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 .
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 in the specification.
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 1-19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites “to acquire operation data including an operation of a train and load factors of vehicles of the train from a data collection device to collect equipment data on the train” in lines 4-6; however, it is unclear what exactly is meant by “load factors” in lines 4-5 of the claim. While Applicant’s specification (which is a translation based on international parent application PCT/JP2021/041572) repeatedly uses the term “load factor,” Applicant’s specification does not appear to provide a meaning for the term, and the term does not have an ordinary and customary meaning to those of ordinary skill in the art. Therefore, because no reasonably clear meaning can be ascribed to the claim term after considering the specification and prior art, the claim is indefinite, and a broadest reasonable interpretation is applied to the claim term as it can be best understood (e.g., see: MPEP 2111.01_V).
Claims 2-12 are dependent from claim 1, such that claims 2-12 also include the indefinite subject matter recited by claim 1 and are rejected for at least the same reasons that claim 1 is rejected. Note that claim 4 also includes repeated usage of the terms “load factors” and “load factor.”
Claim 13 recites “to acquire operation data including an operation of a train and load factors of vehicles of the train from a data collection device to collect equipment data on the train” in lines 8-10 and again in lines 19-21; however, it is unclear what exactly is meant by “load factors” in each of line 9 and line 20 of the claim. While Applicant’s specification (which is a translation based on international parent application PCT/JP2021/041572) repeatedly uses the term “load factor,” Applicant’s specification does not appear to provide a meaning for the term, and the term does not have an ordinary and customary meaning to those of ordinary skill in the art. Therefore, because no reasonably clear meaning can be ascribed to the claim term after considering the specification and prior art, the claim is indefinite, and a broadest reasonable interpretation is applied to the claim term as it can be best understood (e.g., see: MPEP 2111.01_V).
Claim 13, as amended, introduces “operation data” in line 19, “an operation of the train” in lines 19-20, “load factors of vehicles of the train” in line 20, “a data collection device” in line 20, and “equipment data on the train” in lines 20-21; however, claim 13 previously introduces each of “operation data” in line 8, “an operation of the train” in line 8, “load factors of vehicles of the train” in line 9, “a data collection device” in line 9, and “equipment data on the train” in lines 9-10, such that it is unclear whether each of the “operation data” in line 19, the “operation of the train” in lines 19-20, the “load factors of vehicles of the train” in line 20, the “data collection device” in line 20, and the “equipment data on the train” in lines 20-21 is/are intended to be the same as or different from corresponding ones of the “operation data” in line 8, the “operation of the train” in line 8, the “load factors of vehicles of the train” in line 9, the “data collection device” in line 9, and the “equipment data on the train” in lines 9-10. Therefore, it is also unclear what exactly is meant by each of “the operation data” in line 11 and “the operation data” in line 22, as it is unclear whether the “operation data” in line 11 and/or the “operation data” in line 22 is intended to be the same as or different from the “operation data” in line 8 and/or the “operation data” in line 19. Thus, there is improper antecedent basis for the limitations in the claim.
Claim 13, as amended, introduces “operation data on an inter-station” in lines 22-23, “an inter-station” in line 23, “a travel time taken by the train to travel from a first station to a second station” in lines 23-24, “a first station” in line 23, “a second station” in lines 23-24, “a stop time for which the train is stopped at the first station or the second station” in line 24, and “features” in line 25; however, claim 13 previously introduces each of “operation data on an inter-station” in lines 11-12, “an inter-station” in lines 11-12, “a travel time taken by the train to travel from a first station to a second station” in lines 12-13, “a first station” in line 12, “a second station” in lines 12-13, “a stop time for which the train is stopped at the first station or the second station” in line 13, and “features” in line 14, such that it is unclear whether each of the “operation data on an inter-station” in lines 22-23, the “inter-station” in line 23, the “travel time taken by the train to travel from a first station to a second station” in lines 23-24, the “first station” in line 23, the “second station” in lines 23-24, the “stop time for which the train is stopped at the first station or the second station” in line 24, and the “features” in line 25 is/are intended to be the same as or different from corresponding ones of the “operation data on an inter-station” in lines 11-12, the “inter-station” in lines 11-12, the “travel time taken by the train to travel from a first station to a second station” in lines 12-13, the “first station” in line 12, the “second station” in lines 12-13, the “stop time for which the train is stopped at the first station or the second station” in line 13, and the “features” in line 14. Therefore, it is also unclear what exactly is meant by “the features” in line 15, as it is unclear whether the “features” in line 15 are intended to be the same as or different from the “features” in line 14 and/or the “operation data” in line 25. Thus, there is improper antecedent basis for the limitations in the claim.
Claims 14-18 are dependent from claim 13, such that claims 14-18 also include the indefinite subject matter recited by claim 13 and are rejected for at least the same reasons that claim 13 is rejected. Note that claim 16 also includes repeated usage of the terms “load factors” and “load factor.”
Claim 19 recites “acquiring operation data including an operation of a train and load factors of vehicles of the train from a data collection device to collect equipment data on the train” in lines 3-5; however, it is unclear what exactly is meant by “load factors” in line 4 of the claim. While Applicant’s specification (which is a translation based on international parent application PCT/JP2021/041572) repeatedly uses the term “load factor,” Applicant’s specification does not appear to provide a meaning for the term, and the term does not have an ordinary and customary meaning to those of ordinary skill in the art. Therefore, because no reasonably clear meaning can be ascribed to the claim term after considering the specification and prior art, the claim is indefinite, and a broadest reasonable interpretation is applied to the claim term as it can be best understood (e.g., see: MPEP 2111.01_V).
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
Each of claims 1 and 13 is directed to an apparatus. Claims 2-12 depend from claim 1, and claims 14-18 depend from claim 13. Claim 19 is directed to a method. Therefore, claims 1-19 are within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claims 1, 13, and 19 each include limitations that recite an abstract idea (emphasized below).
Claim 1 recites: An automatic train operation assistance device, comprising: processing circuitry
to acquire operation data including an operation of a train and load factors of vehicles of the train from a data collection device to collect equipment data on the train;
to extract, using the operation data, operation data on an inter-station including a travel time taken by the train to travel from a first station to a second station and a stop time for which the train is stopped at the first station or the second station, as features; and
to construct a prediction model using the features, and predict future operating conditions of the train including a future position of the train, using the prediction model and current features. (emphasis added).
Claim 13 recites: An automatic train operation assistance device, comprising: a first automatic train operation assistance device installed in an operation control apparatus to control an operation of a train or in a cloud; and a second automatic train operation assistance device installed on the train,
wherein the first automatic train operation assistance device includes first processing circuitry
to acquire operation data including an operation of the train and load factors of vehicles of the train from a data collection device that collects equipment data on the train,
to extract, using the operation data, operation data on an inter-station including a travel time taken by the train to travel from a first station to a second station and a stop time for which the train is stopped at the first station or the second station, as features, and
to construct a prediction model using the features, and
the second automatic train operation assistance device includes second processing circuitry
to acquire operation data including an operation of the train and load factors of vehicles of the train from a data collection device that collects equipment data on the train,
to extract, using the operation data, operation data on an inter-station including a travel time taken by the train to travel from a first station to a second station and a stop time for which the train is stopped at the first station or the second station, as features, and
to predict future operating conditions of the train including a future position of the train, using the prediction model and current features. (emphasis added).
Claim 19 recites: An automatic train operation assistance method, comprising:
acquiring operation data including an operation of a train and load factors of vehicles of the train from a data collection device to collect equipment data on the train;
extracting using the operation data, operation data on an inter-station including a travel time taken by the train to travel from a first station to a second station and a stop time for which the train is stopped at the first station or the second station, as features;
constructing a prediction model using the features; and
predicting future operating conditions of the train including a future position of the train, using the prediction model and current features. (emphasis added).
The examiner submits that the foregoing bolded limitations constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, each of the recited “extract…” (or “extracting…”), “construct…” (or “constructing…”), and “predict…” (or “predicting…”) limitations, in the context of this claim encompasses a person looking at data collected and forming simple judgments. Also, in claims 1, 13, and 19, at least the recited “construct…” (or “constructing…”) limitations also fall within the “mathematical concepts” group of abstract ideas, because each of the recited “construct…” (or “constructing…”) limitations is directed to mathematical relationships, mathematical formulas or equations, and/or mathematical calculations. Accordingly, each of claims 1, 13, and 19 recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are the underlined portions provided above while the bolded portions continue to represent the “abstract idea.”
For the following reasons, the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
In claims 1, 13, and 19, the underlined “acquire…” (or “acquiring…”) limitations amount to nothing more than insignificant extra-solution activity that merely defines data gathering, all recited at a high level of generality, in conjunction with the aforementioned abstract idea [e.g., see: MPEP 2106.04(d) & 2106.05(g)].
In claim 1, recitation of “processing circuitry” amounts to merely using a computer as a tool to perform the aforementioned abstract idea or reciting implementation of the abstract idea on a computer [e.g., see: MPEP 2106.04(d) & 2106.05(f)]. Likewise, in claim 13, recitation of “first processing circuitry” and “second processing circuitry” amounts to merely using a computer as a tool to perform the aforementioned abstract idea or reciting implementation of the abstract idea on a computer. Note that the courts do not distinguish between claims that recite abstract ideas performed by humans and claims that recite abstract performed on a computer, and both product claims (e.g., computer system, computer-readable medium, etc.) and process claims may recite abstract ideas [e.g., see: MPEP 2106.04(a)2)_III], and simply implementing abstract idea(s) on a physical machine (e.g., a computer or controller) is not a patentable application of that/those abstract idea(s) (e.g., see: MPEP 2106.04(a)(2)_III & 2106.04(d)).
Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception. While the generic structural elements recited by claims 1, 13, and 19 provide some limitation to use of the claimed abstract ideas, the generic structural elements recited by claims 1, 13, and 19 merely confine the judicial exception to a generic technological environment and thus fail to add an inventive concept to the claims (e.g., see: MPEP 2106.06(h)). Also, no particular transformation of an article via the abstract idea(s) is present in claims 1, 13, and 19 (e.g., see: MPEP 2106.05(c)).
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the 2019 PEG, independent claims 1, 13, and 19 do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application.
Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The examiner takes Official Notice (e.g., see: MPEP 2144.03) that use of the processor circuitry and data gathering steps are well-understood, routine, and conventional activities in the art, and are acknowledged as such by at least MPEP 2106. Hence, the claims are not patent eligible.
Claims 2-12 are dependent from claim 1, and claims 14-18 are dependent from claim 13, and claims 2-12 and 14-18 merely further introduce additional “mental process”/“mathematical concepts” abstract idea(s) to the respective method or system and/or further define “mental process”/“mathematical concepts” abstract idea(s) introduced by a preceding claim without including additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 4-12, and 19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by JP 2014-144754 A to Ueda et al. (hereinafter: “Ueda”).
With respect to claim 1, Ueda teaches an automatic train operation assistance device (e.g., apparent from at least Figs. 1-4 & 14-16), comprising: processing circuitry (e.g., 1B & 11C together) to acquire operation data including an operation of a train and load factors of vehicles of the train from a data collection device to collect equipment data on the train [for example, as depicted by at least Fig. 15 and as discussed by at least ¶ 0015-0017 & 0048-0057, the ground control device 1B is structured to perform functions to acquire schedule information 20 (e.g., “operation data”; “operation of a train”; “equipment data”), arrival/departure time history DB (database) 21 (e.g., “operation data”; “operation of a train”; “equipment data”), train history of each train (e.g., “operation data”; “operation of a train”; “equipment data”), and boarding section information 23 collected in real time (e.g., “operation data”; “load factors”; “equipment data”)]; to extract, using the operation data, operation data on an inter-station including a travel time taken by the train to travel from a first station to a second station and a stop time for which the train is stopped at the first station or the second station, as features [for example, as depicted by at least Fig. 15 and as discussed by at least ¶ 0015-0017, the ground control device 1B is structured to perform functions to extract, using the train history of each train, a station departure time of a departure station 50 and a station arrival time of an arrival station 51 of each train (e.g., “travel time taken by the train to travel from a first station to a second station”; “features”) and a station stop time of each train at the departure station 50 or the arrival station 51 (e.g., “stop time for which the train is stopped at the first station or the second station”; “feature”)]; and to construct a prediction model using the features [for example, as depicted by at least Figs. 14 & 16 and as discussed by at least ¶ 0015-0017 & 0022-0031, the automatic train driving device 11C is structured to perform functions to construct, using the station departure time of the departure station 50 and the station arrival time of the arrival station 51 of each train and the station stop time of each train at the departure station 50 or the arrival station 51, a curve (e.g., “prediction model”) via an operation curve selection unit 32], and predict future operating conditions of the train including a future position of the train, using the prediction model and current features [for example, as depicted by at least Figs. 14 & 16 and as discussed by at least ¶ 0015-0017 & 0022-0031, the automatic train driving device 11C is structured to perform functions to predict a driving pattern of the train, including future locations of the train with respect to time, from a departure station 50 to an arrival station 51 (e.g., “future operating condition”; “future position of the train”), based on the curve, the station departure time of the departure station 50 and the station arrival time of the arrival station 51 of each train, and the station stop time of each train at the departure station 50 or the arrival station 51].
With respect to claim 4, Ueda teaches the automatic train operation assistance device according to claim 1, wherein the load factors of the vehicles of the train included in the operation data include, for each vehicle of the train, a load factor when the train is stopped at a station and passengers are getting on and off, and a load factor when the train is traveling (as discussed in detail above with respect to claim 1), and the processing circuitry extracts the features including at least one of a maximum load factor, a minimum load factor, an average load factor, or a standard deviation that indicates variations in the load factor during a time of getting on and off of the passengers when the train is stopped at the station, the standard deviation being a standard deviation in the load factor when the passengers are getting on and off (as discussed in detail above with respect to claim 1; for example, the automatic train driving device 11C necessarily extracts a maximum boarding section information 23 when the extracted boarding section information 23 is largest; because a maximum load factor, a minimum load factor, an average load factor, and a standard deviation that indicates variations in the load factor during a time of getting on and off of the passengers when the train is stopped at the station, the standard deviation being a standard deviation in the load factor when the passengers are getting on and off are recited in the alternative, it is sufficient to address one of the claimed alternatives).
With respect to claim 5, Ueda teaches the automatic train operation assistance device according to claim 4, wherein the processing circuitry uses the features on a vehicle with a longest time of getting on and off, a vehicle with a largest number of passengers who get off the vehicle, a vehicle with a largest number of passengers who get on the vehicle, or a vehicle with a greatest standard deviation, of the vehicles included in the train, to predict the future operating conditions of the train including the vehicle (as discussed in detail above with respect to claim 1; for example, the automatic train driving device 11C necessarily uses a longest station stop time of the station stop times to predict the driving pattern of the train when the station stop time used to predict the driving pattern of the train is the longest station stop time; because a vehicle with a longest time of getting on and off, a vehicle with a largest number of passengers who get off the vehicle, a vehicle with a largest number of passengers who get on the vehicle, and a vehicle with a greatest standard deviation are recited in the alternative, it is sufficient to address one of the claimed alternatives).
With respect to claim 6, Ueda teaches the automatic train operation assistance device according to claim 1, wherein the processing circuitry outputs the predicted future operating conditions of the train to an automatic train operation system (e.g., 33) installed on the train (as discussed in detail above with respect to claim 1).
With respect to claim 7, Ueda teaches the automatic train operation assistance device according to claim 1, wherein the automatic train operation assistance device is installed on the train (as discussed in detail above with respect to claim 1).
With respect to claim 8, Ueda teaches the automatic train operation assistance device according to claim 1, wherein the automatic train operation assistance device is installed in an operation control apparatus to control the operation of the train or in a cloud (as discussed in detail above with respect to at least claim 1; because installed in an operation control apparatus to control the operation of the train and installed in a cloud are recited in the alternative, it is sufficient to address one of the claimed alternatives).
With respect to claim 9, Ueda teaches the automatic train operation assistance device according to claim 8, wherein the operation control apparatus or the cloud performs wireless communications with a plurality of the trains, and the processing circuitry acquires the operation data on the plurality of trains from the data collection device installed in the operation control apparatus or in the cloud (as discussed in detail above with respect to at least claims 1 and 8; because the operation control apparatus performs wireless communications with a plurality of the trains and the cloud performs wireless communications with a plurality of the trains are recited in the alternative, it is sufficient to address one of the claimed alternatives; because the data collection device installed in the operation control apparatus and the data collection device installed in the cloud are recited in the alternative, it is sufficient to address one of the claimed alternatives).
With respect to claim 10, Ueda teaches the automatic train operation assistance device according to claim 8, wherein the processing circuitry acquires the operation data from the data collection device installed on the train via communication (as discussed in detail above with respect to claim 1, and apparent from at least Figs. 19-21 in view of at least ¶ 0064-0068).
With respect to claim 11, Ueda teaches the automatic train operation assistance device according to claim 8, wherein the processing circuitry predicts, for a plurality of the trains, the future operating conditions of each train (as discussed in detail above with respect to claim 1).
With respect to claim 12, Ueda teaches the automatic train operation assistance device according to claim 8, wherein the processing circuitry extracts, as the features, first features on the train for which prediction is performed and, in addition, second features on a preceding train of the train for which prediction is performed (as discussed in detail above with respect to claim 1).
With respect to claim 19, Ueda teaches an automatic train operation assistance method, comprising: acquiring operation data including an operation of a train and load factors of vehicles of the train from a data collection device to collect equipment data on the train; extracting using the operation data, operation data on an inter-station including a travel time taken by the train to travel from a first station to a second station and a stop time for which the train is stopped at the first station or the second station, as features; constructing a prediction model using the features; and predicting future operating conditions of the train including a future position of the train, using the prediction model and current features (as discussed in detail above with respect to claim 1).
Subject Matter Not Rejected Over the Prior Art
Claim 13 may be allowable if rewritten or amended to overcome the rejections under 35 U.S.C. 112(b) & 35 U.S.C. 101 set forth in this Office action. Currently, claim 13 is rendered nonsensical by virtue of inclusion of numerous issues of indefiniteness, such that it is unclear what exactly is meant by the claim as filed. Whether claim 13 is allowable over the prior art of record will be reevaluated in the event that the claim is rewritten or amended to overcome the rejections under 35 U.S.C. 112(b) & 35 U.S.C. 101 set forth in this Office action. Claims 14-18 depend from claim 13 and are also rejected under 35 U.S.C. 112(b) & 35 U.S.C. 101.
Claim 2, which depends from claim 1, may be allowable if rewritten to overcome the rejections under 35 U.S.C. 112(b) & 35 U.S.C. 101 set forth in this Office action and to include all of the limitations of the base claim and any intervening claims. Claim 3 depends from claim 2 and is also rejected under 35 U.S.C. 112(b) & 35 U.S.C. 101.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and is provided on the attached PTO-892 Notice of References Cited form.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN ZALESKAS whose telephone number is (571)272-5958. The examiner can normally be reached M-F 8:00 AM - 4:00 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Logan Kraft can be reached at 571-270-5065. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JOHN M ZALESKAS/Primary Examiner, Art Unit 3747