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 action is in response to the Applicant’s arguments and amendments filed on 3/05/2026. Applicant amended claims 1, 5, 10, 14 and 19. Claims 1-20 are pending and are examined below.
RESPONSE TO REMARKS AND ARGUMENTS
In regards to the objections to the specification, Applicant’s amendment to the specification filed on 3/05/2026 obviates this issue – accordingly, the objections to the specification are withdrawn.
In regards to the claim rejections under § 112(b), Applicant’s amendments filed on 3/05/2026 obviate said rejections – accordingly, the claim rejections under § 112(b) are withdrawn.
In regards to the claim rejections under § 101, Applicant’s amendments filed on 3/05/2026 obviate said rejections. Namely, the claims now recite positive actuation of structure through vehicle control. Accordingly, the claim rejections under § 101 are withdrawn.
In regards to the claim rejections under § 103, Applicant’s amendments and arguments filed on 3/05/2026 have been fully considered but are unpersuasive.
As to amended claim 1, Applicant argues that Bernhard does not teach or suggest the recited determination of extreme values within the recited partial time intervals starting at a present point in time. Applicant submits that Bernhard merely identifies characteristic points based on curve geometry, rather than based on being within defined partial time intervals beginning at a present point in time. Hence, Applicant argues that Bernhard’s discretization intervals Δt are used only for sampling or approximating a curve rather than for determining extreme values within defined time intervals. Applicant further argues that Bernhard does not disclose the “transmitting” step as Bernhard’s supporting points are used internally within the curve approximation process to generate a representation of the forecast curve.
Examiner respectfully disagrees. The combination of Bernhard and Sans arrives the broadest reasonable interpretation (BRI) of the claim limitations at issue.
To begin, Bernhard discloses the following:
determining at least one first extreme value of the forecasted progression within a first partial time interval of the predefined time interval starting at a present point in time (“Analysis unit 104 of control device 100 can select characteristic values Ws of forecast curve 106 for example at minima, maxima or turning points of forecast curve 106. Minima, Maxima and turning points can be determined especially easily within the scope of a curve discussion of forecast curve 106.” Emphases added, ¶ 92; see also FIG. 2A.);
determining at least one second extreme value of the forecasted progression within a second partial time interval of the predefined time interval starting at the present point in time, the second partial time interval being longer than the first partial time interval (“Analysis unit 104 of control device 100 can select characteristic values Ws of forecast curve 106 for example at minima, maxima or turning points of forecast curve 106. Minima, Maxima and turning points can be determined especially easily within the scope of a curve discussion of forecast curve 106.” Emphases added, ¶ 92; see also FIG. 2A. Continuing: FIG. 2B illustrates a “forecast curve …, wherein the selected points in time ts of the set supporting points (Ws, ts)—in the current example eight time points ts=t1′, . . . t8′—have variable time intervals Δt1′ . . . Δt8′. In addition, due to variable and sometimes greater time intervals Δt1′ . . . Δt8′ approximation occurs in the embodiment shown in FIG. 2B in regard to an extended forecast horizon 220, compared to the described approximation in the embodiment shown in FIG. 1B. For example, time interval Δt8′—as is the case between characteristic time points 17′ and 18′—is greater here than time intervals Δt in the example from the state of the art in FIG. 1A.” ¶ 100 and FIG. 2B. Note: Summarizing, extreme values may be determined for a forecasted progression of a parameter over an overall time period, wherein the time period has at least a first partial time interval (e.g., Δt1) and a second partial time interval (e.g., Δt8 or Δt1-Δt8) which is longer than the first time interval.)
Summarizing, Bernhard discloses that, within a predefined time interval starting at a present point in time, at least first and second extrema may be determined, wherein the second extrema is located in a second partial time interval longer than a first partial time interval. Notably, the notion that the first and second partial time intervals start at the same point in time appears to differ from what the BRI of the claim puts forth. That is, the claim rather states that the predefined time interval, from which the first and second predefined partial time intervals are procured, starts at a present point in time. Following this interpretation, Bernhard cleanly reads on the claim limitations at issue.
Even assuming arguendo that the BRI of the claim requires that the partial time intervals begin at the same time, Bernhard would still read on the claim limitations at issue. That is, from Bernhard’s FIG. 2B a PHOSITA would understand that Bernhard calculates extrema for the interval Δt1’ and for the interval Δt1’ – Δt8’. Thus, Bernhard discloses the crux of the claimed invention of calculated extrema within the claimed time intervals over a predefined time interval which starts at a present point in time.
Along the same thread, Examiner submits that the claim does not require that time intervals are first defined and then examined for determining local extrema. Rather, the claim states that extreme values of a forecasted progression are determined within the claimed intervals. In this regard, Examiner submits that Applicant’s arguments pertaining to the foregoing hinge on narrower language than what the BRI of the claim puts forth, and that Bernhard discloses the BRI of the claim limitations at issue.
Addressing the “transmitting” limitation, Bernhard provides the foundation of transmitting a determined at least one first extreme value and a determined at least one second extreme value as the predictive information to a control unit and/or to a software module (See Bernhard, ¶ 92.). Here, Examiner notes that Bernhard reads on the BRI of “transmitting” because the determined values are necessarily transmitted to the analysis unit 104 to perform its processing vis-à-vis the determined extrema. Critically, Sans teaches the BRI of the entire claim limitation at issue:
transmitting predictive information to a control unit of a motor vehicle to determine an activation command for at least one function of the vehicle by evaluating the transmitted predictive information (Disclosed is “a method for optimizing the energy consumption of a motor vehicle;” involving “a computer for managing the drive train of the motor vehicle on a predetermined route, the computer being capable of controlling the internal combustion … and the electric machine;” and the method comprises at least the steps of: “a) defining a prediction period starting from the initial time, b) determining the maximum theoretical variation of each state variable from the initial value of said state variable and over the prediction period so that each state variable satisfies all of the state constraints specific thereto.” ¶ 9.).
A PHOSITA would have motivated to modify Bernhard with Sans with a reasonable expectation of success because Sans’ feature is useful to “to optimize the energy consumption of the drive train on a given or predicted route.” (Sans, ¶ 2.) And as Bernhard also involves control of a drive system of a vehicle, one of ordinary skill in the art would have recognized that Bernhard’s disclosure can with a reasonable expectation of success apply to Sans’ drive train of a motor vehicle.
Accordingly, the claim rejections under § 103 are maintained.
CLAIM INTERPRETATION
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: “a control unit configured to determine,” “a forecasting module configured to forecast,” “a processing module configured to determine” and “a communication module configured to transmit” in claim 10 (with dependent claims 11-18).
The corresponding structure described in the specification as performing the claimed function at least includes:
a control unit configured to determine
processor (PGPUB ¶ 11)
a forecasting module configured to forecast
“The forecasting of the progression, the determination of the extreme values, and their transmission to the control unit 2 are carried out by a predictor or prediction module in the motor vehicle 1, referred to here as the further control unit 6.” (PGPUB ¶ 59.)
“The motor vehicle 1 includes a further control unit 6, which can alternatively be a software module in the vehicle, such as within the control unit 2.” (PGPUB ¶ 45.)
From the foregoing, the disclosed processor can be considered as corresponding structure.
a processing module configured to determine
Through a similar analysis as performed for the forecasting module, the corresponding structure is a processor.
a communication module configured to transmit
Through a similar analysis as performed for the forecasting module, the corresponding structure is a processor.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
Because these claim limitation(s) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
CLAIM REJECTIONS—35 U.S.C. § 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 for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. § 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-5, 9-14 and 18 is/are rejected under § 103 as being unpatentable over Bernhard et al. (US20220276624A1; “Bernhard”) in view of Sans (US20250145144A1; “Sans”).
As to claim 1, Bernhard discloses a method for transmitting predictive information to a control unit of a vehicle to determine an activation command for at least one function of the vehicle by evaluating the transmitted predictive information (“FIG. 1A shows an arrangement 15 with a control device 10 for controlling a technical system 12.” ¶ 73. “A technical system 12 may for example be a drive system, such as a drive system for a ship or a drive system for a rail vehicle.” ¶ 75.), the method comprising:
forecasting a progression of a vehicle parameter of the vehicle for a predefined time interval (“It is the purpose of such a control device 10 to control a technical system 12, inter alia with regard to a target value by taking into account a known or currently postulated and communicated forecast curve 6.” ¶ 76; see also FIGS. 1A-3.);
determining at least one first extreme value of the forecasted progression within a first partial time interval of the predefined time interval starting at a present point in time (“Analysis unit 104 of control device 100 can select characteristic values Ws of forecast curve 106 for example at minima, maxima or turning points of forecast curve 106. Minima, Maxima and turning points can be determined especially easily within the scope of a curve discussion of forecast curve 106.” Emphases added, ¶ 92; see also FIG. 2A.);
determining at least one second extreme value of the forecasted progression within a second partial time interval of the predefined time interval starting at the present point in time, the second partial time interval being longer than the first partial time interval (“Analysis unit 104 of control device 100 can select characteristic values Ws of forecast curve 106 for example at minima, maxima or turning points of forecast curve 106. Minima, Maxima and turning points can be determined especially easily within the scope of a curve discussion of forecast curve 106.” Emphases added, ¶ 92; see also FIG. 2A. Continuing: FIG. 2B illustrates a “forecast curve …, wherein the selected points in time ts of the set supporting points (Ws, ts)—in the current example eight time points ts=t1′, . . . t8′—have variable time intervals Δt1′ . . . Δt8′. In addition, due to variable and sometimes greater time intervals Δt1′ . . . Δt8′ approximation occurs in the embodiment shown in FIG. 2B in regard to an extended forecast horizon 220, compared to the described approximation in the embodiment shown in FIG. 1B. For example, time interval Δt8′—as is the case between characteristic time points 17′ and 18′—is greater here than time intervals Δt in the example from the state of the art in FIG. 1A.” ¶ 100 and FIG. 2B. Note: Summarizing, extreme values may be determined for a forecasted progression of a parameter over an overall time period, wherein the time period has at least a first partial time interval (e.g., Δt1) and a second partial time interval (e.g., Δt8 or Δt1-Δt8) which is longer than the first time interval.); and
transmitting the determined at least one first extreme value and the determined at least one second extreme value as the predictive information to the control unit and/or to the software module (“Analysis unit 104 of control device 100 can select characteristic values Ws of forecast curve 106 for example at minima, maxima or turning points of forecast curve 106. Minima, Maxima and turning points can be determined especially easily within the scope of a curve discussion of forecast curve 106.” Emphasis added, ¶ 92; see also FIG. 2A. Note: The determined values are necessarily transmitted to the analysis unit 104 to perform its processing vis-à-vis the determined extrema).
Bernhard fails to explicitly disclose:
performing the above features in relation to a motor vehicle; and
causing the control unit and/or the software module to execute the activation command to activate, deactivate, or pause the function of the motor vehicle based on the transmitted predictive information.
Nevertheless, Sans teaches:
transmitting predictive information to a control unit of a motor vehicle to determine an activation command for at least one function of the vehicle by evaluating the transmitted predictive information (Disclosed is “a method for optimizing the energy consumption of a motor vehicle;” involving “a computer for managing the drive train of the motor vehicle on a predetermined route, the computer being capable of controlling the internal combustion … and the electric machine;” and the method comprises at least the steps of: “a) defining a prediction period starting from the initial time, b) determining the maximum theoretical variation of each state variable from the initial value of said state variable and over the prediction period so that each state variable satisfies all of the state constraints specific thereto.” ¶ 9.); and
causing the control unit and/or the software module to execute the activation command to activate, deactivate, or pause the function of the motor vehicle based on the transmitted predictive information (“The computer 40 is capable of controlling each device to which it is connected, by issuing a setpoint, as a function of the value or values of variables relating to said device.” ¶ 50.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Bernhard to include the feature of: transmitting predictive information to a control unit of a motor vehicle to determine an activation command for at least one function of the vehicle by evaluating the transmitted predictive information; and causing the control unit and/or the software module to execute the activation command to activate, deactivate, or pause the function of the motor vehicle based on the transmitted predictive information, as taught by Sans, with a reasonable expectation of success because these features are useful to “to optimize the energy consumption of the drive train on a given or predicted route.” (Sans, ¶ 2.) As Bernhard also involves control of a drive system of a vehicle, one of ordinary skill in the art would have recognized that Bernhard’s disclosure can with a reasonable expectation of success apply to Sans’ drive train of a motor vehicle.
Independent claim 10 is rejected for at least the same reasons as claim 1 as the claim recites similar subject matter but for minor differences.
As to claims 2 and 11, Bernhard discloses: wherein the control unit receives the at least one first extreme value and the at least one second extreme value (“Analysis unit 104 of control device 100 can select characteristic values Ws of forecast curve 106 for example at minima, maxima or turning points of forecast curve 106. Minima, Maxima and turning points can be determined especially easily within the scope of a curve discussion of forecast curve 106.” Emphases added, ¶ 92; see also FIG. 2A.).
Bernhard fails to explicitly disclose: check whether at least one of the extreme values is within a predefined value range, and wherein an activation command according to which the function of the motor vehicle is activated is determined and executed if at least one of the extreme values is within the predefined value range.
Nevertheless, Sans teaches: checking whether at least a value is within a predefined value range, and wherein an activation command according to which the function of the motor vehicle is activated is determined and executed if the value is within the predefined value range (“The method … comprises a step E3 of determining the maximum theoretical variation of each state variable.” Emphasis added; ¶ 69. See also ¶¶ 76 and 79 which concrete examples of the maximum theoretical variation – e.g., a maximum theoretical variation may be 2 °C at each timestep. Continuing, “[w]hen the step E3 of determining the maximum theoretical variation of each state variable has been carried out, the method then comprises a step E4 of determining the range of applicable setpoints.” ¶ 81. “During the step E4 of determining the range of applicable setpoints, the computer 40 excludes the values of each setpoint that do not satisfy at least one state constraint applied to a state variable associated with said setpoint.” ¶ 86. Finally, “the computer 40 is capable of controlling each device to which it is connected, by issuing a setpoint, as a function of the value or values of variables relating to said device.” ¶ 50. NOTE: Summarizing, Sans’ maximum theoretical variation analogizes to a predefined value range as it defines a range in which a predicted progression of a vehicle parameter must be within to be considered as valid as opposed to being excluded. Then, a computer 40 controls a vehicle device according to setpoints determined by the foregoing process.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Bernhard to include the feature of: checking whether at least a value is within a predefined value range, and wherein an activation command according to which the function of the motor vehicle is activated is determined and executed if the value is within the predefined value range, as taught by Sans, with a reasonable expectation of success because this feature is useful to “to optimize the energy consumption of the drive train on a given or predicted route.” (Sans, ¶ 2.) Indeed, note well that Bernhard FIG. 2B appears to illustrate an upper threshold “S” under which extreme values fall below. Given at least this context, one of ordinary skill in the art would have been motivated to apply Sans’ teaching to Bernhard to further ensure that the extreme values of a progression of a forecasted vehicle parameter are within acceptable ranges, thereby optimizing operation of a drive train as desired by both Bernhard and Sans.
As to claims 3 and 12, Bernhard discloses: wherein the activation command according to which the function of the vehicle is activated is only determined and executed when the at least one first extreme value and the at least one second extreme value were not forecast for the same point in time (“Analysis unit 104 of control device 100 can select characteristic values Ws of forecast curve 106 for example at minima, maxima or turning points of forecast curve 106. Minima, Maxima and turning points can be determined especially easily within the scope of a curve discussion of forecast curve 106.” Emphasis added, ¶ 92; see also FIG. 2A-2B. Also, “component 108 is controlled on the basis of the approximated forecast curve.” ¶ 113; see also ¶¶ 109-112 and FIG. 4. NOTE: As illustrated in at least FIG. 2B, the determined minima and maxima are necessarily not forecast at the same point in time.).
Bernhard fails to explicitly disclose: wherein the activation command according to which the function of the motor vehicle is activated is only determined and executed when the at least one first extreme value and the at least one second extreme value are within the predefined value range.
Nevertheless, Sans teaches: wherein an activation command according to which a function of a motor vehicle is activated is only determined and executed when the at least one first extreme value and the at least one second extreme value are within a predefined value range (“The method … comprises a step E3 of determining the maximum theoretical variation of each state variable.” Emphasis added; ¶ 69. See also ¶¶ 76 and 79 which concrete examples of the maximum theoretical variation – e.g., a maximum theoretical variation may be 2 °C at each timestep. Continuing, “[w]hen the step E3 of determining the maximum theoretical variation of each state variable has been carried out, the method then comprises a step E4 of determining the range of applicable setpoints.” ¶ 81. “During the step E4 of determining the range of applicable setpoints, the computer 40 excludes the values of each setpoint that do not satisfy at least one state constraint applied to a state variable associated with said setpoint.” ¶ 86. Finally, “the computer 40 is capable of controlling each device to which it is connected, by issuing a setpoint, as a function of the value or values of variables relating to said device.” ¶ 50. NOTE: Summarizing, Sans’ maximum theoretical variation analogizes to a predefined value range as it defines a range in which a predicted progression of a vehicle parameter must be within to be considered as valid as opposed to being excluded. Then, a computer 40 controls a vehicle device according to setpoints determined by the foregoing process.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Bernhard to include the feature of: wherein an activation command according to which a function of a motor vehicle is activated is only determined and executed when the at least one first extreme value and the at least one second extreme value are within a predefined value range, as taught by Sans, with a reasonable expectation of success because this feature is useful to “to optimize the energy consumption of the drive train on a given or predicted route.” (Sans, ¶ 2.) Indeed, note well that Bernhard FIG. 2B appears to illustrate an upper threshold “S” under which extreme values fall below. Given at least this context, one of ordinary skill in the art would have been motivated to apply Sans’ teaching to Bernhard to further ensure that the extreme values of a progression of a forecasted vehicle parameter are within acceptable ranges, thereby optimizing operation of a drive train as desired by both Bernhard and Sans.
As to claims 4 and 13, Bernhard discloses: wherein the respective at least one extreme value describes a maximum and/or a minimum of the progression (“Analysis unit 104 of control device 100 can select characteristic values Ws of forecast curve 106 for example at minima, maxima or turning points of forecast curve 106. Minima, Maxima and turning points can be determined especially easily within the scope of a curve discussion of forecast curve 106.” Emphasis added, ¶ 92; see also FIG. 2A-2B.).
As to claims 5 and 14, Bernhard discloses: wherein an activation command according to which the function is not activated is determined and executed when: the at least one first extreme value and the at least one second extreme value describe a maximum of the forecasted progression corresponding to a same forecast point in time; and the at least one first extreme value and the at least one second extreme value describe minima of the forecasted progression corresponding to different forecast points in time that lie outside the predefined value range (“Analysis unit 104 of control device 100 can select characteristic values Ws of forecast curve 106 for example at minima, maxima or turning points of forecast curve 106. Minima, Maxima and turning points can be determined especially easily within the scope of a curve discussion of forecast curve 106.” Emphasis added, ¶ 92; see also FIG. 2A-2B. Also, “component 108 is controlled on the basis of the approximated forecast curve.” ¶ 113; see also ¶¶ 109-112 and FIG. 4. Note: Focusing on FIG. 2B, note well that at least time instance t5’ shows that a maximum W5 may be calculated which would constitute a maximum at the same point in time for both intervals Δt5’ and Δt6’. Further note that the minima associated with intervals Δt5’ and Δt6’ are necessarily outside the threshold “S” (discussed in ¶ 106). Hence, a control (which one of ordinary skill in the art would understand to include activating and deactivating of functions as appropriate) may be performed when the claimed conditions are met.).
As to claims 9 and 18, Bernhard discloses: wherein the function of the vehicle relates to a drive device of the vehicle, and the activation command predefines an operating strategy for the drive device (“FIG. 1A shows an arrangement 15 with a control device 10 for controlling a technical system 12.” ¶ 73. “A technical system 12 may for example be a drive system, such as a drive system for a ship or a drive system for a rail vehicle.” ¶ 75.).
Bernhard fails to explicitly perform the above in relation to a motor vehicle.
Nevertheless, Sans teaches: wherein the function of the motor vehicle relates to a drive device of the motor vehicle, and the activation command predefines an operating strategy for the drive device (Disclosed is “a method for optimizing the energy consumption of a motor vehicle;” involving “a computer for managing the drive train of the motor vehicle on a predetermined route, the computer being capable of controlling the internal combustion … and the electric machine.” ¶ 9.).
Bernhard discloses: a method for transmitting predictive information to a control unit of a vehicle to determine an activation command for at least one function of the vehicle by evaluating the transmitted predictive information, wherein the method comprises the steps of determining first and second extreme values over an overall time period, wherein the time period has at least a first partial time interval associated with a first extreme value and a second partial time interval which is associated with a second extreme value and which is longer than the first time interval, wherein the function of the vehicle relates to a drive device of the vehicle, and the activation command predefines an operating strategy for the drive device. Sans teaches: a control unit of a motor vehicle evaluating predictive information to determine an activation command for at least one function of the motor vehicle, wherein the function of the motor vehicle relates to a drive device of the motor vehicle, and the activation command predefines an operating strategy for the drive device.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Bernhard to include the feature of: wherein the function of the motor vehicle relates to a drive device of the motor vehicle, and the activation command predefines an operating strategy for the drive device as taught by Sans, with a reasonable expectation of success because this feature is useful to “to optimize the energy consumption of the drive train on a given or predicted route.” (Sans, ¶ 2.) As Bernhard also involves control of a drive system of a vehicle, one of ordinary skill in the art would have recognized that Bernhard’s disclosure can with a reasonable expectation of success apply to Sans’ drive train of a motor vehicle.
Claims 6-8 and 15-17 are rejected under § 103 as being unpatentable over Bernhard in view of Sans as applied to claim 1 – further in view of Schmüdderich et al. (US20160325743A1; “Schmüdderich”).
As to claims 6 and 15, the combination of Bernhard and Sans fails to explicitly disclose: wherein the progression of the vehicle parameter is forecast by applying a forecasting criterion to at least one portion of sensor information detected by a sensor device of the motor vehicle.
Nevertheless, Schmüdderich teaches: wherein the progression of the vehicle parameter is forecast by applying a forecasting criterion to at least one portion of sensor information detected by a sensor device of the motor vehicle (“In FIG. 1 an overview over an advanced driver assistance system 1 comprising a prediction system 2 used for predicting a future movement behavior as one example of an estimated future state of at least one target object (vehicle) and including a global scene context (GSC) unit 3. As shown in FIG. 1 data 10 related to (or describing) a traffic environment of the host vehicle is acquired from one or more sensors, 6.1, 6.2, 6.3 . . . . The sensors 6.1, 6.2, . . . may be of different types or may be of the same type and can in particular be mounted on the host vehicle such that in particular the forward driving direction of the host vehicle can be observed. The sensors 6.1, 6.2, 6.3, . . . are configured to measure the relative speed, position or any other variable that allows to determine the relation between a plurality of traffic participants including the host vehicle.” ¶ 33 and FIG. 1. See also ¶¶ 37-38.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Bernhard and Sans to include the feature of: wherein the progression of the vehicle parameter is forecast by applying a forecasting criterion to at least one portion of sensor information detected by a sensor device of the motor vehicle, as taught by Schmüdderich, with a reasonable expectation of success because this feature is useful for “describing an estimated future state of … the ego-vehicle.” (Schmüdderich, ¶ 10.)
As to claims 7 and 16, the combination of Bernhard and Sans fails to explicitly disclose: wherein a reliability value, which describes a reliability of the forecast of the progression in the respective partial time interval, is determined for the respective extreme value and is transmitted, the control unit and/or the software module utilizing the determined reliability values during the determination of the activation command.
Nevertheless, Schmüdderich teaches: wherein a reliability value, which describes a reliability of the forecast of the progression in the respective partial time interval, is determined and is transmitted, the control unit and/or the software module utilizing the determined reliability values during the determination of the activation command (“The prediction system unit 2 provides a prediction result 15 to a vehicle actuation means 17 and causes either directly actuating controls of the host vehicle such as steering, brakes or throttle on the basis of the prediction result 15 or by means of a controlling unit not shown in FIG. 1.” ¶ 35. Additionally, “[a] “confidence value for weighting the prediction result may be determined” ¶ 17.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Bernhard and Sans to include the feature of: wherein a reliability value, which describes a reliability of the forecast of the progression in the respective partial time interval, is determined and is transmitted, the control unit and/or the software module utilizing the determined reliability values during the determination of the activation command, as taught by Schmüdderich, to yield the claim limitations at issue with a reasonable expectation of success because this feature is useful for “describing an estimated future state of … the ego-vehicle.” (Schmüdderich, ¶ 10.) Furthermore, one of ordinary skill in the art would have recognized that Schmüdderich’s confidence value would apply to Bernhards’ extreme values as Schmüdderich’s confidence value indicates the reliability of a forecast progression in given time interval – such mirrors Applicant’s description of a reliability value as described in PGPUB, [0035].
As to claims 8 and 17, the combination of Bernhard and Sans fails to explicitly disclose: wherein the respective reliability value is determined by a comparison of vehicle parameters forecast for a past time interval to vehicle parameters measured during this time interval.
Nevertheless, Schmüdderich teaches: wherein the respective reliability value is determined by a comparison of vehicle parameters forecast for a past time interval to vehicle parameters measured during this time interval (“The confidence value is weighted or scaled only in case that a mismatch rate between the observed actual state and the prediction result exceeds a predetermined threshold.” ¶ 18.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Bernhard and Sans to include the feature of: wherein a reliability value, which describes a reliability of the forecast of the progression in the respective partial time interval, is determined and is transmitted, the control unit and/or the software module utilizing the determined reliability values during the determination of the activation command, as taught by Schmüdderich, to yield the claim limitations at issue with a reasonable expectation of success because this feature is useful for “describing an estimated future state of … the ego-vehicle.” (Schmüdderich, ¶ 10.) Furthermore, one of ordinary skill in the art would have recognized that Schmüdderich’s confidence value would apply to Bernhards’ extreme values as Schmüdderich’s confidence value indicates the reliability of a forecast progression in given time interval – such mirrors Applicant’s description of a reliability value as described in PGPUB, [0035].
Claims 19-20 are rejected under § 103 as being unpatentable over Bernhard in view of Sans and in view of Schmüdderich.
As to independent claim 19, Bernhard discloses a method for transmitting predictive information to a control unit of a vehicle to determine an activation command for at least one function of the vehicle by evaluating the transmitted predictive information (“FIG. 1A shows an arrangement 15 with a control device 10 for controlling a technical system 12.” ¶ 73. “A technical system 12 may for example be a drive system, such as a drive system for a ship or a drive system for a rail vehicle.” ¶ 75.), the method comprising:
forecasting a progression of a vehicle parameter of the vehicle for a predefined time interval (“It is the purpose of such a control device 10 to control a technical system 12, inter alia with regard to a target value by taking into account a known or currently postulated and communicated forecast curve 6.” ¶ 76; see also FIGS. 1A-3.);
determining at least one first extreme value of the forecasted progression within a first partial time interval of the predefined time interval starting at a present point in time (“Analysis unit 104 of control device 100 can select characteristic values Ws of forecast curve 106 for example at minima, maxima or turning points of forecast curve 106. Minima, Maxima and turning points can be determined especially easily within the scope of a curve discussion of forecast curve 106.” Emphases added, ¶ 92; see also FIG. 2A.);
determining at least one second extreme value of the forecasted progression within a second partial time interval of the predefined time interval starting at the present point in time, the second partial time interval being longer than the first partial time interval (“Analysis unit 104 of control device 100 can select characteristic values Ws of forecast curve 106 for example at minima, maxima or turning points of forecast curve 106. Minima, Maxima and turning points can be determined especially easily within the scope of a curve discussion of forecast curve 106.” Emphases added, ¶ 92; see also FIG. 2A. Continuing: FIG. 2B illustrates a “forecast curve …, wherein the selected points in time ts of the set supporting points (Ws, ts)—in the current example eight time points ts=t1′, . . . t8′—have variable time intervals Δt1′ . . . Δt8′. In addition, due to variable and sometimes greater time intervals Δt1′ . . . Δt8′ approximation occurs in the embodiment shown in FIG. 2B in regard to an extended forecast horizon 220, compared to the described approximation in the embodiment shown in FIG. 1B. For example, time interval Δt8′—as is the case between characteristic time points 17′ and 18′—is greater here than time intervals Δt in the example from the state of the art in FIG. 1A.” ¶ 100 and FIG. 2B. Note: Summarizing, extreme values may be determined for a forecasted progression of a parameter over an overall time period, wherein the time period has at least a first partial time interval (e.g., Δt1) and a second partial time interval (e.g., Δt8 or Δt1-Δt8) which is longer than the first time interval.); and
transmitting the determined at least one first extreme value and the determined at least one second extreme value as the predictive information to the control unit and/or to the software module (“Analysis unit 104 of control device 100 can select characteristic values Ws of forecast curve 106 for example at minima, maxima or turning points of forecast curve 106. Minima, Maxima and turning points can be determined especially easily within the scope of a curve discussion of forecast curve 106.” Emphasis added, ¶ 92; see also FIG. 2A. Note: The determined values are necessarily transmitted to the analysis unit 104 to perform its processing vis-à-vis the determined extrema).
Bernhard fails to explicitly disclose:
performing the above features in relation to a motor vehicle; and
causing the control unit and/or the software module to execute the activation command to activate, deactivate, or pause the function of the motor vehicle based on the transmitted predictive information.
Nevertheless, Sans teaches:
transmitting predictive information to a control unit of a motor vehicle to determine an activation command for at least one function of the vehicle by evaluating the transmitted predictive information (Disclosed is “a method for optimizing the energy consumption of a motor vehicle;” involving “a computer for managing the drive train of the motor vehicle on a predetermined route, the computer being capable of controlling the internal combustion … and the electric machine;” and the method comprises at least the steps of: “a) defining a prediction period starting from the initial time, b) determining the maximum theoretical variation of each state variable from the initial value of said state variable and over the prediction period so that each state variable satisfies all of the state constraints specific thereto.” ¶ 9.); and
causing the control unit and/or the software module to execute the activation command to activate, deactivate, or pause the function of the motor vehicle based on the transmitted predictive information (“The computer 40 is capable of controlling each device to which it is connected, by issuing a setpoint, as a function of the value or values of variables relating to said device.” ¶ 50.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Bernhard to include the feature of: transmitting predictive information to a control unit of a motor vehicle to determine an activation command for at least one function of the vehicle by evaluating the transmitted predictive information; and causing the control unit and/or the software module to execute the activation command to activate, deactivate, or pause the function of the motor vehicle based on the transmitted predictive information, as taught by Sans, with a reasonable expectation of success because these features are useful to “to optimize the energy consumption of the drive train on a given or predicted route.” (Sans, ¶ 2.) As Bernhard also involves control of a drive system of a vehicle, one of ordinary skill in the art would have recognized that Bernhard’s disclosure can with a reasonable expectation of success apply to Sans’ drive train of a motor vehicle.
The combination of Bernhard and Sans fails to explicitly disclose: determining a reliability value for each of the determined extreme values, the reliability value describing a reliability of the forecasted progression in the respective partial time interval; transmitting the determined reliability values as predictive information to the control unit and/or to the software module; and utilizing the determined reliability values during the evaluation of the predictive information to determine and execute the activation command to activate, deactivate, or pause the function of the motor vehicle.
Nevertheless, Schmüdderich teaches: determining a reliability value for each of the determined extreme values, the reliability value describing a reliability of the forecasted progression in the respective partial time interval; transmitting the determined reliability values as predictive information to the control unit and/or to the software module; and utilizing the determined reliability values during the evaluation of the predictive information to determine and execute the activation command to activate, deactivate, or pause the function of the motor vehicle (“The prediction system unit 2 provides a prediction result 15 to a vehicle actuation means 17 and causes either directly actuating controls of the host vehicle such as steering, brakes or throttle on the basis of the prediction result 15 or by means of a controlling unit not shown in FIG. 1.” ¶ 35. Additionally, “[a] “confidence value for weighting the prediction result may be determined” ¶ 17.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Bernhard and Sans to include the feature of: determining a reliability value for each of the determined extreme values, the reliability value describing a reliability of the forecasted progression in the respective partial time interval; transmitting the determined reliability values as predictive information to the control unit and/or to the software module; and utilizing the determined reliability values during the evaluation of the predictive information to determine and execute the activation command to activate, deactivate, or pause the function of the motor vehicle, as taught by Schmüdderich, to yield the claim limitations at issue with a reasonable expectation of success because this feature is useful for “describing an estimated future state of … the ego-vehicle.” (Schmüdderich, ¶ 10.) Furthermore, one of ordinary skill in the art would have recognized that Schmüdderich’s confidence value would apply to Bernhards’ extreme values as Schmüdderich’s confidence value indicates the reliability of a forecast progression in given time interval – such mirrors Applicant’s description of a reliability value as described in PGPUB, [0035].
Claim 20 is rejected for at least the same reasons as claim 8 as the claims recite similar subject matter but for minor differences.
CONCLUSION
This action is final. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire three months from the mailing date of this action. In the event a first reply is filed within two months of the mailing date of this final action and the advisory action is not mailed until after the end of the three-month shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Mario C. Gonzalez whose telephone number is (571) 272-5633. The Examiner can normally be reached M–F, 10:00–6:00 ET.
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If attempts to reach the Examiner by telephone are unsuccessful, the examiner’s supervisor, Fadey S. Jabr, can be reached on (571) 272-1516. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/M.C.G./Examiner, Art Unit 3668
/Fadey S. Jabr/Supervisory Patent Examiner, Art Unit 3668
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