DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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.
Examiner’s Note
Examiner has cited particular paragraphs/columns and line numbers or figures in the references as applied to the claims below for convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations with the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant, in preparing the responses, to fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. Applicant is reminded that the Examiner is entitled to give the broadest reasonable interpretation to the language of the claims. Furthermore, the Examiner is not limited to the Applicant’s definition which is not specifically set forth in the claims.
Information Disclosure Statements
The Information Disclosure Statement(s) (IDS) filed on 12/09/2024 has/have been acknowledged.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant's cooperation is requested in correcting any errors of which applicant may become aware of, in the specification.
Status of Application
The preliminarily amended list of claims 1-20 is pending in this application. In the preliminarily amended claim set filed 12/09/2024:
Claim(s) 1-20 has/have been amended.
Claim(s) 21-30 has/have been cancelled.
Claim(s) 1, 8 and 16 is/are the independent claim(s) observed in the application.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim(s) 1, 8 and 16 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite a vehicle system or component that uses a processor to perform steps of: 1) outputting a series of parameter values and a series of time values associated with the series of parameter values, wherein the parameter values are predicted, measured, estimated, or inferred by the vehicle system; 2) receiving, from the vehicle system or vehicle component, the series of parameter values and the associated series of time values; 3) determining a time period for the series of parameter values to satisfy a defined condition using at least one time value of the series of time values; 4) correlating each of the values of the series of parameter values with a corresponding one of the values of the series reference values produce a series of correlated value sets and associated correlated times (in the case of claim 16); 5) determining a difference between each value of each correlated value set of the series of correlated value sets and further determining a time period for the series of correlated value sets to satisfy a defined condition using the time values associated with the series of parameter values and associated correlated times (in the case of claim 16); and 6) outputting the time period, wherein the vehicle system or vehicle component is adjusted based on the output time period.
The limitations of 1) outputting a series of parameter values and a series of time values associated with the series of parameter values, wherein the parameter values are predicted, measured, estimated, or inferred by the vehicle system; 2) receiving, from the vehicle system or vehicle component, the series of parameter values and the associated series of time values; 3) determining a time period for the series of parameter values to satisfy a defined condition using at least one time value of the series of time values; 4) correlating each of the values of the series of parameter values with a corresponding one of the values of the series reference values produce a series of correlated value sets and associated correlated times (in the case of claim 16); 5) determining a difference between each value of each correlated value set of the series of correlated value sets and further determining a time period for the series of correlated value sets to satisfy a defined condition using the time values associated with the series of parameter values and associated correlated times (in the case of claim 16); and 6) outputting the time period, wherein the vehicle system or vehicle component is adjusted based on the output time period, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a vehicle system or component that uses a processor, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the vehicle system or component that uses a processor language, in the context of this claim encompasses the user manually performing steps of: inferring a broadly recited set of parameter values for a series of received time values and performing calculations/data manipulation by correlating these parameter values with a set of reference values to determine a set of values that satisfy a defined condition.
The limitations reciting “receiving, from the vehicle system or vehicle component, the series of parameter values and the associated series of time values” amount to no more than mere data gathering(Insignificant Extra-Solution Activity – MPEP § 2106.05(g)).
The limitations reciting “outputting the time period, wherein the vehicle system or vehicle component is adjusted based on the output time period” are recited at such high level of generality throughout the Applicant’s specification that one of ordinary skill in the art may interpret the “adjusting” of a vehicle system or component as comprising displaying a notification, for example, which would amount to no more than mere data output(Insignificant Extra-Solution Activity – MPEP § 2106.05(g)).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components and Insignificant Extra-Solution Activity, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim(s) recite(s) an abstract idea.
Examiner’s Note: In order for the Applicant’s claimed invention to positively recite a vehicle control step that overcomes the rejections under 35 U.S.C. 101, the Applicant would need to further limit the scope of the claimed invention such the claimed vehicle adjustment clearly comprise of additional elements that add more than insignificant extra-solution activity to the judicial exception. One example, would be to clearly recite controlling a speed, steering or another similar vehicle operation that involves actuation of mechanical components of the vehicle using the outputted time period.
This judicial exception is not integrated into a practical application. In particular, the claim only recites one additional element – vehicle system or component that uses a processor to perform: 1) outputting a series of parameter values and a series of time values associated with the series of parameter values, wherein the parameter values are predicted, measured, estimated, or inferred by the vehicle system; 2) receiving, from the vehicle system or vehicle component, the series of parameter values and the associated series of time values; 3) determining a time period for the series of parameter values to satisfy a defined condition using at least one time value of the series of time values; 4) correlating each of the values of the series of parameter values with a corresponding one of the values of the series reference values produce a series of correlated value sets and associated correlated times (in the case of claim 16); 5) determining a difference between each value of each correlated value set of the series of correlated value sets and further determining a time period for the series of correlated value sets to satisfy a defined condition using the time values associated with the series of parameter values and associated correlated times (in the case of claim 16); and 6) outputting the time period, wherein the vehicle system or vehicle component is adjusted based on the output time period. The vehicle system or component in these steps is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim(s) is/are directed to an abstract idea.
The claim(s) does not/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of a vehicle system or component that uses a processor to perform: 1) outputting a series of parameter values and a series of time values associated with the series of parameter values, wherein the parameter values are predicted, measured, estimated, or inferred by the vehicle system; 2) receiving, from the vehicle system or vehicle component, the series of parameter values and the associated series of time values; 3) determining a time period for the series of parameter values to satisfy a defined condition using at least one time value of the series of time values; 4) correlating each of the values of the series of parameter values with a corresponding one of the values of the series reference values produce a series of correlated value sets and associated correlated times (in the case of claim 16); 5) determining a difference between each value of each correlated value set of the series of correlated value sets and further determining a time period for the series of correlated value sets to satisfy a defined condition using the time values associated with the series of parameter values and associated correlated times (in the case of claim 16); and 6) outputting the time period, wherein the vehicle system or vehicle component is adjusted based on the output time period, amounts to no 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. Therefore, the claim(s) is/are not patent eligible.
Dependent claim(s) 2-7, 9-15 and 17-20 when analyzed as a whole, is/are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea. The additional element(s), if any, in the dependent claim(s) is/are not sufficient to amount to significantly more than the judicial exception for the same reasons as with claim(s) 1, 8 and 16.
With respect to claims 2-7, 9-15 and 17-20, these claims further consist only of limitations that may be performed using pen and paper and/or in the human mind, as these claims further recite only additional determining steps pertaining to the type of data being processed(velocity and number of sides of an object recognition in claims 5, 6, 12, 13 and 20) or further broad recitation of vehicle components (3, 4, 9, 10, 18 and 19).
Claim Rejections - 35 USC § 102
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, 3-5, 8, 10-12 and 14 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by IWASE et al. (Japanese Patent Publication 2009001096 A) referenced as Iwase moving forward.
With respect to claim 1, Iwase discloses:
“A method, comprising: outputting, by a vehicle system or vehicle component of a vehicle, a series of parameter values and a series of time values associated with the series of parameter values, wherein the series of parameter values are estimated values predicted, measured, estimated, inferred, or otherwise determined by the vehicle system or vehicle component” [Iwase; In at least the paragraphs and figures cited, Iwase discloses using a computer(denoted 316 in Fig. 1) to compare time-series data of a vehicle's predicted change in speed in response to an acceleration input from the vehicle's driver; Fig. 1, 11; ¶: 0013, 0026, 0076-0080];
“receiving, by a processor of the vehicle from the vehicle system or vehicle component, the series of parameter values and associated the series of time values; determining, by the processor, a time period for the series of parameter values to satisfy a defined condition using at least one time value of the series of time values; outputting, by the processor, the time period; ” [Iwase; "The computer 16 is comprised of a CPU, a ROM storing a program for the acceleration characteristics learning processing routine described later, a RAM for storing data, and a bus connecting these components;" Fig. 1; ¶: 0026;
"Then, in step 360, the vehicle speed detected by the speed sensor 12 is acquired as the vehicle speed during acceleration, and in step 362, the range of time-series changes in vehicle speed predicted in step 358 is compared with the time-series changes in vehicle speed detected in step 360 to determine whether or not the acceleration operation is in an abnormal state;" Fig. 11; ¶: 0079; See also: ¶: 0013, 0076-0078, 0080];
“and adjusting the vehicle system or vehicle component based on the output time period” [Iwase; "If the time-series change in vehicle speed obtained in step 360 falls outside the predicted range, it is determined that the acceleration operation is abnormal, and in step 364, the warning device 318 displays warning information to the driver, and the process returns to step 350;" Fig. 11; ¶: 0079; See also: Fig. 1; ¶: 0013, 0026, 0076-0078, 0080].
With respect to claim 3, Iwase discloses: “The method of claim 1, wherein the vehicle system or vehicle component is or includes at least one of: an electronic control unit, integrated device controller, or sensor” [Iwase; "As shown in Figure 7, the driver assistance device 310 according to the third embodiment includes a speed sensor 12, an acceleration sensor 13, a driving position measuring device 14, a traffic condition acquisition unit 312 for acquiring traffic conditions including the vehicle's turning direction and the speed limit of the road, a computer 316 that stores a program for realizing an acceleration characteristic learning processing routine, and a program for realizing an abnormality detection processing routine for detecting abnormalities in acceleration operation based on the vehicle speed from the speed sensor 12, the driving position from the driving position measuring device 14, and the traffic conditions from the traffic condition acquisition unit 312, and an alarm device 318 for presenting an alarm to the driver regarding the detection of an abnormality in acceleration operation;" Fig. 7; ¶: 0061].
With respect to claim 4, Iwase discloses: “The method of claim 1,wherein the vehicle system is a safety system of the vehicle, or wherein the vehicle component is a component of the safety system of the vehicle” [Iwase; In at least Fig. 7 and accompanying ¶: 0061, Iwase discloses triggering an alarm based on the determination of whether abnormal acceleration is occurring from step 360 of previously cited Fig. 11; wherein the disclosed alarm has been interpreted as patentably indistinct from the Applicant's broadly recited "component of the safety system of the vehicle"].
With respect to claim 5, Iwase discloses: “The method of claim 1,wherein the series of parameter values are a series of velocity values” [Iwase; In at least the paragraphs and figures cited, Iwase discloses comparing time-series data of a vehicle's predicted change in speed in response to an acceleration input from the vehicle's driver; Fig. 1, 11; ¶: 0013, 0026, 0076-0080].
With respect to claim 8, Iwase discloses:
“A vehicle, comprising: a vehicle system or vehicle component configured to output a series of parameter values and a series of time values associated with the series of parameter values, wherein the parameter values are predicted, measured, estimated, or inferred by the vehicle system” [Iwase; In at least the paragraphs and figures cited, Iwase discloses using a computer(denoted 316 in Fig. 1) to compare time-series data of a vehicle's predicted change in speed in response to an acceleration input from the vehicle's driver; Fig. 1, 11; ¶: 0013, 0026, 0076-0080];
“and a processor configured to: receive, from the vehicle system or vehicle component, the series of parameter values and the associated series of time values; determine a time period for the series of parameter values to satisfy a defined condition using at least one time value of the series of time values” [Iwase; "The computer 16 is comprised of a CPU, a ROM storing a program for the acceleration characteristics learning processing routine described later, a RAM for storing data, and a bus connecting these components;" Fig. 1; ¶: 0026;
"Then, in step 360, the vehicle speed detected by the speed sensor 12 is acquired as the vehicle speed during acceleration, and in step 362, the range of time-series changes in vehicle speed predicted in step 358 is compared with the time-series changes in vehicle speed detected in step 360 to determine whether or not the acceleration operation is in an abnormal state;" Fig. 11; ¶: 0079; See also: ¶: 0013, 0076-0078, 0080];
“and output the time period, wherein the vehicle system or vehicle component is adjusted based on the output time period” [Iwase; "If the time-series change in vehicle speed obtained in step 360 falls outside the predicted range, it is determined that the acceleration operation is abnormal, and in step 364, the warning device 318 displays warning information to the driver, and the process returns to step 350;" Fig. 11; ¶: 0079; See also: Fig. 1; ¶: 0013, 0026, 0076-0078, 0080].
With respect to claim 10, Iwase discloses: “The vehicle of claim 8,wherein the vehicle system or vehicle component is an electronic control unit, integrated device controller, or sensor” [Iwase; "As shown in Figure 7, the driver assistance device 310 according to the third embodiment includes a speed sensor 12, an acceleration sensor 13, a driving position measuring device 14, a traffic condition acquisition unit 312 for acquiring traffic conditions including the vehicle's turning direction and the speed limit of the road, a computer 316 that stores a program for realizing an acceleration characteristic learning processing routine, and a program for realizing an abnormality detection processing routine for detecting abnormalities in acceleration operation based on the vehicle speed from the speed sensor 12, the driving position from the driving position measuring device 14, and the traffic conditions from the traffic condition acquisition unit 312, and an alarm device 318 for presenting an alarm to the driver regarding the detection of an abnormality in acceleration operation;" Fig. 7; ¶: 0061].
With respect to claim 11, Iwase discloses: “The vehicle of claim 8,wherein the vehicle system is a safety system of the vehicle or the vehicle component is a component of the safety system of the vehicle” [Iwase; In at least Fig. 7 and accompanying ¶: 0061, Iwase discloses triggering an alarm based on the determination of whether abnormal acceleration is occurring from step 360 of previously cited Fig. 11; wherein the disclosed alarm has been interpreted as patentably indistinct from the Applicant's broadly recited "component of the safety system of the vehicle"].
With respect to claim 12, Iwase discloses: “The vehicle of claim 8,wherein the series of parameter values are velocity values” [Iwase; Iwase; In at least the paragraphs and figures cited, Iwase discloses comparing time-series data of a vehicle's predicted change in speed in response to an acceleration input from the vehicle's driver; Fig. 1, 11; ¶: 0013, 0026, 0076-0080].
With respect to claim 14, Iwase discloses: “The vehicle of claim 8, wherein the processor is configured to perform the receiving, determining, processing, outputting, and adjusting, as well as being configured to process other data for operating the vehicle” [Iwase; "As shown in Figure 7, the driver assistance device 310 according to the third embodiment includes a speed sensor 12, an acceleration sensor 13, a driving position measuring device 14, a traffic condition acquisition unit 312 for acquiring traffic conditions including the vehicle's turning direction and the speed limit of the road, a computer 316 that stores a program for realizing an acceleration characteristic learning processing routine, and a program for realizing an abnormality detection processing routine for detecting abnormalities in acceleration operation based on the vehicle speed from the speed sensor 12, the driving position from the driving position measuring device 14, and the traffic conditions from the traffic condition acquisition unit 312, and an alarm device 318 for presenting an alarm to the driver regarding the detection of an abnormality in acceleration operation;" Fig. 7; ¶: 0061].
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 of this title, 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 nonobviousness.
This application currently names joint inventors. In considering patentability of the claims under pre-AIA 35 U.S.C. 103(a), the examiner presumes that the subject matter of the various claims was commonly owned at the time any inventions covered therein were made absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and invention dates of each claim that was not commonly owned at the time a later invention was made in order for the examiner to consider the applicability of pre-AIA 35 U.S.C. 103(c) and potential pre-AIA 35 U.S.C. 102(e), (f) or (g) prior art under pre-AIA 35 U.S.C. 103(a).
Claim(s) 2, 6, 9 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Iwase in view of Ohkuwa et al. (United States Patent Publication 2021/0116568 A1) referenced as Ohkuwa moving forward.
With respect to claim 2, Iwase does not specifically state: “wherein the series of parameter values include a first series of parameter values and second series of parameter values, and wherein the time period determined by the processor includes a first time period for the first series of parameter values to satisfy the defined condition, and includes a second time period for the second series of parameter values to satisfy the defined condition.”
Ohkuwa, which is in the same field of invention of using time-series data to control a vehicle, teaches: “wherein the series of parameter values include a first series of parameter values and second series of parameter values, and wherein the time period determined by the processor includes a first time period for the first series of parameter values to satisfy the defined condition, and includes a second time period for the second series of parameter values to satisfy the defined condition” [Ohkuwa; "In the first aspect of the invention, the first generating unit may estimate a future input value and may generate the first time-series data containing the future input value. In this case, by generating the second time-series data containing a future intermediate computation value corresponding to the future input value, a selectable range for a selection value widens, so it is possible to select a further suitable selection value for calculating a control variable;" ¶: 0009;
"In addition, in the first aspect of the invention, the first generating unit may generate a plurality of types of first value time-series data corresponding to a plurality of types of input values, the second generating unit may generate a plurality of types of second time-series data on the basis of the plurality of types of first value time-series data, the selecting unit may select selectable data ranges from among the respective types of second time-series data in accordance with a second selection condition, and the output unit may calculate the control variables from intermediate computation values contained in the respective selectable data ranges;" ¶: 0010; See also: ¶: 0131-0138].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system/method for controlling a vehicle based on a predicted change in speed over time with respect to an acceleration input as disclosed by Iwase to incorporate the teachings regarding controlling the vehicle using a plurality of time-series data in accordance with multiple selection conditions as taught by Ohkuwa with a reasonable expectation of success. By combining these inventions, the outcome is a system/method for controlling a vehicle based on a predicted change in speed over time with respect to an acceleration input that is more robust in its ability to select values “suitable for calculating a control variable; that is a control target may be flexibly selected for an actual period of time consumed for the processes, so it is possible to improve the reliability of control over a controlled object” “even when a delay occurs in a plurality of processes” [Ohkuwa; ¶: 0006-0008].
With respect to claim 6, Iwase does not specifically state: “wherein the vehicle system or vehicle component includes an object recognition system and wherein the series of parameter values are a number of sides of an object recognized by the object recognition system.”
Ohkuwa teaches: “wherein the vehicle system or vehicle component includes an object recognition system and wherein the series of parameter values are a number of sides of an object recognized by the object recognition system” [Ohkuwa; "As shown in FIG. 26, the recognition ECU 42 acquires time-series data of an image input value Bi, time-series data regarding an obstacle, time-series data regarding the location and direction of the vehicle and an up-to-date vehicle speed input value Ei from the image ECU 37, the radar ECU 38, the location calculation ECU 39 and the vehicle speed sensor 25 (S101);" Fig. 26; ¶: 0162;
"The recognition ECU 42 recognizes the type of the obstacle, the shape and size of the obstacle, the location of the obstacle, the relative speed between the obstacle and the vehicle and the moving direction of the obstacle on the basis of the acquired various pieces of time-series data and vehicle speed input value Ei, and then generates pieces of time-series data of them (S102). The recognition ECU 42 outputs the generated pieces of time-series data regarding obstacle recognition to the driving target ECU 43 (S103);" Fig. 26; ¶: 0163; See also: ¶: 0141-0147, 0164].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system/method for controlling a vehicle based on a predicted change in speed over time with respect to an acceleration input as disclosed by Iwase to incorporate the teachings regarding controlling the vehicle using a plurality of time-series data in accordance with multiple selection conditions as taught by Ohkuwa with a reasonable expectation of success. By combining these inventions, the outcome is a system/method for controlling a vehicle based on a predicted change in speed over time with respect to an acceleration input that is more robust in its ability to select values “suitable for calculating a control variable; that is a control target may be flexibly selected for an actual period of time consumed for the processes, so it is possible to improve the reliability of control over a controlled object” “even when a delay occurs in a plurality of processes” [Ohkuwa; ¶: 0006-0008].
With respect to claim 9, Iwase does not specifically state: “wherein the series of parameter values include a include a first and second series of parameter values, and the time period determined by the processor includes a first time period for the first series of parameter values to satisfy the defined condition and a second time period for the second series of parameter values to satisfy the defined condition.”
Ohkuwa teaches: “wherein the series of parameter values include a include a first and second series of parameter values, and the time period determined by the processor includes a first time period for the first series of parameter values to satisfy the defined condition and a second time period for the second series of parameter values to satisfy the defined condition” [Ohkuwa; "In the first aspect of the invention, the first generating unit may estimate a future input value and may generate the first time-series data containing the future input value. In this case, by generating the second time-series data containing a future intermediate computation value corresponding to the future input value, a selectable range for a selection value widens, so it is possible to select a further suitable selection value for calculating a control variable;" ¶: 0009;
"In addition, in the first aspect of the invention, the first generating unit may generate a plurality of types of first value time-series data corresponding to a plurality of types of input values, the second generating unit may generate a plurality of types of second time-series data on the basis of the plurality of types of first value time-series data, the selecting unit may select selectable data ranges from among the respective types of second time-series data in accordance with a second selection condition, and the output unit may calculate the control variables from intermediate computation values contained in the respective selectable data ranges;" ¶: 0010; See also: ¶: 0131-0138].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system/method for controlling a vehicle based on a predicted change in speed over time with respect to an acceleration input as disclosed by Iwase to incorporate the teachings regarding controlling the vehicle using a plurality of time-series data in accordance with multiple selection conditions as taught by Ohkuwa with a reasonable expectation of success. By combining these inventions, the outcome is a system/method for controlling a vehicle based on a predicted change in speed over time with respect to an acceleration input that is more robust in its ability to select values “suitable for calculating a control variable; that is a control target may be flexibly selected for an actual period of time consumed for the processes, so it is possible to improve the reliability of control over a controlled object” “even when a delay occurs in a plurality of processes” [Ohkuwa; ¶: 0006-0008].
With respect to claim 13, Iwase does not specifically state: “wherein the vehicle system or vehicle component includes an object recognition component and the series of parameter values are a number of sides of an object recognized by the object recognition component.”
Ohkuwa teaches: “wherein the vehicle system or vehicle component includes an object recognition component and the series of parameter values are a number of sides of an object recognized by the object recognition component” [Ohkuwa; "As shown in FIG. 26, the recognition ECU 42 acquires time-series data of an image input value Bi, time-series data regarding an obstacle, time-series data regarding the location and direction of the vehicle and an up-to-date vehicle speed input value Ei from the image ECU 37, the radar ECU 38, the location calculation ECU 39 and the vehicle speed sensor 25 (S101);" Fig. 26; ¶: 0162;
"The recognition ECU 42 recognizes the type of the obstacle, the shape and size of the obstacle, the location of the obstacle, the relative speed between the obstacle and the vehicle and the moving direction of the obstacle on the basis of the acquired various pieces of time-series data and vehicle speed input value Ei, and then generates pieces of time-series data of them (S102). The recognition ECU 42 outputs the generated pieces of time-series data regarding obstacle recognition to the driving target ECU 43 (S103);" Fig. 26; ¶: 0163; See also: ¶: 0141-0147, 0164].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system/method for controlling a vehicle based on a predicted change in speed over time with respect to an acceleration input as disclosed by Iwase to incorporate the teachings regarding controlling the vehicle using a plurality of time-series data in accordance with multiple selection conditions as taught by Ohkuwa with a reasonable expectation of success. By combining these inventions, the outcome is a system/method for controlling a vehicle based on a predicted change in speed over time with respect to an acceleration input that is more robust in its ability to select values “suitable for calculating a control variable; that is a control target may be flexibly selected for an actual period of time consumed for the processes, so it is possible to improve the reliability of control over a controlled object” “even when a delay occurs in a plurality of processes” [Ohkuwa; ¶: 0006-0008].
Prior Art (Not relied upon)
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure can be found in the attached form 892.
Conclusion
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/R.N.B./Examiner, Art Unit 3666C
/SCOTT A BROWNE/Supervisory Patent Examiner, Art Unit 3666
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