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 .
Status of Claims
This is in response to Applicant’s case, no. 18/880,823, with an effective filing date of 2 January 2025. Claims 1-15 are currently pending.
Priority
This is the first office action on the merits of the instant application which was filed 2 January 2025, claiming priority to DE Pat. Pub. No. 10 2022 206 924.2 and 371 of PCT/EP2023/068180, filed 7/6/2022 and 7/3/2023, respectively. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Should applicant desire to obtain the benefit of foreign priority under 35 U.S.C. 119(a)-(d) prior to declaration of an interference, a certified English translation of the foreign application must be submitted in reply to this action. 37 CFR 41.154(b) and 41.202(e).
Failure to provide a certified translation may result in no benefit being accorded for the non-English application. No action by Applicant is requested at this time.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 2 January 2025 is/are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement(s) is/are being considered by the Examiner.
Drawings
Drawings 1-2 are objected to under 37 CFR 1.83(a) because they fail to show: (a) with respect to Fig. 1 details regarding the identifications (i.e.,Fig.1 items s1-s2), as described in the specification and (b) with regard to Fig. 2, details regarding the blocks contained therein (i.e. Fig. 2 items 10a-10b, 12, 14, 16a-16b, 18, 20, 22, 24, D1-D6), as described by the specification. Any structural detail that is essential for a proper understanding of the disclosed invention should be shown in the drawing. MPEP § 608.02(d). Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as "amended." If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either "Replacement Sheet" or "New Sheet" pursuant to 37 CFR 1.121(d). If the changes are not accepted by the Examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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The drawings are further objected to as failing to comply with 37 CFR 1.84(p)(4) because reference characters:
10a (infrastructure data signal), 10b (vehicle sensor data) and 22 (first means for providing at least one infrastructure data signal) (see Fig. 2) have all been used to designate the left box, but it is unclear how these features are related and they can be represented by a single box;
12 (plurality of safety-related vehicle functions), 14 (safety integrity level), 16a (first weighting), 16b (second weighting), 24 (second means for providing at least one infrastructure data signal) (see Fig. 2) have all been used to designate the right box, but it is unclear how these different features are related and can be represented by a single box;
D1-D2 (first and second data corresponding to different sensed data) (see Fig. 2) have all been used to designate the connecting two-way arrow but have different claimed capabilities; and
20 (controller) and D3-D6 (third-to-sixth data corresponding to different control signals) (see Fig. 2) have all been used to designate the overarching box, but it is unclear how these features are related and can be represented by a single box.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
Applicant is reminded of the proper language and format for an abstract of the disclosure.
The abstract should be in narrative form and generally limited to a single paragraph on a separate sheet within the range of 50 to 150 words in length. The abstract should describe the disclosure sufficiently to assist readers in deciding whether there is a need for consulting the full patent text for details.
The language should be clear and concise and should not repeat information given in the title. It should avoid using phrases which can be implied, such as, “The disclosure concerns,” “The disclosure defined by this invention,” “The disclosure describes,” etc. In addition, the form and legal phraseology often used in patent claims, such as “means” and “said,” should be avoided.
See MPEP § 608.01(b) for guidelines for the preparation of patent abstracts.
The abstract of the disclosure is objected to because: it contains phraseology that may be implied (i.e., line 1 “A method is for…,”). A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
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The abstract of the disclosure is further objected to because the abstract is greater than 150 words. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
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The disclosure is further objected to because of the following informalities:
[0016] and [0020] states “at least one infrastructure data signal which represents infrastructure data and at least one vehicle sensor data signal which represents vehicle sensor data” and it is unclear the difference between the two as the Applicant uses the word signal interchangeably with the term data throughout the specification.
Appropriate correction is required.
Claim Objections
Claim(s) 15 is/are objected to because of the following informalities:
Claim 15 (line 1), the claim recites the limitation A non-transitory computer-readable data carrier, however, there is no antecedent basis for the “non-transitory” structure elicited within the claim based on the Applicant’s description (i.e., Applicant describes the “data carrier” in [0022] as merely a computer readable data carrier and does not disclose transitory and/or non-transitory embodiments).
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim(s) 15 is/are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding the preliminarily amended claim 15 (line 1), the original disclosure fails to recite a non-transitory computer-readable data carrier and is, therefore, considered new matter and is rejected as such.
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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(s) 1-13 is/are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the Applicant), regards as the invention.
Regarding claim 1 (i.e., lines 5-7) and claim 13, recites the limitation at least one infrastructure data signal which represents infrastructure data and at least one vehicle sensor data signal which represents vehicle sensor data and it is unclear the difference between signal and data as the Applicant uses the word signal interchangeably with the term data throughout the specification and claims.
Claims 2-12 and 14-15 are rejected as they inherit the rejection of the claim from which they are based.
Further regarding claims 2-13 (e.g., claim 2 line 2 and claim 6 lines 3-4) recite the word signal and it is unclear the difference between signal and data as the Applicant uses the word signal interchangeably with the term data throughout the specification and claims and it is unclear how a signal represents data yet data can comprise a signal.
Further regarding claim 9, the phrase "in particular" is construed as exemplary language which renders the claim indefinite because it is unclear whether the limitation(s) following the phrase are part of the claimed invention (i.e., a Kalman filter or a deep learning based algorithm). See MPEP § 2173.05(d). For purposes of prosecution, the limitation is interpreted to be directed solely toward either a Kalman filter or a deep learning based algorithm.
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The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim(s) 14 is/are rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends.
Regarding claim 14 (lines 2-4), the claim recites the limitation a computer program comprises program code for performing the method when the computer program is executed on a computer. However, claim 1 recites the limitations A computer-implemented method… a model of surroundings of a vehicle, which is construed as a computer program (i.e., model) which necessarily comprises a program code to perform methods when executed on a computer (i.e., a computer-implemented method) and it is unclear how claim 14 further limits claim 1.
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 therefore, subject to the conditions and requirements of this title.
Claim(s) 1-15 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The determination of whether a claim recites patent ineligible subject matter is a two-step inquiry.
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), see MPEP 2106.03, or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis: see MPEP 2106.04
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon? see MPEP 2106.04(II)(A)(1)
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? see MPEP 2106.04(II)(A)(2)
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? see MPEP 2106.05
101 Analysis – Step 1
Claim 1 is directed toward a method for determining required safety integrity level (i.e., a process). Therefore, claims 1 is within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes. see MPEP 2106(A)(II)(1) and MPEP 2106.04(a)-(c)
Independent claim 1 includes limitations that recite an abstract idea (emphasized below [with the category of abstract idea in brackets]) and will be used as a representative claim for the remainder of the 101 rejection.
Claim 1 recites:
A computer-implemented method for determining a required safety integrity level for safety-related vehicle functions of a model of surroundings of a vehicle, the model having a plurality of safety-related vehicle functions [mental process/step], the method comprising:
providing (i) at least one infrastructure data signal which represents infrastructure data, and (ii) at least one vehicle sensor data signal which represents vehicle sensor data, each piece of vehicle sensor data being determined for the plurality of safety-related vehicle functions; and
determining a safety integrity level for the plurality of safety-related vehicle functions based on the provided at least one infrastructure data signal and the at least one vehicle sensor data signal [mental process/step],
wherein a first weighting is added to the vehicle sensor data signal, and a second weighting is added to the infrastructure data signal in order to determine the required safety integrity level for the plurality of safety-related vehicle functions [mental process/step].
The Examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, “determining…”, and “weighting is added…” in the context of this claim encompasses a person looking at data collected and forming a simple judgement. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. see MPEP 2106.04(II)(A)(2) and MPEP 2106.04(d)(2). It must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” [with a description of the additional limitations in brackets], while the bolded portions continue to represent the “abstract idea”.):
A computer-implemented method for determining a required safety integrity level for safety-related vehicle functions of a model of surroundings of a vehicle, the model having a plurality of safety-related vehicle functions, the method comprising:
providing (i) at least one infrastructure data signal which represents infrastructure data, and (ii) at least one vehicle sensor data signal which represents vehicle sensor data, each piece of vehicle sensor data being determined for the plurality of safety-related vehicle functions [insignificant extra-solution activity (data gathering) using generic sensors]; and
determining a safety integrity level for the plurality of safety-related vehicle functions based on the provided at least one infrastructure data signal and the at least one vehicle sensor data signal,
wherein a first weighting is added to the vehicle sensor data signal, and a second weighting is added to the infrastructure data signal in order to determine the required safety integrity level for the plurality of safety-related vehicle functions.
For the following reason(s), the Examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of “providing…,” the Examiner submits that these limitations are insignificant extra-solution activities that merely use a computer (controller) to perform the process. In particular, the providing step from the sensors and/or from an external source are recited at a high level of generality (i.e. as a general means of gathering vehicle, route, and road condition data for use in the determining step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception. see MPEP § 2106.05. Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the Revised Guidance, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a vehicle controller to perform the determining and weighting information… amounts to nothing more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of “providing…,” the Examiner submits that these limitations are insignificant extra-solution activities. The “providing…,” amounts to no more than what is well-understood, routine and conventional activity under TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data or performing functions 'known' in the art.").
Hence, claim 1 is not patent eligible.
Independent claim 13 recites a controller having substantially the same features of claim 1 above, therefore claim 13 is rejected for the same reasons as claim 1.
Dependent claim(s) 2-12, and 14-15 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application as they provide for further examples of mental processes such as determine, select, and weighting and additional limitations that also do not integrate the judicial exception into a practical application such as provide and generate. Therefore, dependent claims 2-12, and 14-15 are not patent eligible under the same rationale as provided for in the rejection of independent claims 1 and 13
Therefore, claim(s) 1-15 is/are ineligible under 35 USC §101.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(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.
Claim(s) 1-4, 6-8, and 10-15 is/are rejected under 102(a)(1) as being anticipated by Heyl et al. (US Pat. Pub. No. 2020/0377122 A1), hereinafter referred to as Heyl.
Regarding claim 1, Heyl discloses:
A computer-implemented method for determining a required safety integrity level for safety-related vehicle functions of a model of surroundings of a vehicle, the model having a plurality of safety-related vehicle functions, ([0013] sentence(s) (s.) 3-4, the electronic based aspects of the invention may be implemented in software, including that of the “controllers” described in the specification can include one or more electronic processors, one or more memories including non-transitory computer-readable media, one or more input/output interfaces, one or more application specific integrated circuits (ASICs) and other circuits, and various connections (for example, wires, printed traces, and busses) connecting the various components; [0033] determine different integrity thresholds that define different levels of risk when involved in driving situations, based at least in part on certain international standards such as International Organization for Standardization (ISO) 26262, the risk is calculated based upon an expected loss or severity in case of an incident and the probability of an incident occurring; and [0035] s. 1-3, if the integrity level is calculated such that an ASIL Level D risk is present, the actions taken may include acceleration, deceleration or braking, and steering the vehicle within the physical limits of the vehicle in order to reduce the risk), the method comprising:
providing (i) at least one infrastructure data signal which represents infrastructure data ([0022] s.1-2, safety architecture software 240 may also include a digital map or global positioning system (GPS) to allow the electronic controller to determine a location of the vehicle and other potential features located at the location of the vehicle and the digital map is a static map of the driving environment illustrating various features of the driving environment; [0034] s.2, if the compared integrity level of a hypothesis meets the threshold for an ASIL Level D hazard, certain actions, such as hard changes in steering angle or rapid acceleration or deceleration, may be selected in order to avoid high risk collisions with objects or other dangerous driving situations; and [0036] s.2, determining that an object is traveling alongside the vehicle in an adjacent lane, where the electronic controller may be configured to prohibit the vehicle from making a lane change in the direction of the detected object until a new hypothesis with a higher integrity level indicating that the object is no longer present alongside the vehicle is selected which are construed as infrastructure data based at least in part on the Applicant’s description of infrastructure in the instant application [0031-36]), and
(ii) at least one vehicle sensor data signal which represents vehicle sensor data, each piece of vehicle sensor data being determined for the plurality of safety-related vehicle functions ([0004] s.2, a control system that generates multiple probabilistic hypotheses… used to actuate vehicle systems; [0018] s.4, plurality of sensors 140-143 can have various sensor types, such as radar sensors, light detection and ranging (LIDAR) sensors, cameras, audio sensors, vibration sensors, accelerometers, gyroscopes, and the like; [0021] s.6, safety architecture software is configured to receive data and metadata from the plurality of sensors via the electronic processor and, amongst other things, perform functions; and [0035] s.1, If the integrity level is calculated such that an ASIL Level D risk is present, the actions taken may include acceleration, deceleration or braking, and steering the vehicle within the physical limits of the vehicle 100 in order to reduce the risk); and
determining a safety integrity level for the plurality of safety-related vehicle functions based on the provided at least one infrastructure data signal and the at least one vehicle sensor data signal ([0003] s.1, fusion of data from multiple sensors, sensor modalities, and other data sources is often performed to obtain a fuller representation of the driving environment; [0032] integrity level can be thought of as a confidence level in a particular hypothesis being the correct outcome for the current driving situation, and can be quantified as, for example, percentage, a number, or a particular status, such as “Confident,” “Careful,” and “Constrained” and the integrity levels can then be compared to integrity thresholds to select a) which actions should be taken based upon the integrity level of different hypotheses and/or b) how to limit certain actions taken based upon the integrity levels; [0033] determine different integrity thresholds that define different levels of risk when involved in driving situations, based at least in part on certain international standards such as International Organization for Standardization (ISO) 26262, the risk is calculated based upon an expected loss or severity in case of an incident and the probability of an incident occurring; and [0035] sentence(s) (s.) 1-3, if the integrity level is calculated such that an ASIL Level D risk is present, the actions taken may include acceleration, deceleration or braking, and steering the vehicle within the physical limits of the vehicle in order to reduce the risk),
wherein a first weighting is added to the vehicle sensor data signal ([0023] s.4, sensor data or each sensor input to the electronic controller is assigned a weight factor by the electronic controller), and a second weighting is added to the infrastructure data signal in order to determine the required safety integrity level for the plurality of safety-related vehicle functions ([0022] s.1-4, where environmental features are stored using a digital map which is deprioritized in the safety architecture software to the sensory inputs that allow the system to update the digital map to form a localization map which is construed as a weighting provided to infrastructure data that is different than the vehicle sensor data).
Claim 13 recites a controller having substantially the same features of claim 1 above, therefore claim 13 is rejected for the same reasons as claim 1
Regarding claim 2, Heyl discloses:
The computer-implemented method according to claim 1, wherein the at least one infrastructure data signal comprises information as to which regional areas of the surrounding of the vehicle have which safety integrity level ([0022] s.1-2, digital map is a static map of the driving environment illustrating various features of the driving environment (e.g., known road signs, driving lanes, or other road or geography features), and [0036] s.2, if the selected hypothesis or final hypothesis indicate that an object is traveling alongside the vehicle in an adjacent lane, the electronic controller may be configured to prohibit the vehicle from making a lane change in the direction of the detected object until a new hypothesis with a higher integrity level indicating that the object is no longer present alongside the vehicle is selected, where the driving environment may necessarily affects the safety integrity levels of the areas surrounding the vehicle (e.g., contain lane closures, construction signage, reduced speed limits, or other infrastructure data)).
Regarding claim 3, Heyl discloses:
The computer-implemented method according to claim 1, wherein the at least one infrastructure data signal comprises information about static obstacles, a traffic infrastructure, and/or dynamic objects ([0022] s.2, the digital map is a static map of the driving environment illustrating various features of the driving environment; [0034] s.2, if the compared integrity level of a hypothesis meets the threshold for an ASIL Level D hazard, certain actions, such as hard changes in steering angle or rapid acceleration or deceleration, may be selected in order to avoid high risk collisions with objects or other dangerous driving situations; and [0036] s.2, determining that an object is traveling alongside the vehicle in an adjacent lane, where the electronic controller may be configured to prohibit the vehicle from making a lane change in the direction of the detected object until a new hypothesis with a higher integrity level indicating that the object is no longer present alongside the vehicle is selected which are construed as infrastructure data based at least in part on the Applicant’s description of infrastructure in the instant application [0031-36]).
Regarding claim 4, Heyl discloses:
The computer-implemented method according to claim 1,wherein the at least one infrastructure data signal comprises information about (i) a type of objects occurring with a predetermined probability in regional areas of the surroundings of the vehicle, and (ii) a type of objects not occurring with a predetermined probability in regional areas of the surroundings of the vehicle ([0003] the gathering of sensor data and the processing of the sensor data is based upon probabilistic algorithms, however, using probabilistic algorithms may lead to incorrect classification of objects or dangers, incorrect tracking of objects, missed detection of objects, the detection of “ghost” objects (objects that are “detected” that are not actually present in the driving environment), incorrect target selection, and incorrect kinematic estimation of objects (for example, a speed of an object is incorrectly calculated) and [0004] a control system is needed to better process these probabilistic inputs and generate a control solution based upon the various probabilistic hypotheses generated based upon the data fusion of the multiple sensors, which is construed as a solution to the problem described in [0003] above where information about a type of object that is probabilistically occurring or not occurring in an area surrounding the vehicle).
Regarding claim 6, Heyl discloses:
The computer-implemented method according to claim 1,wherein, based on the determined safety integrity level for the plurality of safety-related vehicle functions, first data, including a control signal for controlling at least one vehicle sensor, is generated which represents the sensor modalities, including video, radar, lidar, ultrasonic, and/or microphone, with which regional areas of the surroundings of the vehicle are to be covered by vehicle sensors ([0018] s.4, plurality of sensors 140-143 can have various sensor types, such as radar sensors, light detection and ranging (LIDAR) sensors, cameras, audio sensors, vibration sensors, accelerometers, gyroscopes, and the like).
Regarding claim 7, Heyl discloses:
The computer-implemented method according to claim 1, wherein, based on the determined safety integrity level for the plurality of safety-related vehicle functions, second data, including a control signal for controlling at least one vehicle sensor, is generated which represents sensor redundancy, sensor resolution, and/or sensor measurement frequency, with which regional areas of the surroundings of the vehicle are to be covered ([0018] s.6, plurality of sensors also send metadata about the operation of each sensor, such as operating status, error code, and other data, to the electronic controller; [0029] s.2, if the received metadata indicates that a radar sensor of the plurality of sensors is not operating correctly, hypotheses including determinations based upon radar data may be determined to have a low integrity level. In addition, such hypotheses may be excluded from the determination of a final hypothesis; [0030] s.2, having a single point of failure does not impact the performance of the entire system to a degree that causes system safety and performance problems; and [0031] s.2, if a particular probability hypothesis relied on only two sensors, and one of the sensors delivers an operating status of “inoperative” or “faulty” to the electronic controller, the integrity level of that particular hypothesis may be reduced or downgraded because the determination now only relies on one correctly operating sensor or other data source, which are construed as a redundant system of sensors such that if a sensor is deemed faulty or less than optimal, the remainder of the system operates as to insure the proper performance of the system as a whole).
Regarding claim 8, Heyl discloses:
The computer-implemented method according to claim 1, wherein, based on the determined safety integrity level for the plurality of safety-related vehicle functions, third data, including a control signal, is generated for weighting perception functions ([0023] s.4, sensor data or each sensor input to the electronic controller is assigned a weight factor by the electronic controller, Heyl does not explicitly disclose the limitation) object models ([0026] s.1, determine a plurality of hypotheses indicating how close an object is to the vehicle, construed as an object model), and/or movement models regarding their suitability for sensing vehicle surroundings ([0036] s.2, selected hypothesis or final hypothesis indicate that an object is traveling alongside the vehicle 100 in an adjacent lane, which is construed as a movement model).
Regarding claim 10, Heyl discloses:
The computer-implemented method according to claim 1, wherein, based on the determined safety integrity level for the plurality of safety-related vehicle functions, fifth data, including a control signal, is generated to set at least one limit value of an object detector ( [0027] s.2, metadata of each of the plurality of sensors is analyzed to determine if any faults or limitations are present in the plurality of sensors; [0036] s.1, action taken may also include limiting or prohibiting behaviors of the vehicle; and [0031] s.2, if a particular probability hypothesis relied on only two sensors, and one of the sensors delivers an operating status of “inoperative” or “faulty” to the electronic controller, the integrity level of that particular hypothesis may be reduced or downgraded because the determination now only relies on one correctly operating sensor or other data source, which is construed as a limit value for an object detector).
Regarding claim 11, Heyl discloses:
The computer-implemented method according to claim 1, wherein, based on the determined safety integrity level for the plurality of safety-related vehicle functions, sixth data, including a control signal for selecting a controller for carrying out the safety-related vehicle functions, is generated ([0004] s.3, that these hypotheses are used to support the selection of a final hypothesis and to select a vehicle control to achieve or enhance safety of the intended functionality (“SOTIF”); [0035] sentence(s) (s.) 1-3, if the integrity level is calculated such that an ASIL Level D risk is present, the actions taken may include acceleration, deceleration or braking, and steering the vehicle within the physical limits of the vehicle in order to reduce the risk; and [0038] s.1, that electronic controller is configured to initiate the determined action by sending a signal to a system of the vehicle associated with the determined action).
Regarding claim 12, Heyl discloses:
The computer-implemented method according to claim 1, wherein the at least one infrastructure data signal is provided before or when traversing a path portion sensed by vehicle sensors ([0022] s.2, the digital map is a static map of the driving environment illustrating various features of the driving environment; [0034] s.2, if the compared integrity level of a hypothesis meets the threshold for an ASIL Level D hazard, certain actions, such as hard changes in steering angle or rapid acceleration or deceleration, may be selected in order to avoid high risk collisions with objects or other dangerous driving situations; and [0036] s.2, determining that an object is traveling alongside the vehicle in an adjacent lane, where the electronic controller may be configured to prohibit the vehicle from making a lane change in the direction of the detected object until a new hypothesis with a higher integrity level indicating that the object is no longer present alongside the vehicle is selected which are construed as infrastructure data based at least in part on the Applicant’s description of infrastructure in the instant application [0031-36], which is construed as the infrastructure data being provided before and/or when traversing a vehicle sensed path).
Regarding claim 14, Heyl discloses:
The computer-implemented method according to claim 1, wherein a computer program comprises program code for performing the method when the computer program ([0013] computer modules in which are construed as computer programming comprising code that is executed on “controllers” that can include one or more electronic processors, one or more memories including non-transitory computer-readable media, one or more input/output interfaces, one or more application specific integrated circuits (ASICs) and other circuits).
Regarding claim 15, Heyl discloses:
A non-transitory computer-readable data carrier comprising the program code according to claim 14 ([0013] s.1-3 plurality of hardware and software-based devices (e.g., stored on non-transitory computer-readable media) executable by one or more electronic controllers or electronic processors).
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:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claim(s) 5 and 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Heyl et al. (US Pat. Pub. No. 2020/0377122 A1), hereinafter referred to as Heyl, in view of Jin et al. (US Pat. No. 12,560,702), hereinafter referred to as Jin.
Regarding claim 5, Heyl discloses:
The computer-implemented method according to claim 1, wherein the at least one infrastructure data signal (infrastructure data in [0022], [0034], and [0036] as discussed above), Heyl does not explicitly disclose
infrastructure data signal comprises information about a traffic density, a time, weather, light conditions, and/or a sun position.
However, Jin teaches in col 34 ln 37-39 that map information includes information regarding traffic and road conditions, which is construed infrastructure data comprising information regarding traffic density.
Therefore, it would have been obvious to one of ordinary skill in the art of vehicle controls, navigation, and automotive safety-integrated risk management before the effective filing date of the current invention to modify the vehicle control and safety architecture of Heyl, by incorporating the machine learning model teachings of Jin, such that the combination would provide for the predictable result of, as acknowledged by Jin in col 1 ln 6-7, safely driving a vehicle autonomously without human supervision.
Regarding claim 9, Heyl discloses:
The computer-implemented method according to claim 1, wherein, based on the determined safety integrity level for the plurality of safety-related vehicle functions, fourth data, including a control signal, is generated to select an algorithm type, in particular a Kalman filter or a deep learning based algorithm.
However, Jin teaches in col 5 ln 31-32 systems for performing deep learning operations. Furthermore, Jin teaches in col 10 ln 65 - col 11 ln 9 that one or more machine learning models may include any type of machine learning model, such as a machine learning model(s) using linear regression, logistic regression, decision trees, support vector machines (SVM), Naive Bayes, k-nearest neighbor (Knn), K means clustering, random forest, dimensionality reduction algorithms, gradient boosting algorithms, neural networks (e.g., auto-encoders, convolutional, recurrent, perceptrons, long/short term memory/LSTM, Hopfield, Boltzmann, deep belief, deconvolutional, generative adversarial, liquid state machine, etc.), lane detection algorithms, computer vision algorithms, and/or other types of machine learning models, which is construed as a system selecting a type of algorithm including deep learning or Kalman filtering.
Therefore, it would have been obvious to one of ordinary skill in the art of vehicle controls, navigation, and automotive safety-integrated risk management before the effective filing date of the current invention to modify the vehicle control and safety architecture of Heyl, by incorporating the machine learning model teachings of Jin, such that the combination would provide for the predictable result of, as acknowledged by Jin in col 1 ln 6-7, safely driving a vehicle autonomously without human supervision.
Prior Art
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure. Please see:
Jin et al. (US Pat. Pub. No. 2026/0140256 A1) is directed towards sampling and transmitting the most useful information from a radar signal representing a scene while staying within the computational and storage confines of a standard automotive radar sensor and the bandwidth constraints of a standard communication link between a radar sensor and processing unit;
Goyal et al. (US Pat. Pub. No. 2024/0371082 A1) is directed towards an area of interest may correspond to a predicted location of an object in the environment, such as an object that an autonomous machine is instructed to manipulate, the system magnifies the area of interest, and then uses the rendered images to make predictions related to key-frame poses associated with a future state of the autonomous machine; and
Khastgir et al. article “Introducing ASIL inspired dynamic tactical safety decision framework for automated vehicles” is directed towards an ASIL inspired dynamic tactical safety framework, which evaluates the severity, controllability and exposure ratings in real-time based on the real time values of the various vehicle and environment parameters.
Conclusion
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to KEITH ALLEN VON VOLKENBURG whose telephone number is (703)756-5886. The Examiner can normally be reached Monday-Friday 8:30 am-5:00 pm.
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If attempts to reach the Examiner by telephone are unsuccessful, the Examiner’s supervisor, Erin D. Bishop can be reached at (571) 270-3713. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Keith A von Volkenburg/ Examiner, Art Unit 3665
/TIFFANY P YOUNG/Primary Examiner, Art Unit 3665
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