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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 12/17/2025 has been entered.
Introduction
The following is a non-final Office action in response to Applicant’s RCE submission filed on 12/17/2025. Currently claims 1-8, 10 are pending and claims 1 and 8 are independent. Claims 1, 7, 8, 10, have been amended from the previous claim set dated 7/29/2025. No claims have been added and claim 8 is cancelled.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. CN202110188356.2, filed on 2/18/2021.
Response to Amendments
Applicant’s amendments are acknowledged and necessitated the new grounds of rejection in this Office Action. In light of the amendments, the 35 USC §112 rejections have been withdrawn.
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 1-8, 10 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), specifically an abstract idea, without significantly more. With respect to claims 1-8, 10, following guidance contained within MPEP 2106, the inquiry for patent eligibility follows two steps: Step 1: Does the claimed invention fall within one of the four statutory categories of invention? Step 2A (Prong 1): Is the claim “directed to” an abstract idea? Step 2A (Prong 2): Is the claim integrated into a practical application? Step 2B: Does the claim recite additional elements that amount to “significantly more” than the abstract idea?
In accordance with these steps, the Examiner finds the following:
Step 1: Claim 1 and its dependent claims (claims 2-7) are directed to a statutory category, namely a system/machine. Claim 8 and its dependent claims (claims 10) are directed to a statutory category, namely a method.
Step 2A (Prong 1): Claims 1 and 8, which are substantially similar claims to one another, are directed to the abstract idea of “Mental processes”, or more particularly, “Concepts performed in the human mind (including an observation, evaluation, judgment, opinion) (See MPEP 2106).” In this application that refers to using a computer system to manage, analyze, and evaluate the scheduling of trains. To clarify this further, the Applicant’s disclosed invention is a conceptual system meant to perform the same function that a train dispatcher for a subway system performs. The abstract elements of claims 1 and 8 recite in part “Evaluate the difference…Calculate passenger flow…Determine if adjustment needed…Determine adjustment scheme…Optimize and adjust operation diagram…Acquire operation data…Filter data…Convert data…Perform analysis…Calculate deviation…Extract capacity data…”. Dependent claims 10 add to the abstract idea the following limitations which recite in part “Set adjustment threshold…”. All of these additional limitations, however, only serve to further limit the abstract idea, and hence are nonetheless directed towards fundamentally the same abstract idea as independent claims 1, 8. Dependent claims 2-7 does not include any limitations that are directed toward the abstract idea and will be addresses in either the Step 2A (Prong 2) or Step 2B analysis below.
Step 2A (Prong 2): Independent claims 1, 8, which are substantially similar claims to one another, do not contain additional elements, either considered individually or in combination, that effectively integrate the exception into a practical application of the exception. These claims do include the limitation that recites in part “Data analysis module…passenger flow module…adjustment module…train supervision system…data interface…database…” which limits the claims to a networked/computer based environment, but this is insufficient with respect to integration into a practical application because it is merely applying the abstract idea to a general computer (See MPEP 2106.05(f)).
Dependent claims 2-7 add the additional element which recites in part “Interface…Processing unit…Checking unit…Data analysis unit…Adjustment module…Adjustment unit…time adjustment unit…” which again limits the claims to a networked/computer based environment, but this is again insufficient with respect to integration into a practical application because it is merely applying the abstract idea to a general computer (See MPEP 2106.05(f)).
Additionally, dependent claims 10 do not include any additional elements to conduct a further Step 2A (Prong 2) analysis.
Step 2B: Independent claims 1, 8 which are substantially similar claims to one another, include additional elements, when considered both individually and as an ordered combination, which are insufficient to amount to significantly more than the judicial exception. The additional elements of these claims recite in part “Data analysis module…passenger flow module…adjustment module…train supervision system… data interface…database…”. These items are not significantly more because these are merely the software and/or hardware components used to implement the abstract idea (manage, analyze, and evaluate the scheduling of trains) on a general purpose computer (See MPEP 2106.05(f)).
Dependent claims 2-7 include additional elements, when considered both individually and as an ordered combination and in view of their respective independent claims, which are insufficient to amount to significantly more than the judicial exception. Specifically, dependent claims 2-7 include the additional element which recites in part “Interface…Processing unit…Checking unit…Data analysis unit…Adjustment module…Adjustment unit…time adjustment unit …”. These are similar additional elements that are addressed above in claims 1, 8, and are not significantly more because these are merely the software and/or hardware components used to implement the abstract idea (manage, analyze, and evaluate the scheduling of trains) on a general purpose computer (See MPEP 2106.05(f)).
Additionally, dependent claims 10 do not include any additional elements to conduct a further 2B analysis.
Accordingly, whether taken individually or as an ordered combination claims 1-8, 10 are rejected under 35 USC § 101 because the claimed invention is directed to a judicial exception, an abstract idea, without significantly more.
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 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.
Claims 1-7, 10 are rejected under 35 U.S.C. 103 as being unpatentable over Wang (US 20210001906 A1) in view of Liu et al. (CN 111361609 B) further in view of Luo et al. (CN 111055891 A)
Regarding claim 1 (Amended), Wang discloses a system for automatically adjusting a planned train operation diagram (Wang ABS - The present invention relates to an intelligent train operation adjustment system…the intelligent train operation adjustment module adjusts a working diagram in real time based on the real-time passenger flow and an operation result of the matching module, and adds or removes a train and arranges a path plan for the train with reference to a dispatching plan and device information), a passenger flow data matching module and an operation diagram adjustment module which are connected in sequence (Wang ¶6 - a real-time passenger flow and transport capacity matching module, and an intelligent train operation adjustment module), wherein the train operation data analysis module is connected with the operation diagram adjustment module (Wang Fig. 2); the passenger flow data matching module calculates actual passenger flow distribution based on vehicle weighing passenger flow data and an automatic fare collection (AFC} passenger flow data, and matches the same with the actual operation diagram to obtain a passenger flow matching result (Wang ¶39 - As shown in FIG. 2, the system mainly includes three parts: a real-time passenger flow counting system based on video counting, train weighing, and AFC, a real-time passenger flow and transport capacity matching system, and an intelligent train operation adjustment system. The real-time passenger flow counting system counts current real-time passenger flow based on video identification-counting information, train weighing information, AFC counting information, historical data, and the like. The real-time passenger flow and transport capacity matching system matches a current passenger flow demand with a current transport capacity of a line, and determines, with reference to a current device status, how to adjust the transport capacity); and the operation diagram adjustment module optimizes and adjusts an original planned operation diagram according to the operation diagram evaluation result and the passenger flow matching result combined with driving conditions of a line and constraints of transportation resources (Wang ¶31 - The intelligent train operation adjustment system adjusts a working diagram in real time based on the real-time passenger flow and an operation result of the matching system, and adds or removes a train and arranges a path plan for the train with reference to a dispatching plan and device information); filter out invalid data (Wang ¶40 - After a station obtains large passenger flow data through video and AFC, whether the large passenger flow data is caused by a device fault or is an outstanding abnormal case on a day is determined {i.e. invalid data is filtered out} based on the historical database and device status information, and a real-time passenger flow demand at this time is finally obtained);
and extract transportation capacity data based on the actual operation data to improve an accuracy of transportation capacity and traffic volume matching (Wang ¶25 - Accuracy of passenger flow identification can be effectively increased by using a passenger flow technology based on a video fusion AFC and train weighing, and in addition, a passenger flow section is effectively estimated with reference to a large quantity of historical data. A transport capacity is accurately matched with passenger flow. A high-performance machine automatically matches section passenger flow with a currently planned transport capacity of the system in time)
Wang lacks a train operation data analysis module, the train operation data analysis module evaluates the difference between an actual operation diagram and a planned operation diagram based on an automatic train supervision system (ATS) historical operation data to obtain an operation diagram evaluation result; acquire actual operation data through a train operation data interface, and store the actual operation data in a database, wherein the actual operation data comprises an arrival time of each of trains at each of station tracks, a departure time of each of the trains at each of the station tracks, a difference from a planned time, a destination, and direction; convert the arrival time and the departure time into operation process data according to a train travel sequence; perform statistical analysis on a large amount of data in each of operation processes; calculate a deviation between planned values and actual values of operation process parameters to obtain a reference process time, wherein the reference process time comprises at least one of fitting values of actual stop time, a section operation time, and a turn-back time at each of positions.
Liu, from the same field of endeavor, teaches a train operation data analysis module (Liu - ATS (Automatic Train Supervision System)), the train operation data analysis module evaluates the difference between an actual operation diagram and a planned operation diagram based on an automatic train supervision system (ATS} historical operation data to obtain an operation diagram evaluation result (Liu - establishing communication connection with the ATS; receiving the operation plan sent by the ATS, and driving according to the operation plan; the operation plan comprises the plan arrival time and the planned departure time of the train at each station: when the train arrives at the station, comparing the actual arrival time and the planned arrival time of the train arriving at the current station; if the train is early or late, adjusting the stop time of the train at the current station and the running time of the next interval; making the actual arrival time of the train arriving the next station consistent with the planned arrival time, wherein the next interval is the driving circuit between the current station and the next station; when the train leaving station, comparing the actual departure time of the train leaving the current station and the planned departure time; if the train is early or late, adjusting the running time of the train in the next interval; making the actual arrival time of the train arriving at the next station consistent with the planned arrival time); acquire actual operation data through a train operation data interface, and store the actual operation data in a database, wherein the actual operation data comprises an arrival time of each of trains at each of station tracks, a departure time of each of the trains at each of the station tracks, a difference from a planned time, a destination, and direction (Liu - ATS (Automatic Train Supervision System, automatic train monitoring system) for collecting the train actual to the station or departure time to the station or leave the train, to the actual station or departure time and train operation plan or the departure time. when the train arrives, if earlier or late train, the train at the station stop time and running time of the next interval); convert the arrival time and the departure time into operation process data according to a train travel sequence (Liu - As an embodiment, operation plan further includes a minimum dwell time of each station, if the train breakfast, then adjusting the train on the current station stop time T1, the train reaches the actual arrival time of the next station consistent with the planned arrival time, wherein, T1=T2 + T3, wherein, T2 is a train of current station plan stop time, planned stop time for planning the arrival of the difference between time and scheduled departure time, T3 is the difference between train scheduled arrival time and the actual arrival time); perform statistical analysis on a large amount of data in each of operation processes; calculate a deviation between planned values and actual values of operation process parameters to obtain a reference process time, wherein the reference process time comprises at least one of fitting values of actual stop time, a section operation time, and a turn-back time at each of positions (Liu - a first adjusting module; when the train arrives at the station, it is used for comparing the actual arrival time and the planned arrival time of the train arriving at the current station; if the train is early or late, adjusting the stop time of the train at the current station and the running time of the next interval; making the actual arrival time of the train arriving at the next station and the planned arrival time consistent, wherein the next interval is the driving line between the current station and the next station; the second adjusting module, train leaving station, for comparing the train leaving the actual departure time of the current station and the planned departure time; if the train is early or late, adjusting the running time of the train in the next interval, making the actual arrival time of the train arriving the next station consistent {i.e. fitting} with the planned arrival time).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the intelligent train methodology/system of Wang by including the train adjustment techniques of Liu because Liu discloses “the invention realizes the active adjustment of the train operation, makes the adjustment of the train more accurate and efficient, reduces the load of the vehicle ground communication network (Liu ABS)”. Additionally, Wang further details “an intelligent train operation adjustment system (Wang ABS)” so it would be obvious to consider including the additional train adjustment techniques that Liu discloses because it increases accuracy of the adjustments made within the system of Wang.
Wang further lacks adjust a planned operation parameter only if a difference between the reference process time in an operation data evaluation result and the planned operation parameter exceeds an adjustment threshold, wherein the operation diagram adjustment module optimizes and adjusts the original planned operation diagram by: setting an initial adjustment value of a planned parameter as the reference process time, iteratively checking whether a front and rear train spacing after adjustment is satisfactory, and if the front and rear train spacing is not satisfactory, automatically reducing an adjustment range of the planned parameter until the front and rear train spacing is satisfactory to generate a new planned operation diagram.
Luo, from the same field of endeavor, teaches adjust a planned operation parameter only if a difference between the reference process time in an operation data evaluation result and the planned operation parameter exceeds an adjustment threshold (Luo - it is necessary to adjust the departure interval of a plurality of train in current of the train running chart, shorten the departure interval, so as to adjust the neutral interval not less than minimum time, train number needs to be adjusted corresponding to the minimum), wherein the operation diagram adjustment module optimizes and adjusts the original planned operation diagram by: setting an initial adjustment value of a planned parameter as the reference process time, iteratively checking whether a front and rear train spacing after adjustment is satisfactory, and if the front and rear train spacing is not satisfactory, automatically reducing an adjustment range of the planned parameter until the front and rear train spacing is satisfactory to generate a new planned operation diagram (Luo - the train running chart adjusting method of the invention, wherein determining the train number to be increased according to the passenger flow information, with the train of each increase correspondingly, in selecting a plurality of adjusted current running chart object group composed of multiple adjacent of train, train and ensuring the adjusting object group is added corresponding to be increased, the interval between the trains is greater than or equal to the minimum departure interval based on each adjusted object group, calculating the running time of each train of the train to be increased after adding, generating updated train running chart; sending the updated train running chart to the ATS).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the intelligent train methodology/system of Wang by including the train adjustment techniques of Luo because Luo discloses “the train running chart not only can improve the working efficiency, but also plays an important role to the train running safety (Luo)”. Additionally, Wang further details “an intelligent train operation adjustment system (Wang ABS)” so it would be obvious to consider including the additional train adjustment techniques that Luo discloses because it increases the safety and efficiency of the system disclosed by Wang.
Regarding claim 2, Wang in view of Liu further in view of Luo discloses a system for automatically adjusting a planned train operation diagram (Wang ABS - The present invention relates to an intelligent train operation adjustment system…the intelligent train operation adjustment module adjusts a working diagram in real time based on the real-time passenger flow and an operation result of the matching module, and adds or removes a train and arranges a path plan for the train with reference to a dispatching plan and device information).
Liu further teaches the train operation data analysis module comprises a train operation data interface, a train operation data preprocessing unit and a train operation parameter checking unit (Liu - ATS (Automatic Train Supervision System)…each functional unit in each embodiment of the present invention can be integrated in a processing module, also can be individual physical presence of each unit, also can be two or more than two units integrated in one module. The integrated module can be implemented in the form of hardware, and also can be implemented in the form of software function module. The integrated module may be stored in a computer-readable storage medium if implemented in the form of a software function module).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the intelligent train methodology/system of Wang by including the train adjustment techniques of Liu because Liu discloses “the invention realizes the active adjustment of the train operation, makes the adjustment of the train more accurate and efficient, reduces the load of the vehicle ground communication network (Liu ABS)”. Additionally, Wang further details “an intelligent train operation adjustment system (Wang ABS)” so it would be obvious to consider including the additional train adjustment techniques that Liu discloses because it increases accuracy of the adjustments made within the system of Wang.
Regarding claim 3, Wang in view of Liu further in view of Luo discloses the passenger flow data matching module comprises a passenger flow data interface, a passenger flow data analysis unit and a transportation capacity and traffic volume matching unit (Wang Fig. 2).
Regarding claim 4, Wang in view of Liu further in view of Luo discloses the operation diagram adjustment module comprises a starting scheme adjustment module and an operation parameter adjustment module (Wang Fig. 2).
Regarding claim 5, Wang in view of Liu further in view of Luo discloses the starting scheme adjustment module comprises a routing scheme adjustment unit, an interval scheme adjustment unit, and a vehicle bottom use scheme adjustment unit (Wang Fig. 2).
Regarding claim 6, Wang in view of Liu further in view of Luo discloses the operation parameter adjustment module comprises a stop time adjustment unit, a section operation time adjustment unit, and a turn-back time adjustment unit (Wang Fig. 2).
Regarding claim 7, Wang in view of Liu further in view of Luo discloses data of operation data analysis module and passenger flow matching module are stored in a unified database server, which can store and quickly read and write a large number of multi-source heterogeneous data (Wang Fig. 2).
Claims 8, 10 are rejected under 35 U.S.C. 103 as being unpatentable over Wang (US 20210001906 A1) in view of Liu et al. (CN 111361609 B)
Regarding claim 8, Wang discloses an adjustment method adopting the system for automatically adjusting the planned train operation diagram according to claim 1 (Wang ABS - The present invention relates to an intelligent train operation adjustment system…the intelligent train operation adjustment module adjusts a working diagram in real time based on the real-time passenger flow and an operation result of the matching module, and adds or removes a train and arranges a path plan for the train with reference to a dispatching plan and device information) comprising: conducting passenger flow analysis based on vehicle weighing data and automatic fare collection (AFC) data, and conducting transportation capacity and a traffic volume matching in combination with an actual train operation data in the step 1 to obtain a transportation capacity and traffic volume matching result (Wang ¶39 - As shown in FIG. 2, the system mainly includes three parts: a real-time passenger flow counting system based on video counting, train weighing, and AFC, a real-time passenger flow and transport capacity matching system, and an intelligent train operation adjustment system. The real-time passenger flow counting system counts current real-time passenger flow based on video identification-counting information, train weighing information, AFC counting information, historical data, and the like. The real-time passenger flow and transport capacity matching system matches a current passenger flow demand with a current transport capacity of a line, and determines, with reference to a current device status, how to adjust the transport capacity); determining whether a routing scheme, an interval scheme and a vehicle bottom use scheme need to be adjusted based on the transportation capacity and traffic volume matching result in the step 2, and determining an adjustment scheme in combination with actual line transportation capacity resource allocation if yes (Wang ¶20 - determining, based on a transport capacity determining situation and a device status, whether the current capacity needs to be increased or decreased; if the capacity needs to be increased, determining, based on a minimum system operation interval and a working diagram of a current in-service train, whether a condition for continuing increasing the capacity is met…after a transport capacity adjustment request is confirmed, checking, by the system, a dispatching plan and device status information; determining to wake up a train at an optimum location based on the capacity increasing request, and for the capacity decreasing request, providing a train that is suggested to withdraw from operation, a withdrawal path, and a sleep location); and (5) adjusting and optimizing the planned operation diagram based on the adjustment of the operation parameters and the adjustment of a starting scheme in the steps 3 and 4 (Wang ¶31 - The intelligent train operation adjustment system adjusts a working diagram in real time based on the real-time passenger flow and an operation result of the matching system, and adds or removes a train and arranges a path plan for the train with reference to a dispatching plan and device information).
Wang lacks preprocessing and analyzing train operation data recorded by an automatic train supervision system (ATS), and evaluating the difference between planned values and actual values of operation parameters to obtain an operation data evaluation result; determining whether the operation parameters of stop time, section operation time and turn-back time need to be adjusted based on the operation data evaluation result in the step 1, and determining an adjustment scheme in combination with the constraints of actual line driving conditions if yes.
Liu, from the same field of endeavor, teaches preprocessing and analyzing train operation data recorded by an automatic train supervision system (ATS), and evaluating the difference between planned values and actual values of operation parameters to obtain an operation data evaluation result (Liu - establishing communication connection with the ATS; receiving the operation plan sent by the ATS, and driving according to the operation plan; the operation plan comprises the plan arrival time and the planned departure time of the train at each station: when the train arrives at the station, comparing the actual arrival time and the planned arrival time of the train arriving at the current station); determining whether the operation parameters of stop time, section operation time and turn-back time need to be adjusted based on the operation data evaluation result in the step 1, and determining an adjustment scheme in combination with the constraints of actual line driving conditions if yes (Liu - For example, if the train evening point, the actual departure time of the train is later than the planned departure time; the VOBC of the train calculates the time difference of the late point; for example, the actual departure time is 9: 00; the planned departure time is 8: 50; the time difference of the late point is 10 minutes; the VOBC of the train according to the time difference of the late point; properly shortening the running time of the train in the next interval; the VOBC of the train controls the train operation according to the running time of the next interval after adjusting; the actual arrival time of the train arriving at the next station is the same as the planned arrival time. In this embodiment, shortening the train running time of the next interval 10 minutes, the train reaches the next station of the actual arrival time and plan to the station time. if the train is early, the specific implementation is the same with the method).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the intelligent train methodology/system of Wang by including the train adjustment techniques of Liu because Liu discloses “the invention realizes the active adjustment of the train operation, makes the adjustment of the train more accurate and efficient, reduces the load of the vehicle ground communication network (Liu ABS)”. Additionally, Wang further details “an intelligent train operation adjustment system (Wang ABS)” so it would be obvious to consider including the additional train adjustment techniques that Liu discloses because it increases accuracy of the adjustments made within the system of Wang.
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the intelligent train methodology/system of Wang by including the train adjustment techniques of Liu because Liu discloses “the invention realizes the active adjustment of the train operation, makes the adjustment of the train more accurate and efficient, reduces the load of the vehicle ground communication network (Liu ABS)”. Additionally, Wang further details “an intelligent train operation adjustment system (Wang ABS)” so it would be obvious to consider including the additional train adjustment techniques that Liu discloses because it increases accuracy of the adjustments made within the system of Wang.
Regarding claim 10, Wang in view of Liu discloses setting an adjustment threshold for a section full load rate (Wang ¶18 - determining, based on information of passenger flow in coaches of a train that is to enter a station, whether a transport capacity meets a real-time requirement), adjusting the starting scheme if a full load rate in the transportation capacity and traffic volume matching result obtained in the step 2 exceeds the threshold, and otherwise, conducting no adjustment ((Wang ¶20 - determining, based on a transport capacity determining situation and a device status, whether the current capacity needs to be increased or decreased; if the capacity needs to be increased, determining, based on a minimum system operation interval and a working diagram of a current in-service train, whether a condition for continuing increasing the capacity is met…after a transport capacity adjustment request is confirmed, checking, by the system, a dispatching plan and device status information; determining to wake up a train at an optimum location based on the capacity increasing request, and for the capacity decreasing request, providing a train that is suggested to withdraw from operation, a withdrawal path, and a sleep location).
Response to Arguments
Applicant's arguments filed 12/17/2025 have been fully considered but they are not persuasive and/or are moot in light of the new rejections addressed above.
Regarding the arguments related to the 35 USC § 112 rejections, as addressed above, the rejections are withdrawn in light of the amendments.
Regarding the arguments related to the 35 USC § 101 rejections, as addressed above according to the guidance for 35 USC § 101 rejections contained within MPEP 2106, the Examiner maintains that the claimed invention is an abstract idea, without significantly more, and not integrated into a practical application.
Applicant first argues that the claimed invention is patent eligible because it is analogous to claim 3 if Example 47. Examiner does not find this persuasive because within Example 47, the system itself is able to perform the functionality of blocking the traffic, however within Applicant’s claims it is not clear that the system can perform the functionality adjusting actual trains.
Examiner will note that the amendments bring the claims closer to overcoming the 101 rejection, however, it is unclear to examiner how the train adjustment actually occurs. While it is clear that the train diagram is being adjusted, it is not clear how that translates to the actual trains being adjusted. Including claim language which ties actual trains and the diagram together (e.g. claiming actual train cars which are controlled by the diagram) would address this issue.
Finally, Applicant argues that “optimizing and adjusting” are significantly more and overcome the rejection within the Step 2B analysis. Examiner does not find this persuasive because the identified limitations are not interpreted as additional elements but rather elements of the abstract idea and are considered within the Step 2A (Prong 1) analysis.
Regarding the 35 USC § 103 rejections on the previous Office action, Applicant amended the independent claims to further limit the claims with respect to adjusting diagrams according to train spacing. In light of this amendment, Examiner agrees that the original references did not specifically cite to these limitations, however the amendment necessitated further search and consideration. As a result of this further search and consideration, prior art was found to teach these limitations and is now cited (See Luo above). As such, Applicant’s arguments (with respect to the independent claims and their respective dependent claims) are unpersuasive.
Conclusion
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/MICHAEL R KOESTER/Examiner, Art Unit 3624
/Jerry O'Connor/Supervisory Patent Examiner,Group Art Unit 3624