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 .
Information Disclosure Statement
No additional information disclosure statement(s) (IDS) were submitted for consideration.
Priority
Acknowledgment is made of applicant's claim for foreign priority based on an application filed in Republic of Korea on 05/24/2024.
Status of Application
Claims 1, 3-11, and 13-21, are pending.
Claims 1, 3, 11, and 13, are amended.
No claims are withdrawn from consideration.
Claims 2 and 12 are cancelled.
Claim 21 is added.
Claims 1, 11, and 21, are independent claims.
Claims 1, 3-11, and 13-21, will be examined.
This Non-Final Office action is in response to the amended “Claims” and “Applicant Arguments/Remarks” dated 06/24/2026.
Response to Arguments
Applicant’s Remarks/Arguments and amended claims, filed 06/24/2026, with respect to claims 1, 3-11, and 13-21, have been fully considered and Applicant' s remarks will be addressed in sequential order as they were presented.
Regarding Objection to Title (Specification), the applicant’s response has been fully considered and is persuasive. Therefore, the Objection to Title is withdrawn.
Regarding Rejections under 35 U.S.C. 103, and the remarks, “Yin and King fail to cure the deficiencies of Cheng,” and the alleged combination does not obtain a "heading confidence value" "based on a peak of the loss function and a valley of the loss function," the Office respectfully disagrees. The prior art Yin and King discloses/teaches "heading confidence value" "based on a peak of the loss function and a valley of the loss function." Prior art Yin discloses using “gradient descent method (SGD)” as a fundamental gradient descent algorithm for machine learning using potential maximum/minimum values (i.e. peaks/valleys of loss function) to determine a “global minimum value of the loss value.” This gradient descent method from prior art Yin equates to “a gradient descent algorithm” disclosed within the Applicant paragraph [0124]. Furthermore, the illustrative language used in the applicant claim is no more than broadly describing the gradient descent algorithm. Prior art King teaches tracking adjustment of vehicles as boxes wherein a machine learning (ML) model “may predict an (x,y) translation that moves the track center to the true center,” and “validity score… may indicate higher confidence in the validity of the observation,” (i.e. heading confidence value).
It remains the Offices stance that the cited prior art anticipates or renders obvious this claimed subject matter.
Applicant further argues that the other independent claims which recite similar features are allowable and the dependent claims are also allowable since they depend on allowable subject and the Office respectfully disagrees. It is the Office's stance that all of the claimed subject matter has been properly rejected; therefore the Office's respectfully disagrees with applicant' s arguments.
Therefore, it remains the Office’s stance that the combination of Cheng, King, and Yin, disclose/teach the claimed subject matter as presented in the grounds for rejection below.
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.
Claim(s) 1 and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over CHENG et al., US 20190179332, herein further known as Cheng, in view of KING et al., US 20250165869, herein further known as King further in view of YIN et al., CN 116486381, herein further known as Yin.
Regarding claim 1, Cheng discloses an apparatus for controlling autonomous driving of a vehicle (¶ [0039], see also FIG. 1), a sensor configured to obtain a cluster of points (¶¶ [0050-0051], [0105], [0113]), wherein the cluster of points corresponds to an object (¶¶ [0050-0051], obstacle [01265], [0133], [0138], claims 7-9, obstacle); a processor configured to generate, based on information from the sensor (¶¶ [0045], [0050-0051], [0105]), a first virtual box, wherein the first virtual box corresponds to the object (circumscribing rectangle of the target obstacle point cloud - ¶¶ [0006-0023], [0030-0031], see also FIGS. 3A and 3B, [0061-0075], [0079-0083], [0095-0097], [0101], 0105-0107], [0110], [0113], [0115], [0118], [0120-0121], [0130], [0133], [0136-0137], [0140-0149], and claims 1-2, 4-11); obtain, based on a(¶¶ [0087], [0137], electronic device may output the direction information corresponding to the target obstacle point cloud, target circumscribing rectangle…), a heading confidence value for a heading direction of the first virtual box (confidence level of target level - ¶¶ [0012-0014], [0021-0023], [0124-0127], [0131-0138], [0147-0149]),
However, Cheng does not explicitly state a loss function, wherein the loss function is obtained by applying a designated algorithm, and wherein the loss function represents a degree of accuracy of the designated algorithm for determining the direction; obtain, based on the heading confidence value, an angle value for adjusting the heading direction; output, based on adjusting the heading direction of the first virtual box, a second virtual box, wherein the heading direction is adjusted based on the angle value; generate a signal indicating the second virtual box; and control, based on the signal, autonomous driving of the vehicle and a peak of the loss function and a valley of the loss function.
King teaches a loss function, wherein the loss function is obtained by applying a designated algorithm, and wherein the loss function represents a degree of accuracy of the designated algorithm for determining the direction; obtain, based on the heading confidence value, an angle value for adjusting the heading direction; output, based on adjusting the heading direction of the first virtual box, a second virtual box, wherein the heading direction is adjusted based on the angle value; generate a signal indicating the second virtual box (¶¶ [0058], neural network engine (i.e. algorithm), [0089-0094], [0118], input track boxes (i.e. first virtual box), predicted track boxes (i.e. second virtual box) [0118], track adjustment model based upon angle (i.e. heading direction is adjusted based on the angle value)); and control, based on the signal, autonomous driving of the vehicle (¶¶ [0039], [0058], generating suitable control signals for controlling the various controls in the vehicle control system).
It would have been obvious to person of ordinary skill in the art before the effective filing date of the invention, with a reasonable expectation of success, to incorporate in to Cheng the loss function, wherein the loss function is obtained by applying a designated algorithm, and wherein the loss function represents a degree of accuracy of the designated algorithm for determining the direction; obtain, based on the heading confidence value, an angle value for adjusting the heading direction; output, based on adjusting the heading direction of the first virtual box, a second virtual box, wherein the heading direction is adjusted based on the angle value; generate a signal indicating the second virtual box; and control, based on the signal, autonomous driving of the vehicle as taught by King.
One would be motivated to modify Cheng in view of King for the reasons stated in King paragraph [0003], a more robust system and method wherein the state of the objects dynamically changes, and improves efficiently updating the tracking and/or identifying of the object by using new measurement data. Moreover, when sensors of an autonomous vehicle obtain measurements at multiple points (i.e. cluster of points or cloud points), the more robust system and method improves efficient processing of multiple points.\
Furthermore, Yin teaches obtain, based on a peak of the loss function and a valley of the loss function, the heading confidence value (pages 16-17, gradient descent method (SGD) [0192], global minimum value is relative to the local minimum value…).
It would have been obvious to person of ordinary skill in the art before the effective filing date of the invention, with a reasonable expectation of success, to incorporate in to Cheng the obtain, based on a peak of the loss function and a valley of the loss function, the heading confidence value as taught by Yin.
One would be motivated to modify Cheng in view of Yin for the reasons stated in Yin wherein obstacle detection and identifying the forward direction of the automobile is the key technical feature for the automobile to improve the living standard of people.
Regarding claim 11, all limitations have been examined with respect to the apparatus in claim 1. The method/steps taught/disclosed in claim 11 can clearly perform on the apparat
us of claim 1. Therefore, claim 11 is rejected under the same rationale as claim 1 above.
Claim(s) 6, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Cheng, King, and Yan further in view of HAN, CN 118823722, herein further known as Han.
Regarding claim 6, the combination of Cheng, King, and Yan, disclose all elements of claim 1 above.
However, Cheng does not explicitly state obtain, heading value based on applying the heading confidence value to direction of the first virtual box, the angle value.
Han teaches obtain, heading value based on applying the heading confidence value to direction of the first virtual box, the angle value, (paragraph stating, course angle classification result with the highest confidence score is used as the course angle classification result)
It would have been obvious to person of ordinary skill in the art before the effective filing date of the invention, with a reasonable expectation of success, to incorporate in to Cheng the obtain, heading value based on applying the heading confidence value to direction of the first virtual box, the angle value as taught by Han.
One would be motivated to modify Cheng in view of Han for the reasons stated in Han, more robust methods wherein the target course angle identification algorithm is only increased with little calculation amount, and the time consumption is hardly increased in the algorithm reasoning process.
Regarding claim 16, all limitations have been examined with respect to the apparatus in claim 6. The method/steps taught/disclosed in claim 16 can clearly perform on the apparatus of claim 6. Therefore, claim 16 is rejected under the same rationale as claim 6 above.
Allowable Subject Matter
Claim 21 is allowed.
Claims 3-5, 7-10, 13-15, 17-20, 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.
The best prior art available is believed to be Cheng, King, Yan, and Han, as cited above. However the cited art does not fully disclose or suggest each and every feature of claim(s) 21. Accordingly, claim(s) 21 appear(s) to contain allowable subject matter in view of the available prior art. The prior art fails to make obvious or disclose a sensor within a vehicle configured to obtain a cluster of points, wherein the cluster of points corresponds to an object, a processor to generate, based on information from the sensor, a first virtual box corresponding to the object; obtained, based on a loss function by a designated algorithm associated with the first virtual box, a heading confidence value for a heading direction of the first virtual box, and the loss function represents a degree of accuracy for determining the heading direction, and adjusting the heading direction of the first virtual box.
The elements of output of a second virtual box, wherein the heading direction is adjusted based on the angle value, generating a control signal indicating the second virtual box for operation of the vehicle, and perform at least one of: generating the second virtual box, wherein the second virtual box is obtained by adjusting the first virtual box based on at least one of: a width of the first virtual box being smaller than a first length and a length of the first virtual box being smaller than a second length, or a maximum value of a vertical axis direction of the object, a minimum value of the vertical axis direction, and the angle value among coordinate values of points in the cluster of points; obtaining, based on applying the heading confidence value to the heading direction of the first virtual box, the angle value by obtaining the angle value based on applying a coefficient to the heading direction, wherein the coefficient is obtained by multiplying the heading confidence value by the heading confidence value; or generating the second virtual box with a second heading direction, wherein the second heading direction indicates a difference in the angle value based on a longitudinal axis of the vehicle in a vehicle coordinate system, and wherein the vehicle coordinate system is centered on the vehicle, which combination of features or aspect of the independent claim features overcomes the art of record, and are not explicitly disclosed, taught, or suggested in the previous art.
It should be noted that this is in view of the prior art only. The claim rejections under 35 USC § 103, which are detailed above, must be overcome before a notice of allowance can be considered.
As allowable subject matter has been indicated, applicant's reply must either comply with all formal requirements or specifically traverse each requirement not complied with. See 37 CFR 1.111(b) and MPEP § 707.07(a).
Conclusion
THIS ACTION IS MADE FINAL. 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 Terry Buse whose telephone number is (313)446-6647. The examiner can normally be reached Monday - Friday 8-5 PM EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Scott Browne can be reached at (571) 270-0151. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/TERRY C BUSE/Examiner, Art Unit 3666
/SCOTT A BROWNE/Supervisory Patent Examiner, Art Unit 3666
Prosecution Insights