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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on December 23, 2025 has been entered.
3. This Office Action is sent in response to Applicant's Communication received on December 23, 2025.
Response to Arguments
Applicant’s amendments/arguments filed December 23, 2025, with respect to the rejections of claims 11-20 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of ALEMANI.
Disposition of Claims
Claims 11-20 are pending in this application.
Claims 11-20 are rejected.
Claim Rejections - 35 USC § 112
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.
Claims 11-20 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 pre-AIA the applicant regards as the invention.
Regarding claim 11, the limitations “…wherein said emissions not associated with the drivetrain are non-enqine particle emissions caused by a vehicle that are not directly produced in an enqine combustion process…” renders the claim undefined because said limitations includes subjective and relative language that fails to set the bounds and metes of what Applicant regards as their invention.
More specifically, inspection of Present Application Written Specification ([0005, 0026, 0030, 0034-0037, 0039, 0042-0044, 0104]) reveals that said limitations are referring to several situations involving several parameters, variables and strategies to retrieve and process data pertinent to particle emissions of friction brakes and tyre surfaces of a vehicle.
To advance prosecution, the Examiner will interpret and read said limitation as “…wherein said emissions not associated with the drivetrain are non-enqine particle emissions caused by the vehicle that are not directly produced in an enqine combustion process that includes particle emissions of a friction brake and a tyre surface of the vehicle…”, as this is consistent with present application written specification, drawings and claims on record.
Claims 12-20 are also rejected under 35 U.S.C. 112(b) as being dependent on, and failing to cure the deficiencies of, rejected base claim 11 above.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claims 11-20 are rejected under 35 U.S.C. 103 as being unpatentable over (NAMBA – US 2022/0242408 A1), in view of (CHEN – CN 110329258 A), further in view of (BEIDL – EP 3289192 B1), further in view of (ALEMANI – WO 2020/031103 A1).
Regarding claim 11, NAMBA discloses:
A vehicle state control system (automatic driving assistance system 1 for Vehicle M: Figs. 1-2), comprising:
a state detection unit (front-traveling-environment recognition section 21d, autonomous traveling sensor 14 and traveling data detector 26: Fig. 1),
a database unit (locator unit 11 including high-precision road map database 16 and traveling-environment data among other types of data: Fig. 1),
a control and evaluation unit (vehicle control unit 22: Fig. 1), and
an actuator unit (steering processor 31, a brake processor 32, and an acceleration/deceleration processor 33: Fig. 1);
said state detection unit (front-traveling-environment recognition section 21d, autonomous traveling sensor 14 and traveling data detector 26: Fig. 1) being configured for providing state data, the state data being traffic situation data, vehicle state data or vehicle subsystem data ([0019-0020, 0024, 0028-0029, 0030, 0032, 0039-0040, 0048]);
said state detection unit (front-traveling-environment recognition section 21d, autonomous traveling sensor 14 and traveling data detector 26: Fig. 1) including
a traffic situation detection unit (front-traveling-environment recognition section 21d and traveling data detector 26: Fig. 1) being configured for recording the traffic situation data and for providing the traffic situation data in a transmittable form ([0019-0020, 0024, 0028-0029, 0030, 0032, 0039-0040, 0048]),
a vehicle state detection unit (autonomous traveling sensor 14: Fig. 1) being configured for recording the vehicle state data and for providing the vehicle state data in a transmittable form ([0019-0020, 0024, 0028-0029, 0030, 0032, 0039-0040, 0048]), and
a vehicle subsystem detection unit (destination data input device 15: Fig. 1 and [0020-0023]) being configured for recording the vehicle subsystem data and for providing the vehicle subsystem data in a transmittable form {Using an input unit of a car navigation system (e.g., a touch panel of a monitor), a portable terminal such as a smart phone, or a personal computer} ([0019-0020, 0024, 0028-0029, 0030, 0032, 0039-0040, 0048]);
said database unit (locator unit 11: Fig. 1) being data-linked to said state detection unit (front-traveling-environment recognition section 21d, autonomous traveling sensor 14 and traveling data detector 26: Fig. 1),
said database unit (locator unit 11: Fig. 1) including
a static database module (read only memory {ROM} that store a program to be executed by the CPU and a base map or other fixed data, for example “predetermined data/values” that will not change during the processing of the control system: [0019, 0056]),
a dynamic database module (random access memory {RAM} that store “temporary calculated/retrieved/processed data/values” that will change during the processing of the control system: [0019, 0056]) and
a data management module (road map database 16 and traveling-environment data among other types of data: Fig. 1),
,
,
said data management module (road map database 16 and traveling-environment data among other types of data: Fig. 1) being configured for writing the variable data into the dynamic database module (random access memory {RAM} that store “temporary calculated/retrieved/processed data/values” that will change during the processing of the control system: [0019, 0056]) or deleting the variable data and, being configured for retrieving the static data from said static database module (read only memory {ROM} that store a program to be executed by the CPU and a base map or other fixed data, for example “predetermined data/values” that will not change during the processing of the control system: [0019, 0056]) and the variable data from the dynamic database module (random access memory {RAM} that store “temporary calculated/retrieved/processed data/values” that will change during the processing of the control system: [0019, 0056]) and for providing the static and variable data in a transferable form as database data;
said control and evaluation unit (vehicle control unit 22: Fig. 1) being data-linked to said state detection unit (front-traveling-environment recognition section 21d, autonomous traveling sensor 14 and traveling data detector 26: Fig. 1) and said database unit (locator unit 11: Fig. 1),
said control and evaluation unit (vehicle control unit 22: Fig. 1) being configured for
receiving the state data from said state detection unit (front-traveling-environment recognition section 21d, autonomous traveling sensor 14 and traveling data detector 26: Fig. 1) and the database data from said database unit (locator unit 11: Fig. 1) and for providing alternative preliminary control commands from the state data and the database data, and ;
said control and evaluation unit (vehicle control unit 22: Fig. 1)
,
said control and evaluation unit (vehicle control unit 22: Fig. 1) including
an assessment module (vehicle control calculator 22a: Fig. 1 and [0030, 0032]) being configured for
, and
said control and evaluation unit (vehicle control unit 22: Fig. 1) being configured for
outputting the final control command to said actuator unit (steering processor 31, a brake processor 32, and an acceleration/deceleration processor 33: Fig. 1), said actuator unit (steering processor 31, a brake processor 32, and an acceleration/deceleration processor 33: Fig. 1) for influencing a vehicle state ([0031-0033, 0040]).
But NAMBA does not explicitly and/or specifically meet the following limitations:
said static database module including static data on cause-effect relationships to emissions not associated with the drivetrain, said dynamic database module including variable data on emissions not associated with the drivetrain; and predictive emission parameters being assigned to the alternative preliminary control commands; a calculation module being configured for calculating an emission budget of a driving unit from the state data and the database data and for using the emission budget for determining target emission parameters for the preliminary alternative control commands; selecting a final control command from the alternative preliminary control commands by a comparison of the predictive emission parameters with the target emission parameters.
wherein said emissions not associated with the drivetrain are non-enqine particle emissions caused by the vehicle that are not directly produced in an enqine combustion process that includes particle emissions of a friction brake and a tyre surface of the vehicle.
However, regarding limitation (A) above, CHEN discloses/teaches the following:
An energy-saving emission-reducing coordination control method for intelligent drive automobile, comprising following steps: firstly, collecting a front distance and a relative speed signal, and obtaining road information of a future road section through the collection of high-precision map information, comprehensively using the aforementioned information to perform speed planning on an intelligent cruise drive vehicle with energy saving as the goal to realize the control of the drive torque of the vehicle; with the goal of reducing emissions, controlling the opening, EGR opening and ignition advance angle of the throttle by the power demand torque under the energy saving target to achieve the minimum NOx emission effect, and finally realizing the coordinated control of energy saving and emission reduction for vehicles under intelligent driving. The invention combines the traditional energy-saving emission reduction technology of the automobile industry and the multi-source information brought by the intelligentization, and achieves the purpose of energy saving and emission reduction while satisfying the adaptive cruise driving by reasonably matching the relationship between the power transmission system of the vehicle, the movement of the vehicle and the road conditions (Abstract).
Please see mathematical relationships to predict NOx emissions in Paragraphs [0122-0195], using an engine emissions model identification and a variable prediction model.
Further on, BEIDL (Figs. 1-3) discloses/teaches the following:
According to a preferred embodiment, the emissions forecast provides a statement about
whether and / or how, as a result of the vehicle behavioral prediction, the pollutant emissions of the internal combustion engine will change over a forecast period; and or
whether and / or how the behavior of at least one component of an exhaust aftertreatment device will change; and or
how the at least one component of the exhaust aftertreatment device will behave with respect to a possible change in the pollutant emissions of the internal combustion engine ([0040]).
In step S500 (Fig. 3), an emissions forecast is calculated using the vehicle behavior prognosis. This is done according to a preferred embodiment by the {{{emission prediction generating device 260}}} of the control unit 200 ([0094]). In step S600, the emission forecast is evaluated based on predetermined criteria. This is done according to a preferred embodiment by an evaluation unit of the control unit 200 ([0095]). In step S700, a {{{control value or rate for driving the actuator 220 is derived based on the emissions forecast}}} ([0096]).
"Environment-related state parameters" in the sense of the present invention are state parameters which relate in particular to the current weather and the road condition in which the motor vehicle is moving. Corresponding parameters are preferably the temperature and / or the atmospheric pressure of the ambient air, in particular for the prediction of weather changes, the presence of rain and / or snowfall, rainfall and / or snowfall amount and also the amount of snow on the ground, degree of smoothness, etc ([0035]). A "state model" in the sense of the present invention is in particular a data set or, in particular, several data sets and / or one or more computer models which at least approximately represent the actual state of the motor vehicle (eg speed, steering wheel position, gear, total weight), in particular in its current environment (eg, road surface, weather, obstacles, road layout) and / or in its current driving situation (eg, accelerating, driving at substantially constant speed, braking, overtaking, turning, etc.).
The state model determination device 230 is provided to determine a state model from the measured values and / or data of the sensor devices 210. This state model is a multicriterial mapping of the current actual state of the motor vehicle 1 (eg speed, steering wheel position, gear, total weight) in its current environment (eg road surface, weather, obstacles, road course) and in its current driving situation (eg acceleration, at substantially constant speed driving, braking, overtaking, turning) ([0086]).
Taking into account a driver profile or automatically selected driver profile 250a, 250b, the vehicle behavior prediction calculation device 240 calculates a prediction of the vehicle behavior during the future forecast horizon. The tasks are preferably adopted by the state determination device 230 by the vehicle behavior prediction calculation device 240, so that the vehicle behavior prediction calculation device 240 calculates the vehicle behavior prognosis directly from the data of the sensor devices 210 and, in particular, the driver profile management device 250. From the vehicle behavior prognosis, an emission prognosis generating device 260 generates an emissions prognosis, in particular taking into account the measured values of the sensor devices for detecting emission parameters 210d. From this emission forecast, a control value or tax rate for controlling the setting device 220 is derived and transmitted to the respective setting device 220, preferably via a BUS system. On the basis of incoming data and / or measured values, the degree of occurrence of the prognosis is evaluated. If deviations are ascertained here which are to be assigned to the current driver, then the respective driver profile 250a, 250b is updated accordingly in order to continuously improve the forecast reliability. This update is performed by the vehicle behavior prediction calculator 240 and / or the driver profile manager 250 ([0087-0096]).
It is noted that, both, CHEN and BEIDL discloses a similar automatic driving assistance system to be applied to a vehicle like NAMBA above.
Accordingly, one skilled in the art would have been motivated to incorporate the teachings of CHEN and BEIDL into NAMBA to achieves the purpose of energy saving and emission reduction while satisfying the adaptive cruise driving by reasonably matching the relationship between the power transmission system of the vehicle, the movement of the vehicle and the road conditions.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified the vehicle system of NAMBA incorporating an emissions-reducing and optimization strategy as taught by CHEN and BEIDL to achieves the purpose of energy saving and emission reduction while satisfying the adaptive cruise driving by reasonably matching the relationship between the power transmission system of the vehicle, the movement of the vehicle and the road conditions.
Still further, regarding limitation (B) above, ALEMANI discloses/teaches the following:
A method for detecting and providing braking assessment information (I) is described, indicative of a particulate emission due to the use of a vehicle braking system. The method comprises the step of determining, upon a braking event, one or more physical quantities (A, B, C) related to the particulate emission caused by the braking event, based on the detection of at least one physical quantity (A) detected from the aforesaid one or more physical quantities, performed by respective detection means (10) provided in the vehicle. The method comprises then the step of calculating, by means of an algorithm or mathematical assessment model (M1), stored and executable in a computer (10), at least one braking assessment index (ivf), based on the aforesaid one or more determined physical quantities (A, B, C). Such index ivf is {{{representative of a particulate emission amount (QP)}}} by the vehicle braking system upon the braking event. The method lastly includes providing a user with braking assessment information (I) related to the aforesaid calculated braking assessment index (ivf), by means of a user interface (14). A device (1) for detecting and providing braking assessment information indicative of a particulate emission by a braking system is also described, capable of performing the aforesaid method ([Abstract]).
The method, first of all, comprises the step of determining, upon a braking event, one or more physical quantities (A, B, C) related to the vehicle particulate emission caused by the braking event, based on the detection of at least one physical quantity (A) detected from the aforesaid one or more physical quantities, performed by respective detection means 10 provided in the vehicle ([0031]).
The method comprises then the step of calculating, by means of an algorithm or mathematical assessment model M1 , stored and executable in a computer 10 provided in the vehicle, at least one braking assessment index ivf, based on the aforesaid one or more determined physical quantities (A, B, C). Such braking assessment index ivf is representative of a particulate emission amount QP due to the use of the vehicle braking system upon the braking event ([0032]). In accordance with different possible embodiments of the method, the aforesaid one or more determined physical quantities (A, B, C) comprise one or more quantities belonging to the following group: vehicle speed (v), and/or vehicle acceleration/deceleration (a), and/or vehicle braking system temperature (T), and/or braking pressure (p), and/or vehicle engine torque (c), and/or braking torque, and/or vehicle inclination, and/or number and/or concentration of particles emitted by the vehicle braking system ([0034]).
The device 1 comprises detection means 10, provided in the vehicle, a first communication infrastructure 11, provided in the vehicle, a computer 12, provided in the vehicle, a second communication infrastructure 13 and a user interface 14 ([0108]). The computer 12 is connected to the first communication infrastructure 11 to receive the aforesaid first signals SA, and configured to determine, based on such first signals SA, by means of an algorithm or mathematical assessment model M1 stored therein, one or more physical quantities (A, B, C) related to the vehicle particulate emission caused by the braking event ([0111]). The computer 12 is further configured to calculate, by means of an algorithm or mathematical determination model M2 stored therein, based on said one or more determined physical quantities (A, B, C) at least one braking assessment index ivf, representative of a particulate emission amount QP due to the use of the vehicle braking system on braking ([0112]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified the vehicle system of NAMBA in view of CHEN and BEIDL further incorporating another emissions-reducing and optimization strategy as taught by ALEMANI to identify non-exhaust emissions, originating from brake wear and tire wear.
Regarding claim 12, NAMBA as combined above disclose the vehicle state control system according to claim 11, and further on NAMBA as combined above also discloses:
wherein the system is a system according to SAE Level 2 to 5.
Examiner Note:
From Applicant’s Present Application Written Description, the “SAE Level” is defined as the well-known “System Automated Level” that goes from 0 to 5, where level 0 is no driving automation and where level 5 is Full Automated/Autonomous Driving.
In view of the above, the Examiner submits that any one of NAMBA, CHEN and BEIDL are a vehicle system according to SAE Level 2 to 5.
Regarding claim 13, NAMBA as combined above disclose the vehicle state control system according to claim 11, and further on NAMBA as combined above also discloses:
wherein the vehicle subsystem is at least one of a braking system or a tire system (NAMBA, CHEN and BEIDL all have a braking system).
Regarding claim 14, NAMBA as combined above disclose the vehicle state control system according to claim 13, and further on NAMBA as combined above also discloses:
wherein the vehicle state is influenced by the braking system as a deceleration (At least BEIDL discloses/teaches that the vehicle state is influenced by the braking system as a deceleration).
Regarding claim 15, NAMBA as combined above disclose the vehicle state control system according to claim 11, and further on NAMBA as combined above also discloses:
wherein said control and evaluation unit and said database unit define a structural unit (Please follow element limitations annotated above regarding NAMBA Fig. 1).
Regarding claim 16, NAMBA as combined above disclose the vehicle state control system according to claim 11, and further on NAMBA as combined above also discloses:
wherein data is written to a status history in the dynamic database (Please follow element limitations annotated above regarding NAMBA Fig. 1).
Regarding claim 17, NAMBA as combined above disclose the vehicle state control system according to claim 11, and further on NAMBA as combined above also discloses:
wherein said control and evaluation unit is configured to use the state data to assess an emission-related degree of fulfilment of a previous final control command and to update the variable data with the data management module (When combining CHEN and BEIDL into NAMBA, one skilled in the art would have arrived at the claimed limitation. More specifically, the Examiner submit reading the citations above regarding BEIDL).
Regarding claim 18, NAMBA as combined above disclose the vehicle state control system according to claim 11, and further on NAMBA as combined above also discloses:
a road vehicle, comprising:
the vehicle state control system according to claim 11 and a friction brake (When combining CHEN and BEIDL into NAMBA, one skilled in the art would have arrived at the claimed limitation. More specifically, the Examiner submit reading the citations above regarding BEIDL).
Regarding claim 19, NAMBA as combined above disclose the vehicle state control system according to claim 11, and further on NAMBA as combined above also discloses:
A method for vehicle state control with a vehicle state control system, comprising:
providing the vehicle state control system according to claim 11; and
including the following process steps:
a) writing static data as parametrization into the static database module (Please follow element limitations annotated above regarding NAMBA Fig. 1);
b) recording state data with the state detection unit and providing the state data for transmission (Please follow element limitations annotated above regarding NAMBA Fig. 1);
c) obtaining state data from the state detection unit and database data from the database unit with the control and evaluation unit (Please follow element limitations annotated above regarding NAMBA Fig. 1);
d) providing alternative preliminary control commands and assigning predictive emission parameters to the alternative preliminary control commands with the control and evaluation unit (When combining CHEN and BEIDL into NAMBA, one skilled in the art would have arrived at the claimed limitation. More specifically, the Examiner submit reading the citations above regarding BEIDL);
e) calculating an emission budget of a driving unit from the state data and the database data (When combining CHEN and BEIDL into NAMBA, one skilled in the art would have arrived at the claimed limitation. More specifically, the Examiner submit reading the citations above regarding BEIDL);
f) calculating target emission parameters from the emission budget (When combining CHEN and BEIDL into NAMBA, one skilled in the art would have arrived at the claimed limitation. More specifically, the Examiner submit reading the citations above regarding BEIDL);
g) selecting a final control command from the alternative preliminary control commands by comparing the predictive emission parameters and the target emission parameters (When combining CHEN and BEIDL into NAMBA, one skilled in the art would have arrived at the claimed limitation. More specifically, the Examiner submit reading the citations above regarding BEIDL);
h) outputting the final control command to the actuator unit and affecting a vehicle state (When combining CHEN and BEIDL into NAMBA, one skilled in the art would have arrived at the claimed limitation. More specifically, the Examiner submit reading the citations above regarding BEIDL); and
i) at least one of writing or deleting variable data of the dynamic database module with the data management unit (Please follow element limitations annotated above regarding NAMBA Fig. 1).
Regarding claim 20, NAMBA as combined above disclose the vehicle state control method according to claim 19, and further on NAMBA as combined above also discloses:
repeating execution of the process steps a) to i); and
including the following additional process steps:
j) recording actual emission parameters from final control commands already issued in the driving unit (When combining CHEN and BEIDL into NAMBA, one skilled in the art would have arrived at the claimed limitation. More specifically, the Examiner submit reading the citations above regarding BEIDL);
k) including the actual emission parameters in the emission budget and calculating a residual emission budget for a residual driving unit (When combining CHEN and BEIDL into NAMBA, one skilled in the art would have arrived at the claimed limitation. More specifically, the Examiner submit reading the citations above regarding BEIDL);
(l) calculating updated target emission parameters from the residual emission budget (When combining CHEN and BEIDL into NAMBA, one skilled in the art would have arrived at the claimed limitation. More specifically, the Examiner submit reading the citations above regarding BEIDL); and
(m) selecting the final control command from the alternative preliminary control commands by a comparison of the predictive emission parameters with the updated target emission parameters (When combining CHEN and BEIDL into NAMBA, one skilled in the art would have arrived at the claimed limitation. More specifically, the Examiner submit reading the citations above regarding BEIDL).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Ruben Picon-Feliciano whose telephone number is (571)-272-4938. The examiner can normally be reached on Monday-Thursday within 11:30 am-7:30 pm ET.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Lindsay M. Low can be reached on (571)272-1196. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RUBEN PICON-FELICIANO/Examiner, Art Unit 3747
/GRANT MOUBRY/Primary Examiner, Art Unit 3747