control for switching the driving mode of the vehicle 1. The autonomous driving control device 3 executes control for causing the vehicle 1 to travel when the vehicle 1 is set in the autonomous driving mode.”).
Regarding claim 9, Hoshina in view of Kumavat teach all elements of the ego-machine according to claim 1 as explained above. Hoshina further teaches
wherein the one or more operations comprise using the second set of the plurality of processors to initiate, in response to identifying the one or more identified faults, one or more of disengagement of an autonomous driving feature, generation of a notification prior to the disengagement of the autonomous driving feature, or execution of one or more emergent driving maneuvers (see at least Hoshina [0114]: “In particular, even in a case where it is not determined whether or not the vehicle 1 is in the immediately-before-transition state, that is, in a case where it is unknown whether or not the vehicle 1 is in the immediately-before-transition state and it is unknown when the vehicle 1 will be switched from the autonomous driving mode to the manual driving mode, it is possible to assume that the vehicle 1 is in the immediately-before-transition state if the vehicle 1 is set to the autonomous driving mode, and to thereby prevent detection failures of an abnormal state. As a result, it is possible to switch from the autonomous driving mode to the manual driving mode at any time when the switching is required, thereby making it possible not to miss an abnormal state.”; [0022]: “That is, the vehicle 1 can travel in any of a manual driving mode or an autonomous driving mode. An autonomous driving control device 3 executes control for switching the driving mode of the vehicle 1.”).
Regarding claim 10, Hoshina in view of Kumavat teach all elements of the ego-machine according to claim 1 as explained above. Hoshina further teaches wherein one or more processors of the plurality of processors are comprised in at least one of:
a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system for performing deep learning operations; a system for performing remote operations; a system for performing real-time streaming; a system for generating or presenting one or more of augmented reality content, virtual reality content, or mixed reality content; a system implemented using an edge device; a system implemented using a robot; a system for generating synthetic data; a system for generating synthetic data using AI; a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources (see at least Hoshina [0022]: “The vehicle 1 has a function of autonomous driving. That is, the vehicle 1 can travel in any of a manual driving mode or an autonomous driving mode. An autonomous driving control device 3 executes control for switching the driving mode of the vehicle 1. The autonomous driving control device 3 executes control for causing the vehicle 1 to travel when the vehicle 1 is set in the autonomous driving mode.”; Hoshina discloses at least a control system for an autonomous or semi-autonomous machine; examiner notes it is only required for the reference to disclose at least one limitation of the claim since the claim language uses “or” when listing claim limitations).
Regarding claim 11, this claim recites a system of the ego machine of claim 1. Hoshina in view of Kumavat also teach a system of the ego machine of claim 1 as outlined in the rejection to claim 1 above. Therefore, claim 11 is rejected for the same rationale as claim 1.
Regarding claim 12, this claim recites a system for the ego machine of claim 2 as explained above. Therefore, claim 12 is rejected for the same rationale as claim 2.
Regarding claim 18, this claim recites a system for the ego machine of claim 10 as explained above. Therefore, claim 18 is rejected for the same rationale as claim 10.
Regarding claim 19, this claim recites a method performed by the ego machine of claim 1. Hoshina in view of Kumavat also teach a method performed by the ego machine of claim 1 as outlined in the rejection to claim 1 above. Therefore, claim 19 is rejected for the same rationale as claim 1.
Regarding claim 20, this claim recites a method performed by the ego machine of claim 10 as explained above. Therefore, claim 20 is rejected for the same rationale as claim 10.
Claims 3-6 and 13-16 are rejected under 35 U.S.C. 103 as being unpatentable over Hoshina in view of Kumavat, and further in view of Wu, U.S. Patent No. 11951833 B1.
Regarding claim 3, Hoshina in view of Kumavat teach all elements of the ego-machine according to claim 1 as explained above. Hoshina in view of Kumavat fail to expressly disclose applying a threshold range of motion to a detected head pose. However, Wu teaches
wherein the second set of the plurality of processors is further to execute the one or more validity checks based at least on applying a designated threshold range of motion to a detected head pose represented by the one or more detected human features (see at least Wu Col. 42, lines 40-53: “The processors 106a-106n may further analyze the head/face detection 472 to determine the behavior of the driver 202 (e.g., determine whether the driver 202 is attempting to provide input to the infotainment unit 352). The processors 106a-106n may analyze the direction of the head/face 472. In the example shown, the head/face 472 is shown facing straight ahead (e.g., towards the windshield 404). When the head/face 472 is directed straight ahead, the confidence level for interaction with the infotainment unit may be decreased. In an example, if the head/face 472 is determined to not be facing the windshield 404 (e.g., the head/face 472 is turned towards the location of the infotainment unit 352), then the confidence level for input from the driver 202 may be increased.”; Col. 23, lines 17-20: “For example, the drowsiness and/or attentiveness of the driver 202 may be detected (e.g., recognizing that eyes are closing, recognizing that the head is drifting down, etc.).”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the system disclosed by Hoshina in view of Kumavat with the threshold taught by Wu with reasonable expectation of success. Wu is directed towards the related field of determining infotainment system permission control based on in-cabin monitoring. Therefore, one of ordinary skill in the art would be motivated to modify Hoshina in view of Kumavat with Wu to prevent driver distraction and frustration (see at least Wu Col. 3, lines 36-53: “To prevent driver distraction, the infotainment system may be configured to operate in a locked mode while the vehicle is moving (e.g., not stationary)…If one of the passengers is attempting to provide the touch input while the vehicle is moving, then the touch input may be enabled (e.g., to add convenience and/or prevent frustration).”).
Regarding claim 4, Hoshina in view of Kumavat teach all elements of the ego-machine according to claim 1 as explained above. Hoshina in view of Kumavat fail to expressly disclose applying a threshold range of motion to a detected gaze direction. However, Wu teaches
wherein the second set of the plurality of processors is further to execute the one or more validity checks based at least on applying a designated threshold range of motion to a detected gaze direction represented by the one or more detected human features (see at least Wu Col. 42, line 54-Col. 43, line 12: “The processors 106a-106n may be configured to analyze the eyes 474a-474b to determine the behavior of the driver 202. The processors 106a-106n may be configured to determine the direction of the eyes 474a-474b…In the example shown, the eyes 474a-474b may be directed straight ahead (e.g., towards the windshield 404 and not directed towards the location of the infotainment unit 352), which may decrease the confidence level of detection of input by the driver 202. In another example, if the eyes 474a-474b were directed towards the location of the infotainment unit 352, then the decision module 158 may increase the confidence level of detection of input by the driver 202.”; Col. 23, lines 16-20: “In some embodiments, the processors 106a-106n may be configured to approximate the gaze of the driver 202. For example, the drowsiness and/or attentiveness of the driver 202 may be detected (e.g., recognizing that eyes are closing, recognizing that the head is drifting down, etc.).”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the system disclosed by Hoshina in view of Kumavat with the threshold taught by Wu with reasonable expectation of success. Wu is directed towards the related field of determining infotainment system permission control based on in-cabin monitoring. Therefore, one of ordinary skill in the art would be motivated to modify Hoshina in view of Kumavat with Wu to prevent driver distraction and frustration (see at least Wu Col. 3, lines 36-53: “To prevent driver distraction, the infotainment system may be configured to operate in a locked mode while the vehicle is moving (e.g., not stationary)…If one of the passengers is attempting to provide the touch input while the vehicle is moving, then the touch input may be enabled (e.g., to add convenience and/or prevent frustration).”).
Regarding claim 5, Hoshina in view of Kumavat teach all elements of the ego-machine according to claim 1 as explained above. Hoshina in view of Kumavat fail to expressly disclose applying a threshold on a change in a detected head pose. However, Wu teaches
wherein the second set of the plurality of processors is further to execute the one or more validity checks based at least on applying a designated threshold on a change in a detected head pose represented by the one or more detected human features (see at least Wu Col. 42, lines 40-53: “The processors 106a-106n may further analyze the head/face detection 472 to determine the behavior of the driver 202 (e.g., determine whether the driver 202 is attempting to provide input to the infotainment unit 352). The processors 106a-106n may analyze the direction of the head/face 472. In the example shown, the head/face 472 is shown facing straight ahead (e.g., towards the windshield 404). When the head/face 472 is directed straight ahead, the confidence level for interaction with the infotainment unit may be decreased. In an example, if the head/face 472 is determined to not be facing the windshield 404 (e.g., the head/face 472 is turned towards the location of the infotainment unit 352), then the confidence level for input from the driver 202 may be increased.”; Col. 23, lines 17-20: “For example, the drowsiness and/or attentiveness of the driver 202 may be detected (e.g., recognizing that eyes are closing, recognizing that the head is drifting down, etc.).”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the system disclosed by Hoshina in view of Kumavat with the threshold taught by Wu with reasonable expectation of success. Wu is directed towards the related field of determining infotainment system permission control based on in-cabin monitoring. Therefore, one of ordinary skill in the art would be motivated to modify Hoshina in view of Kumavat with Wu to prevent driver distraction and frustration (see at least Wu Col. 3, lines 36-53: “To prevent driver distraction, the infotainment system may be configured to operate in a locked mode while the vehicle is moving (e.g., not stationary)…If one of the passengers is attempting to provide the touch input while the vehicle is moving, then the touch input may be enabled (e.g., to add convenience and/or prevent frustration).”).
Regarding claim 6, Hoshina in view of Kumavat teach all elements of the ego-machine according to claim 1 as explained above. Hoshina in view of Kumavat fail to expressly disclose applying a threshold on a change in a detected gaze direction. However, Wu teaches
wherein the second set of the plurality of processors is further to execute the one or more validity checks based at least on applying a designated threshold on a change in a detected gaze direction represented by the one or more detected human features (see at least Wu Col. 42, line 54-Col. 43, line 12: “The processors 106a-106n may be configured to analyze the eyes 474a-474b to determine the behavior of the driver 202. The processors 106a-106n may be configured to determine the direction of the eyes 474a-474b…In the example shown, the eyes 474a-474b may be directed straight ahead (e.g., towards the windshield 404 and not directed towards the location of the infotainment unit 352), which may decrease the confidence level of detection of input by the driver 202. In another example, if the eyes 474a-474b were directed towards the location of the infotainment unit 352, then the decision module 158 may increase the confidence level of detection of input by the driver 202.”; Col. 23, lines 16-20: “In some embodiments, the processors 106a-106n may be configured to approximate the gaze of the driver 202. For example, the drowsiness and/or attentiveness of the driver 202 may be detected (e.g., recognizing that eyes are closing, recognizing that the head is drifting down, etc.).”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the system disclosed by Hoshina in view of Kumavat with the threshold taught by Wu with reasonable expectation of success. Wu is directed towards the related field of determining infotainment system permission control based on in-cabin monitoring. Therefore, one of ordinary skill in the art would be motivated to modify Hoshina in view of Kumavat with Wu to prevent driver distraction and frustration (see at least Wu Col. 3, lines 36-53: “To prevent driver distraction, the infotainment system may be configured to operate in a locked mode while the vehicle is moving (e.g., not stationary)…If one of the passengers is attempting to provide the touch input while the vehicle is moving, then the touch input may be enabled (e.g., to add convenience and/or prevent frustration).”).
Regarding claim 13, this claim recites a system for the ego machine of claim 3 as explained above. Therefore, claim 13 is rejected for the same rationale as claim 3.
Regarding claim 14, this claim recites a system for the ego machine of claim 4 as explained above. Therefore, claim 14 is rejected for the same rationale as claim 4.
Regarding claim 15, this claim recites a system for the ego machine of claim 5 as explained above. Therefore, claim 15 is rejected for the same rationale as claim 5.
Regarding claim 16, this claim recites a system for the ego machine of claim 6 as explained above. Therefore, claim 16 is rejected for the same rationale as claim 6.
Claims 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Hoshina in view of Kumavat, and further in view of Chiu, U.S. Patent Application Publication No. 2025/0206323 A1.
Regarding claim 7, Hoshina in view of Kumavat teach all elements of the ego-machine according to claim 1 as explained above. Hoshina in view of Kumavat fail to expressly disclose applying a maximum time or maximum number of frames between detected blinks. However, Chiu teaches
wherein the second set of the plurality of processors is further to execute the one or more validity checks based at least on applying at least one of a maximum time or a maximum number of frames between detected blinks (see at least Chiu [0035]: “In an embodiment, the physiological status is that a number of blinks is higher than the corresponding threshold. For example, blinking more than twice within 5 seconds; or blinking more than three times within 10 seconds. The above physiological status may be regarded as a slightly abnormal status.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the system disclosed by Hoshina in view of Kumavat with the blink detection taught by Chiu with reasonable expectation of success. Chiu is directed towards the related field of a driver monitoring method and driving risk evaluation system. Therefore, one of ordinary skill in the art would be motivated to modify Hoshina in view of Kumavat with Chiu to reduce accidents without frequently disturbing the driver (see at least Chiu [0005]: “The disclosure provides a driving monitoring method and a driving risk evaluation system, which may remind a driver in a timely manner to reduce the occurrence of accidents without disturbing the driver too frequently.”).
Regarding claim 17, this claim recites a system for the ego machine of claim 7 as explained above. Therefore, claim 17 is rejected for the same rationale as claim 7.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Hoshina in view of Kumavat, and further in view of Liu, U.S. Patent Application Publication No. 2024/0336262 A1.
Regarding claim 8, Hoshina in view of Kumavat teach all elements of the ego-machine according to claim 1 as explained above. Hoshina in view of Kumavat fail to expressly disclose executing the one or more validity checks based at least on applying a designated threshold on a change in a detected measure of drowsiness. However, Liu teaches
wherein the second set of the plurality of processors is further to execute the one or more validity checks based at least on applying a designated threshold on a change in a detected measure of drowsiness (see at least Liu [0165]: “When the driver state monitoring unit 200 is directly associated with the vehicle control unit 500, and the real-time sentiment identification result and/or the abnormal behavior monitoring result and/or the fatigue state monitoring result of the driver reaches or exceeds a danger threshold, the vehicle control unit 500 controls the vehicle to perform speed limit, deceleration, or emergency braking, and the alarm prompt unit sends an alarm prompt of a dangerous state or a dangerous behavior, and the analysis, identification or determination result and an action state of the vehicle control unit are uploaded to the remote management unit 600 through the on-board gateway unit 300.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the system disclosed by Hoshina in view of Kumavat with Liu with reasonable expectation of success. Liu is directed towards the related field of an active safety driver assistance system based on driver state monitoring. Therefore, one of ordinary skill in the art would be motivated to modify Hoshina in view of Kumavat with Liu to improve operating safety (see at least Liu [0010]: “Therefore, how to effectively monitor and actively process potential accident risks that may be caused by a driver, to effectively improve operating safety of all commercial vehicles such as vehicles included in the term “two types of passenger vehicles, one type of hazardous goods vehicles, one type of freight vehicles, and one type of school vehicles”, taxis, online vehicles and rental cars on various platforms is a problem urgently to be resolved in the art.”).
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 ELIZABETH J SLOWIK whose telephone number is (571)270-5608. The examiner can normally be reached MON - FRI: 0900-1700.
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/ELIZABETH J SLOWIK/Examiner, Art Unit 3662
/ANISS CHAD/Supervisory Patent Examiner, Art Unit 3662