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
The information disclosure statement (IDS) submitted on 03/14/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
On January 7, 2019, the USPTO released new examination guidelines setting forth a two-step inquiry for determining whether a claim is directed to non-statutory subject matter. According to the guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), 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:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claims 1, 12 and 17 are directed toward non-statutory subject matter, as shown below:
STEP 1: Do claims fall within one of the statutory categories? Claims 1 and 12 are system and method and claim 17 is non-transitory computer-readable media storing computer-executable instructions, and as such fall within one of the statutory categories.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? Yes, claims 1, 12 and 17 are directed to mental processes.
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
NOTE: Claims 1, 12 and 17 recite limitations that are similar in scope, hence examiner will assess method of claim 1.
The method of claim 1 contains a mental process that can be practicably performed in the human mind and, therefore, an abstract idea. The claim merely recites detecting a safety issue based on sensor data. A human can look at sensor data and determine that there is a safety issue. Furthermore, generating an alert to driver is interpreted as displaying an alert (in view of [0013] of specification) i.e., collecting information, analyzing it, and displaying certain results of the collection and analysis. Hence is recognized as observations, evaluations, judgments, and opinions. See Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016).
Therefore, limitation of “detecting, by the computing system, and based at least in part on the sensor data, a safety issue associated with the maneuver; and
generating, by the computing system, output configured to alert a driver of the vehicle of the safety issue” is a mental process, hence an abstract idea.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? No, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses 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 more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claims 1, 12 and 17 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. Also, as noted above, merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea is indicative that the judicial exception has not been integrated into a practical application.
The steps identified in prong 1 are performed by a computer. Thus, it is clear that the abstract idea is merely implemented on a computer, which is indicative of the abstract idea having not been integrated into a practical application. See MPEP 2106.05(f).
Furthermore, the steps performed by controller above are performed “receiving, by a computing system comprising a processor, sensor data, wherein:
the sensor data is captured by at least one sensor in association with a maneuver performed by a vehicle during towing of a towable object by the vehicle”, this is mere data gathering, hence an insignificant extra solution activity. See MPEP 2106.05(g).
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No, the claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Claims 1, 7 and 13 not recite any specific limitation or combination of limitations that are not well-understood, routine, conventional (WURC) activity in the field. Limitations identified as “apply it” in step 2A qualify as apply it in step 2B as well.
With respect to “receiving, by a computing system comprising a processor, sensor data, wherein: the sensor data is captured by at least one sensor in association with a maneuver performed by a vehicle during towing of a towable object by the vehicle”, this is receiving or transmitting data. And as such has been recognized as well-understood
routine and conventional. See MPEP 2106.05(d).
CONCLUSION
Thus, since claims 1, 12 and 17 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that claims 1, 12 and 17 are directed towards non-statutory subject matter.
With respect to claims 2 and 18, the claims further limit a maneuver to be a cornering maneuver and safety issue associated with a likelihood of the towable object veering outside a current travel lane. A human can determine that towable object is veering outside current travel lane during cornering or turning. Hence does not amount to a practical application or significantly more.
With respect to claim 3, the claim further limits maneuver to be turning or cornering. And a human can determine that towable object will likely collide with an external object. Therefore, is not considered a practical application or significantly more.
With respect to claim 4, the claim further limits maneuver to be a backup maneuver. And a human can determine that towable object will likely collide with an external object. Therefore, is not considered a practical application or significantly more.
With respect to claim 5, the claim further limits the display to be a safety tip via a chat bot. This is still part of the abstract idea and not considered a practical application or significantly more.
With respect to claim 6, the claim further limits chat bot to be a generative pre-trained transformer (GPT) model. This is still part of the abstract idea, or at most apply it. Hence is not considered a practical application or significantly more.
With respect to claim 7, under displaying a visual alert is still part of the abstract idea and not considered a practical application or significantly more.
With respect to claims 8, 14 and 19, generating a predicted likelihood and comparing the likelihood to a threshold is still part of the abstract idea as human can predict a likelihood and compare it to a threshold i.e., a mathematical calculation. Hence is not considered a practical application or significantly more.
With respect to claims 9 and 19, training a machine learning model to predict likelihood of safety issue is still part of apply it. And is not considered a practical application or significantly more.
With respect to claims 10, 16 and 20, generating a predicted action to avoid the safety issue and outputting the predicted action to driver is still part of the abstract idea and not considered a practical application or significantly more.
With respect to claim 11, the claim merely limits safety issue to be object veering outside a current travel lane or colliding with an external object, and predicted action to as modification of driving speed or angle. This is still part of the abstract idea and not considered a practical application or significantly more.
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-3, 12, 17 and 18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Prasad (US 20180061239).
For claim 1, Prasad teaches: A computer-implemented method for providing driving assistance ([0029-0032], disclosing an alert device for warning operator of a vehicle i.e., providing driving assistance), the method comprising:
receiving, by a computing system comprising a processor, sensor data ([0016], disclosing angle-detector 20 used to determine a trailer-angle 22 of the trailer 12 relative to the host-vehicle. The angle-detector 20 may be a Lidar-sensor), wherein:
the sensor data is captured by at least one sensor in association with a maneuver performed by a vehicle during towing of a towable object by the vehicle ([0016], disclosing angle-detector 20 used to determine a trailer-angle 22 of the trailer 12 relative to the host-vehicle. The angle-detector 20 may be a Lidar-sensor. [0032], disclosing controller 44 is further configured to determine when the trailer 12 is departing from the travel-lane 64 based on the trailer-angle. [0030], disclosing determining ), and
the at least one sensor is mounted on the vehicle or the towable object ([0016], disclosing angle-detector 20 may be a device (not shown) mounted on a trailer-hitch (not shown) of the host-vehicle 14 or on the trailer);
detecting, by the computing system, and based at least in part on the sensor data, a safety issue associated with the maneuver ([0030], disclosing controller 44 may be configured to determine whether a current path of the host-vehicle 14 and trailer 12 may collide with an object or other-vehicle 48, based on the turning path of the combination of the host-vehicle 14 and the trailer. [0032], disclosing controller 44 is further configured to determine when the trailer 12 is departing from the travel-lane 64 based on the trailer-angle and controller 44 may consider the departure of the trailer 12 from the travel-lane 64 unintentional when a turn-signal of the host-vehicle 14 is not activated prior to the departure of the trailer 12 from the travel-lane, i.e., safety issue); and
generating, by the computing system, output configured to alert a driver of the vehicle of the safety issue ([0032], disclosing activate the alert-device 56 to warn the operator 58 of the host-vehicle 14 that the trailer 12 is making an unintentional departure from the travel-lane 64, i.e. issue a lane-departure-warning. [0030], disclosing controller 44 may also be configured to activate the alert-device 56 to warn the operator 58 of the impending collision).
Computer system of claim 12 recites limitations similar in scope to claim 1, hence is similarly rejected.
For claim 17, Prasad teaches One or more non-transitory computer-readable media storing computer-executable instructions associated with a smart towing assistant configured to provide driving assistance that, when executed by one or more processors of a computing system ([0028-0032], disclosing controller receives sensor data, determines safety issue and alerts driver. Instructions are necessary to be executed in controller to perform the identification of safety issue and alerting driver), cause the one or more processors to: LIMITATIONS SIMILAR IN SCOPE TO CLAIM 1, HENCE SIMILARLY REJECTED.
For claim 2, Prasad teaches: The computer-implemented method of claim 1, wherein:
the maneuver is a turning or cornering maneuver ([0030], disclosing determine whether a current path of the host-vehicle 14 and trailer 12 may collide with an object or other-vehicle 48, based on the turning path of the combination of the host-vehicle 14 and the trailer. [0031], disclosing identifying lane markings by a camera), and
the safety issue is associated with a likelihood of the towable object veering outside a current travel lane during the turning or cornering maneuver ([0032], disclosing determine when the trailer 12 is departing from the travel-lane 64 based on the trailer-angle 22 and the trailer-model 36, and may activate the alert-device 56 to warn the operator 58 of the host-vehicle 14 that the trailer 12 is making an unintentional departure from the travel-lane i.e., trailer is likely veering outside current travel lane).
Claim 13, under BRI recites limitations similar in scope to claim 2, hence is similarly rejected.
Claim 18 recites limitations similar in scope to claim 2, hence is similarly rejected.
For claim 3, Prasad teaches: The computer-implemented method of claim 1, wherein:
the maneuver is a turning or cornering maneuver ([0030], disclosing determine whether a current path of the host-vehicle 14 and trailer 12 may collide with an object or other-vehicle 48, based on the turning path of the combination of the host-vehicle 14 and the trailer. [0031], disclosing identifying lane markings by a camera), and
the safety issue is associated with a likelihood of the towable object colliding with an external object during the turning or cornering maneuver ([0030], disclosing determine whether a current path of the host-vehicle 14 and trailer 12 may collide with an object or other-vehicle 48, based on the turning path of the combination of the host-vehicle 14 and the trailer).
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.
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 4 is rejected under 35 U.S.C. 103 as being unpatentable over Prasad in view of Enno (US 20230331151).
For claim 4, Prasad teaches: The computer-implemented method of claim 1, wherein:
Although backing up is spart of driving, Prasad does not explicitly teach: the maneuver is a backup maneuver, and
the safety issue is associated with a likelihood of the towable object colliding with an external object during the backup maneuver.
Enno teaches maneuver is a backup maneuver, and the safety issue is associated with a likelihood of the towable object colliding with an external object during the backup maneuver (abstract, disclosing collision avoidance assembly for reducing collisions with a semitrailer includes a rear and side facing alert modules. [0023], disclosing. The collision avoidance assembly 10 also will notify the operator of the semitruck 54 when the semitrailer 18 is approaching a stationary object, which will help the operator to avoid such objects when making turns and when backing up the semitrailer)
Enno and Prasad are analogous arts as they are in same field of endeavor i.e., alerting driver of a towing vehicle about potential collisions. It would have been obvious to one having ordinary skill in the art before effective filing date of claimed invention to modify art of Prasad to teaches maneuver is a backup maneuver, and the safety issue is associated with a likelihood of the towable object colliding with an external object during the backup maneuver as taught by Enno to prevent collisions in all maneuvers. Thereby, improving safety.
Claims 5 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Prasad in view of Ariyoshi (US 20250272961).
For claim 5, Prasad teaches: The computer-implemented method of claim 1,
Prasad does not explicitly teach: wherein the output is natural language output, generated via a chatbot, that expresses a safety tip associated with a resolution of the safety issue.
Ariyoshi teaches wherein the output is natural language output, generated via a chatbot, that expresses a safety tip associated with a resolution of the safety issue ([0067], disclosing a driving assistance system. HMI displays a risk area RA2 corresponding to a pedestrian P5 depicted in the out-vehicle image, and outputs a warning message (“Be careful not to look aside while driving”) as text information or voice information in a case where the driver's gaze depicted in the in-vehicle image is not directed toward the pedestrian P5. This makes it possible to realize driving assistance considering the driver's condition)
Ariyoshi and Prasad are analogous arts as they are in same field of endeavor i.e., driving assistance. It would have been obvious to one having ordinary skill in the art before effective filing date of claimed invention to modify art of Prasad to wherein the output is natural language output, generated via a chatbot, that expresses a safety tip associated with a resolution of the safety issue as taught by Ariyoshi to make the driver aware of the safety condition and necessary action to take.
For claim 7, Prasad teaches: The computer-implemented method of claim 1,
Although, an alert necessarily has to be an audible alert, a visual alert, or a haptic alert, Prasad does not explicitly teach: wherein the output is at least one of an audible alert, a visual alert, or a haptic alert presented via a user interface during the maneuver.
Ariyoshi teaches wherein the output is at least one of an audible alert, a visual alert, or a haptic alert presented via a user interface ([0067], disclosing a driving assistance system. HMI displays a risk area RA2 corresponding to a pedestrian P5 depicted in the out-vehicle image, and outputs a warning message (“Be careful not to look aside while driving”) as text information or voice information in a case where the driver's gaze depicted in the in-vehicle image is not directed toward the pedestrian P5. This makes it possible to realize driving assistance considering the driver's condition)
Ariyoshi and Prasad are analogous arts as they are in same field of endeavor i.e., driving assistance. It would have been obvious to one having ordinary skill in the art before effective filing date of claimed invention to modify art of Prasad to wherein the output is at least one of an audible alert, a visual alert, or a haptic alert presented via a user interface during the maneuver as taught by Ariyoshi as a means to alert the driver.
Claims 6 is rejected under 35 U.S.C. 103 as being unpatentable over Prasad in view of Ariyoshi and Mazed (US 11892746).
For claim 6, modified Prasad teaches: The computer-implemented method of claim 5,
Mazed teaches: wherein the chatbot is a generative pre-trained transformer (GPT) model (column 24, disclosing a machine learning system integrating Generative Pre-trained Transformer with ability to recognize its senses beyond computer vision and natural algorithm and it can alert the user (driver) of the intelligent vehicle. Column 64, disclosing Super System on Chip 400A/400B/400C/400D can be sensor-aware and/or context-aware and it can alert the user (driver) of the intelligent vehicle about the intention of other users (drivers of other intelligent vehicles) in proximity).
Mazed and Prasad are analogous art as they are in same field of endeavor i.e., alerting user of vehicle. It would have been obvious to one having ordinary skill in the art before effective filing date of claimed invention to further modify art of Prasad to wherein the chatbot is a generative pre-trained transformer (GPT) model as additional tool to provide alerts to user. Thereby, improving driver awareness.
Claims 8, 9, 14, 15 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Prasad in view of Huerlin (US 20250033533) and Donderici (US 20230256999).
For claim 8, Prasad teaches: The computer-implemented method of claim 1,
Prasad does not teach: wherein detecting the safety issue associated with the maneuver comprises:
generating, by the computing system, and via a machine learning model, a predicted likelihood of the safety issue occurring in association with the maneuver; and
determining, by the computing system, that the predicted likelihood exceeds a threshold likelihood.
Huerlin teaches generating, by the computing system, and via a machine learning model, a predicted likelihood of the safety issue occurring in association with the maneuver ([0279], disclosing machine learning model 902 is trained using data which is general to the vehicle types and is used for detecting a collision probability and thus determining a risk and a risk level)
Huerlin and Prasad are analogous arts as they are in same field of endeavor i.e., predicting collision for vehicle. It would have been obvious to one having ordinary skill in the art before effective filing date of claimed invention to modify art of Prasad to generating, by the computing system, and via a machine learning model, a predicted likelihood of the safety issue occurring in association with the maneuver to determine a collision probability and thus determining a risk and a risk level.
Donderici teaches determining, by the computing system, that the predicted likelihood exceeds a threshold likelihood ([0035], disclosing calculate collision imminency using a kinematic simulation of autonomous vehicle 102 and location and/or shape of other objects (e.g., objects 202, 204), a kinematic simulation of autonomous vehicle 102 and an occupancy map, a machine-learning model of vehicle kinematics and interaction with other objects (e.g., objects 202, 204), planning data generated by planning stack 118, comparison of a collision probability with a threshold)
Denderici and Prasad are analogous arts as they are in same field of endeavor i.e., predicting collision for a vehicle. It would have been obvious to one having ordinary skill in the art before effective filing date of claimed invention to further modify art of Prasad to determining, by the computing system, that the predicted likelihood exceeds a threshold likelihood as taught by Denderici to determine risk revel.
Claim 14 recites limitations similar in scope to claim 8, hence is similarly rejected.
Claim 19 recites limitations similar in scope to claim 8, hence is similarly rejected.
For claim 9, modified Parasad teaches: The computer-implemented method of claim 8, further comprising:
receiving, by the computing system, a training dataset indicative of historical instances of the maneuver (as modified Prasad utilizes machine learning model to determine collision probability. A training dataset indicative of historical instances of the maneuver is necessarily received for machine learning model); and
training, by the computing system, and based upon the training dataset, the machine learning model to identify predictive factors within the training dataset that correspond with the safety issue (a machine learning model is necessarily trained to identify predictive factors within the training dataset that correspond with the safety issue),
wherein the machine learning model generates the predicted likelihood by identifying instances of the predictive factors based upon the sensor data ([0030], disclosing identifying instances to predict collision i.e., turning path of the combination of the host-vehicle 14 and the trailer. And utilizing trailer angle for collision determination).
Claim 15 recites limitations similar in scope to claim 9, hence is similarly rejected.
Claim 10, 11, 16 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Prasad in view of Huerlin, Donderici and Niewiadomski (US 20220230544).
For claim 10, modified Prasad teaches: The computer-implemented method of claim 8,
Prasad does not teach: further comprising:
generating, by the computing system, and via the machine learning model, a predicted action that is likely to avoid the safety issue,
wherein the output recommends the predicted action to the driver.
Niewiadomski teaches generating, by the computing system, a predicted action that is likely to avoid the safety issue, wherein the output recommends the predicted action to the driver (abstract, disclosing a trailer flank contact avoidance system for a vehicle towing a trailer includes a sensor system configured to detect objects in an operating environment of the vehicle. [0028-0029], disclosing providing corrective steering angle and coaching instructions to driver to avoid contacting an object)
Niewiadomski and Prasad are analogous arts as they are in same field of endeavor i.e., collision prediction of vehicle and alerting the driver. It would have been obvious to one having ordinary skill in the art before effective filing date of claimed invention to further modify art of Prasad to further comprising: generating, by the computing system, and via the machine learning model, a predicted action that is likely to avoid the safety issue, wherein the output recommends the predicted action to the driver as taught by Niewiadomski to coach driver in avoiding/correcting the safety issue.
Claim 16 recites limitations similar in scope to claim 10, hence is similarly rejected.
Claim 20 recites limitations similar in scope to claim 10, hence is similarly rejected.
For claim 11, modified Prasad teaches: The computer-implemented method of claim 10, wherein:
the safety issue is associated with at least one of the towable object veering outside a current travel lane or colliding with an external object during the maneuver ([0030], disclosing determine whether a current path of the host-vehicle 14 and trailer 12 may collide with an object or other-vehicle 48, based on the turning path of the combination of the host-vehicle 14 and the trailer. And [0032], disclosing trailer veering outside current lane of travel), and
the predicted action is an action that modifies at least one of a driving speed or driving angle during the maneuver (modification through Niewiadomski teaches of prediction action as modifying driving angle (steering angle)).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ota (US 202202506140) teaches of a risk calculated for collision of vehicle. See [0053].
Venderburgh (US 10583780) teaches of providing collision alerts to operator of vehicle. See column 9.
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/ARSLAN AZHAR/Examiner, Art Unit 3656