DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Claims 1-5, 7, 9, 11, 18-20, 24-25, 32-34, and 43-44 filed on 07/14/2021 and Amendments filed on 05/13/2024 and 02/27/2025 have been examined.
This Office Action is in response to the Applicant’s amendments and remarks filed on 09/24/2025. Claims 1 and 18 have been amended. Claims 4-6, 8, 10, 12-17, 21-23, 26-31, 35-42, and 44-46 have been cancelled by the Applicant. Claims 1-3, 7, 9, 11, 18-20, 24-25, 32-34, and 43 are currently pending and addressed below.
Response to Remarks/Arguments
Applicant’s accompanying amendments and arguments, on page 6 of the Applicant Arguments/Remarks (hereinafter referred to as the “Remarks”), filed 09/24/2025, with respect to the claim objection to claim 1 stating “… Claim 1 stands objected to because of the following informalities: line 3 of claim 1 should read "...said system including orchestration means connected to:". Applicant has made the appropriate correction … and therefore withdrawal of this objection is warranted…” has been considered and is persuasive. Therefore, the Examiner has withdrawn the Claim Objection to claim 1.
Applicant’s accompanying amendments and arguments, on pages 6-7 of the Applicant Arguments/Remarks (hereinafter referred to as the “Remarks”), filed 09/24/2025, with respect to the rejection of claims 1-3, 7, 9, 11, 18-20, 24-25, 32-34, and 43-44 under 35 U.S.C. 112(a) stating “… claim 1 stands rejected for reciting the feature "strategy generator", which allegedly lacks support in Applicant's specification. This rejection is respectfully traversed… Claim 1 is amended to define the computer and strategy algorithm that performs the claimed functions, from which support is derived from Applicant's specification, as originally filed, in claim 44 and page 46, line 9, as well as Figure 2. Specifically, the description discloses There exist a range of 'automated planning engines' (box 6 in Figure 2) in the academic literature that accomplish this for hybrid (i.e. discrete and continuous) formulations. Most of these hybrid planning engines input a language equivalent to a community accepted syntax called PDDL+… A skilled person is equipped with sufficient information to put the claimed invention into practice. In addition, the applicant discloses using the planning engine language PDDL+, used in a particular example to utilize the strategy generator in the manner claimed. The applicant was clearly therefore in possession of the invention at the time of filling… amendments to claim 1 have overcome the issues raised under 35 U.S.C. 112(a) and Applicant respectfully requests the rejection to claims 1-3, 7, 9, 11, 18-20, 24-25, 32-34, and 43-44 be withdrawn…” have been considered and are not persuasive. The Examiner submits that the present application specification does not clearly provide a disclosure of the computer and algorithm that performs the claimed functions recited for the strategy generator in sufficient detail, and that amending claim 1 to recite “a computer operating a planning engine that contains traffic simulator software that simulates the operation of a strategy on the initial traffic state…” does not resolve the lack of disclosure of a computer performing the claimed functions in the application specification, therefore one of ordinary skill in the art cannot reasonably conclude that the inventor possessed the claimed subject matter at the time of filing. Refer to MPEP §2161.01. Therefore, the rejection of claims 1-3, 7, 9, 11, 18-20, 24-25, 32-34, and 43 under 35 U.S.C. 112(a) are maintained by the Examiner.
Applicant’s accompanying amendments and arguments, on pages 7-8 of the Applicant Remarks, filed 09/24/2025, with respect to the rejection of claims 1-3, 7, 9, 11, 18-20, 24-25, 32-34, and 43-44 under 35 U.S.C. 112(b) stating “… Claim 1 is amended to define the computer and strategy algorithm that performs the claimed functions, from which support is derived from Applicant's specification, as originally filed, in claim 44 and page 46, line 9, as well as Figure 2. Specifically, the description discloses There exist a range of 'automated planning engines' (box 6 in Figure 2) in the academic literature that accomplish this for hybrid (i.e. discrete and continuous) formulations. Most of these hybrid planning engines input a language equivalent to a community accepted syntax called PDDL+… A skilled person is equipped with sufficient information to put the claimed invention into practice. In addition, the applicant discloses using the planning engine language PDDL+, used in a particular example to utilize the strategy generator in the manner claimed. The applicant was clearly therefore in possession of the invention at the time of filling… Applicant respectfully requests the rejection to claims 1-3, 7, 9, 11, 18-20, 24-25, 32-34, and 43-44 be withdrawn…” have been considered and are not persuasive. The written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed associated functions and to clearly link the structure, material, or acts to the associated functions. The written description does not describe or further define “strategy generator” beyond these general terms so there is insufficient disclosure of the corresponding structure and material and the written description does not link a defined structure or material to the claimed functions. Additionally, the Examiner also submits that amending claim 1 to recite “a computer operating a planning engine that contains traffic simulator software that simulates the operation of a strategy on the initial traffic state…” does not resolve the lack of disclosure of a computer performing the claimed functions in the application specification. Therefore, the rejection of claims 1-3, 7, 9, 11, 18-20, 24-25, 32-34, and 43 under 35 U.S.C. 112(b) are maintained by the Examiner.
Applicant’s accompanying amendments and arguments, on pages 8-23 of the Applicant Remarks, filed 09/24/2025, with respect to the rejection of claim 1 and its corresponding dependent claims under 35 U.S.C. 103 stating “… In an effort to expedite prosecution and without making any admissions, Applicant amends claim 1 to include a computer operating a planning engine that contains traffic simulator software that simulates the operation of a strategy on the initial traffic state using modelled data for the domain model and a simulation… Applicant respectfully submits David, Bouillet et al., Green et al., Mantalvanos, Dhondse et al., Tourrilhes et al., Chang et al. or any combination thereof, do not teach, disclose, or suggest a computer operating a planning engine that contains traffic simulator software that simulates the operation of a strategy on the initial traffic state using modelled data for the domain model and a simulation… Mantalvanos discloses a traffic signal control system (known as "FITS") using a multi- agent architecture and fuzzy logic for dynamic control of traffic lights… There is no indication that FITS itself takes those simulated alternatives and directly turns them into a deployed strategy in real time. By contrast, claim 1's planning engine automatically generates strategy options using simulation and feeds the chosen strategy's instructions into the orchestration for execution. In Mantalvanos, any new strategy (e.g., a different signal coordination scheme or rerouting plan) would likely require human analysis of the simulation outputs and manual reconfiguration (or new fuzzy rules). Mantalvanos does not disclose a formal "domain model" with defined processes, actions, and events as claimed… Nothing in Mantalvanos suggests that its fuzzy logic rules operate on such a formal domain model… FITS allows the user to select a control policy or objective… While this means the user can influence the system's goal, it is done implicitly through fuzzy rules, not by writing the goal as a formal logical term composed of domain model elements… Mantalvanos also lacks explicit disclosure of domain model constructs and a logical goal term, making the claimed features distinguishing over this reference… Tourrilhes et al.'s contribution is the concept of using input data adaptors to standardize and feed sensor information into multiple subsystems… Tourrilhes et al. is only relevant to a minor aspect of the claim (data adaptors), and Tourrilhes et al. provides no guidance on the central idea of testing traffic management strategies in a simulation engine… Tourrilhes et al. itself therefore does not render obvious any of the newly added simulation/planning features of claim 1… Thus, claim 1, as amended, is patentable over David, Bouillet et al., Green et al., Mantalvanos, Dhondse et al., Tourrilhes et al., Chang et al., or any combination thereof…” have been considered and are not persuasive.
Firstly, as provided below in the rejection of claim 1 under 35 U.S.C. 103, David discloses a traffic control system that utilizes sensor information and prediction algorithms to identify congestion scenarios for road traffic, while, under the broadest reasonable interpretation of amended claim 1, Mantalvanos US 20130099942 (“Mantalvanos”) teaches a strategy generator configured to create at least one traffic management strategy and a set of control instructions for all infrastructure means relevant to the created traffic management strategy, to achieve the goal set by the user (See at least [0065]-[0071] of Mantalvanos – “… The traffic manager has many tools available within the FITS system to manage traffic and meet local policy objectives such as… FITS can reduce vehicle emissions by reducing delays and congestion within the network, however it can be set to adjust the optimisation of the signal timings to minimise emissions … “), by using: a computer operating a planning engine that contains traffic simulator software that simulates the operation of a strategy on the initial traffic state using modelled data for the domain model and a simulation of a traffic management strategy on the persistent data, using the process, action, and event elements present in the domain model (See at least [0072]-[0078] – “… The real-time simulation system models the queues, waiting times and stops at intersections, so it can also estimate the time for cars spent in the various travel-modes: cruising, accelerating, decelerating, idling and stop-and-go. This data can be used to estimate emissions and pollution…. The FITS system controls the real-time simulator. The system collects data from each junction and feeds the results into an integrated server. The speed of FITS, twenty simulation updates per second, means it is possible to provide an accurate real time model of what the traffic situation is. In addition, the system can detect more subtle changes in the traffic and over time give a more accurate view of behavioural patterns allowing a city to do more. The real time traffic simulation model can be animated remotely in 2 or 3D modes. FITS reads the states of all available detectors and uses this information to update a real-time traffic simulation model typically some 20 times per second… A simulation system can be set to continuously run scenarios of various situations within the controlled area… FITS can comprise a pollution reader that detects the level of pollution at a given junction and adjust the timing accordingly to reduce pollution levels…” and [0087] of Mantalvanos – “…The system provides a graphical configuration tool with the junction layout. The configuration tool is an integrated user-friendly tool for setting up the FITS traffic signal control… When user presses "save" the program creates all the configuration files needed in the FITS-control. These files will be transferred to the actual controller in the field to be used by the FITS-signal control software…” Examiner notes that updating a real-time traffic simulation model reads on the limitation of simulating the operation of a strategy on the initial traffic state as an initial traffic state is required to continuously run scenarios and update a real-time traffic simulation model. Examiner also notes that “domain model” is broad and could be the conceptual representation of the simulation model such as the junction layout, properties, fuzzy logic, and signal control rules assigned by a user), and wherein said goal is written as a logical term the components of which are data source means in the form of processes, actions, or events in the domain model that the generated traffic management strategy options can change (See at least [0088] of Mantalvanos – “… In the FITS-system, however, each signal group is aware of the traffic situation of any other signal group. This means they can negotiate with each other about the overall optimal control strategy. The rules for this negotiation are defined by the fuzzy logic, which can be chosen by the user. By fuzzy logic the user describes signal control rules in a way that resembles the natural language. This makes the "programming" of the signal controllers more user-friendly and more traffic engineering oriented than in the present systems. With the fuzzy rules it is possible to implement the chosen traffic control policy for example to prioritize the main street, prioritizing public transport, minimizing emissions instead of delays etc…”).
Secondly, the Examiner notes that although argued above by the Applicant, amended claim 1 does not specifically recite that the planning engine automatically generates strategy options using simulation and feeds the chosen strategy's instructions into the orchestration for execution, therefore, the Applicant’s interpretation of Mantalvanos, particularly that any new strategy would likely require human analysis of the simulation outputs and manual reconfiguration still reads on the broadest reasonable interpretation of amended claim 1. Therefore, the rejection of claim 1 and its corresponding dependent claims under 35 U.S.C. 103 are maintained by the Examiner.
Finally, as previously provided above and detailed below in the rejection of claim 1 under 35 U.S.C. 103, David discloses a traffic control system that utilizes sensor information and prediction algorithms to identify congestion scenarios for road traffic, while Mantalvanos teaches a traffic signal control system that uses a simulator and collected data to aid in providing dynamic control of a plurality of traffic signals based on selected policies (i.e., goals) chosen by a user. Moreover, Tourrilhes, in combination with at least David and Mantalvanos, further teaches wherein the system includes one or more input data adaptors to process information from multiple data source means into the correct form of processes, actions, or events in the domain model for use by the strategy generator (See at least [0038] of Tourrilhes – “forwarders 120a-m may collect information from …sensor controllers … dispatch the information to one or more of the back-end applications 120a-f via adaptors 130a-f corresponding to the back-end applications 120a-f. Each of the back-end applications 140a-f may use its own data format and procedures. The adaptors 130a-f convert messages from the forwarders 120a-m to a format compatible with a corresponding back-end application…”). The Examiner submits that it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the traffic strategy and management system as disclosed in David with Mantalvanos to also include the feature of the system including one or more input data adaptors to process information from multiple data source means into the correct form of processes, actions, or events in the domain model for use by the strategy generator as taught by Tourrilhes, with a reasonable expectation of success, in order for collected data to be compatible with network software or visualization tools making use of the data as specified in at least [0038] of Tourrilhes. Therefore, the rejection of claim 1 and its corresponding dependent claims under 35 U.S.C. 103 are maintained by the Examiner.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that use the word “means” and are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) using the term “means” is coupled with functional language without reciting sufficient structure to perform the recited function. Such claim limitation(s) is/are:
“orchestration means” provided in claim 1
The specification and drawings were used to verify that claim limitations using the term “means” recite sufficient structure, material, or acts to entirely perform the recited functions:
Specification – “The orchestration component 4 performs this
function. For example, it continuously compares real-time with anticipated traffic flows using input data adaptors 6 and the strategy generator's 2 simulator output … it must load, execute and unload in the correct sequence from dozens of traffic controllers using the traffic control computer”
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“strategy generator” provided in claim 1
The specification and drawings were used to define the generic placeholders specified above (item a):
Specification – The corresponding structure or material as performing the claimed function in item listed above is not disclosed in the specification.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-3, 7, 9, 11, 18-20, 24-25, 32-34, and 43 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 recites claim limitation “strategy generator”. Further descriptions for strategy generator are not provided for these limits beyond their general terms. Therefore, it is not made clear to one in the ordinary skill in that art and not properly described in the specification of what the strategy generator is in terms of structure, material, or apparatus to be linked to the claim’s functions.
Claims 2-3, 7, 9, 11, 18-20, 24-25, 32-34, and 43 are rejected by virtue of dependency on claim 1.
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 1-3, 7, 9, 11, 18-20, 24-25, 32-34, and 43 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 limitations “strategy generator” which invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed associated functions and to clearly link the structure, material, or acts to the associated functions. The written description does not describe or further define “strategy generator” beyond these general terms so there is insufficient disclosure of the corresponding structure and material and the written description does not link a defined structure or material to the claimed functions. Therefore, independent claim 1 is indefinite and rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Claims 2-3, 7, 9, 11, 18-20, 24-25, 32-34, and 43 are rejected by virtue of dependency on claim 1.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (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 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.
Claims 1-3, 7, 9, 11, 18-20, 24-25, and 32-34 are rejected under 35 U.S.C. 103 as being unpatentable over David US 20140350830 (“David”) in view of Bouillet et al. US 20170061786 (“Bouillet”), Green et al. US 20180190111 (“Green”), Mantalvanos US 20130099942 (“Mantalvanos”), Dhondse et al. US 20180089994 (“Dhondse”), and Tourrilhes et al. US 20070222597 (“Tourrilhes”).
For claim 1, David discloses a traffic strategy and management system to generate and implement one or more strategy options to achieve a goal set by the user (See at least [0018] of David – “there is provided a system for advanced traffic management… include a system server including instructions to execute commands to enable traffic decision making algorithms to optimize traffic congestion prevention… and users to be automatically channeled to locations”), said system including orchestration means (See at least [0032] of David – “…system server 101 … adapted to facilitate substantially real time traffic control decision making algorithms…”) connected to:
data source means (See at least [0041] of David – “… traffic sensors may include sensors for a wide range or variety of traffic, vehicle, road and environmental (e.g., weather, light conditions, wetness etc.) conditions, to generate useful traffic related data from the sensors.”),
infrastructure means (See at least [0030] of David – “…Traffic Flow Control system is provided, that may include a smart traffic control network, devices and infrastructure for enabling traffic control and management…”); and
at least one management or control means (See at least [0033] of David – “…the vehicle control device 110…”);
characterised in that said orchestration means is also connected to a strategy generator configured to create at least one traffic management strategy and a set of control instructions relevant to the created traffic management strategy, to achieve the goal set by the user (See at least [0032]-[0033] – “… system server 101 and database 102, adapted to facilitate substantially real time traffic control decision making algorithms, wherein the server includes at least a file with instructions to execute commands to enable execution of the traffic control decisions... the system 100 may transmit output information… in accordance with the traffic control decisions and the driver journey and/or route preference information… route preference information may be … in accordance with user generic preferences… The output information may comprise one or more of … congestion prevention information…” and [0046] of David – “… when a congestion scenario is determined, predicted or happens, drivers of excess vehicles … are alerted, and are automatically diverted to one or more geographically positioned traffic control stations to prevent additional congestion … System 100 may incorporate prediction algorithms, traffic control algorithms and other logistic enhancing algorithms to help identify, verify and/or modify users' traffic behavior”).
David fails to specifically disclose said system including orchestration means connected to:
data source means that includes persistent data collected or known before strategy- generation and real time data.
However, Bouillet, in the same field of endeavor teaches said system including orchestration means connected to:
data source means that includes persistent data collected or known before strategy- generation and real time data (See at least [0044] of Bouillet – “… That is, the training data device 108 stores the real time traffic feed data as historical data for offline evaluation that may be performed by the model calibration device 104… The state identification device 102 and the network transition model device 103 utilize the set of parameters stored in the parameter set device to identify, with better accuracy since data is updated over time, the exact locations of mismatches in supply-demand …”). Thus, David discloses a traffic control system that utilizes sensor information and prediction algorithms to identify congestion scenarios for road traffic, while Bouillet teaches an adaptive signal control system that uses modeled data and real time data that are supplied to strategy generating components of the system to generate parameters that may be used in control actions to better serve a transportation demand.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the traffic strategy and management system as disclosed in David to include the feature of the data source means including persistent data collected or known before strategy-generation and real time data as taught by Bouillet, with a reasonable expectation of success, in order to generate a set of system parameters to increase the efficiency of the supply of the strategy and network as specified in at least [0044] of Bouillet.
Furthermore, David also fails to specifically disclose said system including orchestration means connected to:
infrastructure means that includes traffic signals; and
said orchestration means is also connected to a strategy generator configured to create at least one traffic management strategy and a set of control instructions for all infrastructure means relevant to the created traffic management strategy, to achieve the goal set by the user.
However, Green, in the same field of endeavor teaches said system including orchestration means connected to:
infrastructure means that includes traffic signals (See at least [0077] – “… the remote planning system 222 receives the generated traffic data from local control systems 210a-210d controlling traffic lights at different intersections…” and Fig. 3 of Green – Remote planning system 222 connected to traffic lights 230); and
said orchestration means is also connected to a strategy generator configured to create at least one traffic management strategy and a set of control instructions for all infrastructure means relevant to the created traffic management strategy, to achieve the goal set by the user (See at least [0077] Green – “… The remote planning system 222 uses the traffic data, along with the remote machine learning model 224, to generate a remote control instruction for each of the local control systems 210a-210d. For example, by inputting the received traffic data to a trained model 224, the remote planning system 222 can determine timings and offsets of signal phases to improve efficiency and reduce traffic congestion…”). Thus, David discloses a traffic control system that utilizes sensor information and prediction algorithms to identify congestion scenarios for road traffic, while Green teaches a dynamic traffic control system that uses remote machine learning models to generate control instructions for traffic lights based on conditions detected at many different intersections to reduce traffic congestion.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the traffic strategy and management system as disclosed in David to include the features of the orchestration means being connected to infrastructure means that includes traffic signals and said orchestration means also connected to a strategy generator configured to create at least one traffic management strategy and a set of control instructions for all infrastructure means relevant to the created traffic management strategy, to achieve the goal set by the user as taught by Green, with a reasonable expectation of success, in order to determine timings and offsets of signal phases that improve efficiency and reduce traffic congestion and transmit the instructions to traffic lights as specified in at least [0077] and [0086] of Green.
Moreover, David fails to specifically disclose a strategy generator configured to create at least one traffic management strategy and a set of control instructions for all infrastructure means relevant to the created traffic management strategy, to achieve the goal set by the user, by using:
a computer operating a planning engine that contains traffic simulator software that simulates the operation of a strategy on the initial traffic state using modelled data for the domain model and a simulation of a traffic management strategy on the persistent data, using the process, action, and event elements present in the domain model, and
wherein said goal is written as a logical term the components of which are data source means in the form of processes, actions, or events in the domain model that the generated traffic management strategy options can change.
However, Mantalvanos, in the same field of endeavor teaches a strategy generator configured to create at least one traffic management strategy and a set of control instructions for all infrastructure means relevant to the created traffic management strategy, to achieve the goal set by the user (See at least [0065]-[0071] of Mantalvanos – “… The traffic manager has many tools available within the FITS system to manage traffic and meet local policy objectives such as… FITS can reduce vehicle emissions by reducing delays and congestion within the network, however it can be set to adjust the optimisation of the signal timings to minimise emissions … “), by using:
a computer operating a planning engine that contains traffic simulator software that simulates the operation of a strategy on the initial traffic state using modelled data for the domain model and a simulation of a traffic management strategy on the persistent data, using the process, action, and event elements present in the domain model (See at least [0072]-[0078] – “… The real-time simulation system models the queues, waiting times and stops at intersections, so it can also estimate the time for cars spent in the various travel-modes: cruising, accelerating, decelerating, idling and stop-and-go. This data can be used to estimate emissions and pollution…. The FITS system controls the real-time simulator. The system collects data from each junction and feeds the results into an integrated server. The speed of FITS, twenty simulation updates per second, means it is possible to provide an accurate real time model of what the traffic situation is. In addition, the system can detect more subtle changes in the traffic and over time give a more accurate view of behavioural patterns allowing a city to do more. The real time traffic simulation model can be animated remotely in 2 or 3D modes. FITS reads the states of all available detectors and uses this information to update a real-time traffic simulation model typically some 20 times per second… A simulation system can be set to continuously run scenarios of various situations within the controlled area… FITS can comprise a pollution reader that detects the level of pollution at a given junction and adjust the timing accordingly to reduce pollution levels…” and [0087] of Mantalvanos – “…The system provides a graphical configuration tool with the junction layout. The configuration tool is an integrated user-friendly tool for setting up the FITS traffic signal control… When user presses "save" the program creates all the configuration files needed in the FITS-control. These files will be transferred to the actual controller in the field to be used by the FITS-signal control software…” Examiner notes that updating a real-time traffic simulation model reads on the limitation of simulating the operation of a strategy on the initial traffic state as an initial traffic state is required to continuously run scenarios and update a real-time traffic simulation model. Examiner also notes that “domain model” is broad and could be the conceptual representation of the simulation model such as the junction layout, properties, fuzzy logic, and signal control rules assigned by a user), and
wherein said goal is written as a logical term the components of which are data source means in the form of processes, actions, or events in the domain model that the generated traffic management strategy options can change (See at least [0088] of Mantalvanos – “… In the FITS-system, however, each signal group is aware of the traffic situation of any other signal group. This means they can negotiate with each other about the overall optimal control strategy. The rules for this negotiation are defined by the fuzzy logic, which can be chosen by the user. By fuzzy logic the user describes signal control rules in a way that resembles the natural language. This makes the "programming" of the signal controllers more user-friendly and more traffic engineering oriented than in the present systems. With the fuzzy rules it is possible to implement the chosen traffic control policy for example to prioritize the main street, prioritizing public transport, minimizing emissions instead of delays etc…”). Thus, David discloses a traffic control system that utilizes sensor information and prediction algorithms to identify congestion scenarios for road traffic, while Mantalvanos teaches a traffic signal control system that uses a simulator and collected data to aid in providing dynamic control of a plurality of traffic signals based on selected policies (i.e., goals) chosen by a user.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the traffic strategy and management system as disclosed in David to include the feature of the strategy generator using a computer operating a planning engine that contains traffic simulator software that simulates the operation of a strategy on the initial traffic state using modelled data for the domain model and a simulation of a traffic management strategy on the persistent data, using the process, action, and event elements present in the domain model as taught by Mantalvanos, with a reasonable expectation of success, in order to provide a user control in choosing an optimal control strategy for signal controllers and programming user selected policies (i.e., goals) to implement for traffic control as specified in at least [0088] of Mantalvanos.
Additionally, David fails to specifically disclose wherein the orchestration means continuously compares real time data with the simulation of the traffic management strategy to create control instructions including a signal plan of split timings for signal changes in real time and/or near real time for the infrastructure means.
However, Dhondse, in the same field of endeavor teaches wherein the orchestration means continuously compares real time data with the simulation of the traffic management strategy to create control instructions including a signal plan of split timings for signal changes in real time and/or near real time for the infrastructure means (See at least [0038]-[0041] of Dhondse – “… Traffic density analyzer 314 comprises a computer processor that processes traffic data first collected by sensors 100 for generating data representative of traffic density on a given roadway 14 and lane 12 at a given instant in time so such data can then be used in further processing by the predictive traffic flow modeler 312 … Public transfer system 400 comprises a lane controller 402 (e.g., an automatically controlled gate) and traffic lights controller 404… Based on the real time traffic lane data and the predictive traffic flow data, public transfer system 400 can send signals … In addition, the data provided to public transfer system 400 can be provided to traffic light controller 404 for purposes of providing signals to physical traffic lights to change their pre-programmed patterns and permit more optimal patterns to accommodate the real time actual traffic patterns on roadway 12…”). Thus, David discloses a traffic control system that utilizes sensor information and prediction algorithms to identify congestion scenarios for road traffic, while Dhondse teaches a predictive traffic management system that compares real time traffic data on a road with results from a predictive traffic flow modeler to provide signals for traffic lights to change their patterns and permit more optimal patterns.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the traffic strategy and management system as disclosed in David to include the feature of the orchestration means continuously comparing real time data with the simulation of the traffic management strategy to create control instructions including a signal plan of split timings for signal changes in real time and/or near real time for the infrastructure means as taught by Dhondse, with a reasonable expectation of success, in order to provide signals to physical traffic lights to change their patterns and permit more optimal patterns to accommodate the real time actual traffic conditions as specified in at least [0041] of Dhondse.
Lastly, David fails to specifically disclose wherein the system includes one or more input data adaptors to process information from multiple data source means into the correct form of processes, actions, or events in the domain model for use by the strategy generator.
However, Tourrilhes, in the same field of endeavor teaches wherein the system includes one or more input data adaptors to process information from multiple data source means into the correct form of processes, actions, or events in the domain model for use by the strategy generator (See at least [0038] of Tourrilhes – “forwarders 120a-m may collect information from …sensor controllers … dispatch the information to one or more of the back-end applications 120a-f via adaptors 130a-f corresponding to the back-end applications 120a-f. Each of the back-end applications 140a-f may use its own data format and procedures. The adaptors 130a-f convert messages from the forwarders 120a-m to a format compatible with a corresponding back-end application…”). Thus, David discloses a traffic control system that utilizes sensor information and prediction algorithms to identify congestion scenarios for road traffic, while Tourrilhes teaches an asset tracking system that uses adaptors to convert collected sensor information into a compatible form for use by an application.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the traffic strategy and management system as disclosed in David to include the feature of the system including one or more input data adaptors to process information from multiple data source means into the correct form of processes, actions, or events in the domain model for use by the strategy generator as taught by Tourrilhes, with a reasonable expectation of success, in order for collected data to be compatible with network software or visualization tools making use of the data as specified in at least [0038] of Tourrilhes.
For claim 2, David discloses characterized in that the traffic is road based traffic (See at least [0028] of David – “…the term "traffic congestion" as used herein refers to … road works generated traffic problems…”).
For claim 3, David discloses characterized in that the data source means include any one or any combination of traffic management and control systems, data aggregation hubs, databases, smart city data sources and sensors of any kind, including connected vehicles and sensors thereof (See at least [0041] of David – “….traffic sensors may include sensors for a wide range or variety of traffic, vehicle, road and environmental (e.g., weather, light conditions, wetness etc.) conditions, to generate useful traffic related data from the sensors.”).
For claim 7, David discloses characterized in that the system includes one or more output data adaptors, said output adaptors processing control instructions from the strategy generator (See at least [0018] of David – “… a communications network adapted to facilitate substantially real time communication between multiple traffic system components… include a system server including instructions to execute commands to enable user driven requests to be processed, and users to be automatically channeled to locations”) into a format for use and/or execution by the infrastructure means (See at least [0033] – “the system 100 may transmit output information to the vehicle control device 110 …. The output information may comprise one or more of congestion warning information … acceptable detours… directions to exit to a station…” and [0040] of David – “devices 110 may be equipped with text to speech engines to enable speaking of commands, instructions and updates to drivers, in place or in addition to textual based data”).
For claim 9, David discloses characterized in that the infrastructure means includes real-time traffic control products (See at least [0051] of David – “… vehicle positions of system users may be monitored, as may be roads, environmental factors etc… to generate substantially real time decisions relating to action to be taken by system users to enhance traffic flow and/or prevent traffic congestion”).
For claim 11, David discloses characterized in that the system includes one or more process control adaptors situated to control instruction and/or data flow into and/or out of the orchestration means (See at least [0006] of David – “… a system server and database, adapted to receive traffic information from the traffic related sensors … wherein said server includes a file with instructions to execute commands to enable execution of said traffic control decisions, the system being operable to receive input information from vehicle control devices and transmit output information to the vehicle control devices in accordance with the traffic control decisions”).
For claim 18, David discloses characterized in that the orchestration means orchestrates the set of control instructions produced by the strategy generator across the components of the system (See at least [0051] of David – “… a communication network is set up to connect the respective stations, vehicle devices, sensors, and communications networks, to operate in communication with a central, cloud based and/or distributed server(s) system and system database(s)… decision making processes or queries may be run for all elements in the system, including vehicles, roads, stations, sensors etc., to generate substantially real time decisions relating to action to be taken by system users to enhance traffic flow and/or prevent traffic congestion… drivers of vehicles being monitored by the system may be diverted, aided, provided with a variety of services etc., to enable optimal traffic congestion control and management…”).
For claim 19, David discloses characterized in that the orchestration includes collection, coordination, and/or sending instructions from the strategy generator to at least the infrastructure means (See at least [0051] of David – “… a communication network is set up to connect the respective stations, vehicle devices, sensors, and communications networks, to operate in communication with a central, cloud based and/or distributed server(s) system and system database(s)… decision making processes or queries may be run for all elements in the system, including vehicles, roads, stations, sensors etc., to generate substantially real time decisions relating to action to be taken by system users to enhance traffic flow and/or prevent traffic congestion… drivers of vehicles being monitored by the system may be diverted, aided, provided with a variety of services etc., to enable optimal traffic congestion control and management…”).
For claim 20, David discloses characterized in that the orchestration is in real-time (See at least Abstract of David – “a system server and database, adapted to receive traffic information from the traffic related sensors and facilitate substantially real time traffic control decision making algorithms...”).
For claim 24, David discloses characterized in that the orchestration means converts signal instructions into a collection of signal plans (See at least [0038] of David – “… the system may suggest to the user to drive towards a nearby rest station or alternative route”).
For claim 25, David discloses characterized in that the orchestration means converts signal instructions into a collection of complete signal plans (See at least [0038] of David – “… the system may suggest to the user to drive towards a nearby rest station or alternative route. In some examples the system may inform the driver of the time and/or distance to travel to a rest station, the expected time delay at the station, what may be done at the station, expected time of arrival with or without diverting to the station, benefits for diverting to the station etc. In still further examples, the user may be informed of other benefits, such as amount of fuel, energy or gas to be saved, amount of pollution to be saved, costs of ware/usage of the vehicle, time saved, bonus points or other incentives for cooperation”), which it can load, execute and unload from single or multiple traffic controllers using a traffic control computer (See at least [0018] of David – “…said communications network may include a system server including instructions to execute commands to enable user driven requests to be processed, and users to be automatically channeled to locations”).
For claim 32, David fails to specifically disclose characterized in that the strategy generator inputs include an initial state at some time (T), a goal, a domain model, and a time delay (E) and the strategy generator outputs a traffic signal strategy that if said strategy is executed at time T+E to the initial state to achieve the goal.
However, Bouillet, in the same field of endeavor teaches characterized in that the strategy generator inputs include an initial state at some time (See at least [0032] of Bouillet – “ The traffic state identification device 102 receives the real time traffic feed data from the real time traffic feed data device 105 and identifies a traffic state classification for each sensor of the sensors 112…”), a goal (See at least [0037] of Bouillet – “If the traffic state identification device 102 identifies a sensor as having the green state classification, then that particular sensor is deemed to be working at the optimal service rate”), a domain model, and a time delay (See at least [0044] of Bouillet – “Based on the historical real time traffic feed data stored in the training data device 108 and the infrastructure data of the infrastructure data device 109, the model calibration device 104 generates a set of parameters for the system to increase the efficiency of the supply of the control signal strategy and network…The set of parameters are updated at predetermined times.) and the strategy generator outputs a traffic signal strategy that if said strategy is executed at time T+E to the initial state to achieve the goal (See at least [0047] of Bouillet – “…the model calibration device 104 uses the parameter of probabilities of supply-demand mismatches to train the control strategy and signal control actions for the signalized transportation network to be better rationed to serve the demand”). Thus, David discloses a traffic control system that utilizes sensor information and prediction algorithms to identify congestion scenarios for road traffic, while Bouillet teaches an adaptive signal control system that uses modeled data and real time data that are supplied to strategy generating components of the system to generate parameters that may be used in control actions to better serve a transportation network by identifying initial states of sensors and using a model to implement a strategy at a later time to meet the demands of the system.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the traffic strategy and management system as disclosed in David to include the feature of the strategy generator using an initial state, a goal, a domain model, and a time delay to outputs a traffic signal strategy at a later time to the initial state to achieve the goal as taught by Bouillet, with a reasonable expectation of success, in order to generate a set of system parameters to increase the efficiency of the supply of the strategy and network as specified in [0044] of Bouillet and to train control actions for implementation on the transportation network to be better rationed to serve a demand as discussed [0047] of Bouillet.
For claim 33, David fails to specifically disclose characterized in that an initial state is the set of all the data / knowledge about the traffic scenario within a spatial target region of an area under consideration.
However, Bouillet, in the same field of endeavor teaches characterized in that an initial state is the set of all the data / knowledge about the traffic scenario within a spatial target region of an area under consideration (See at least [0032] of Bouillet – “the traffic state identification device 102 receives the real time traffic feed data from the real time traffic feed data device 105 and identifies a traffic state classification for each sensor of the sensors 112. The traffic state identification device 102 diagnoses a relationship between the real time traffic feed data and a control strategy of the network as a traffic state classification”). Thus, David discloses a traffic control system that utilizes sensor information and prediction algorithms to identify congestion scenarios for road traffic, while Bouillet teaches an adaptive signal control system that uses modeled data and real time data that are supplied to strategy generating components of the system to generate parameters that may be used in control actions to better serve a transportation network.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the traffic strategy and management system as disclosed in David to include the feature of the initial state being the set of all the data / knowledge about the traffic scenario within a spatial target region of an area under consideration as taught by Bouillet, with a reasonable expectation of success, in order for the system to diagnose a relationship between the real time traffic feed data and a control strategy of the network as a traffic state classification as discussed [0032] of Bouillet.
For claim 34, David fails to specifically disclose characterized in that only certain or predetermined initial states are allowed, said initial states comprising at least two types of information, persistent data and real time data wherein persistent data is collected or known before strategy generation and real-time data is data from the target region that is collected instantaneously, in real time or near real time.
However, Bouillet, in the same field of endeavor teaches characterized in that only certain or predetermined initial states are allowed, said initial states comprising at least two types of information, persistent data and real time data wherein persistent data is collected or known before strategy generation and real-time data is data from the target region that is collected instantaneously, in real time or near real time (See at least [0044] of Bouillet – “… That is, the training data device 108 stores the real time traffic feed data as historical data for offline evaluation that may be performed by the model calibration device 104… The state identification device 102 and the network transition model device 103 utilize the set of parameters stored in the parameter set device to identify, with better accuracy since data is updated over time, the exact locations of mismatches in supply-demand …”). Thus, David discloses a traffic control system that utilizes sensor information and prediction algorithms to identify congestion scenarios for road traffic, while Bouillet teaches an adaptive signal control system that uses modeled data and real time data that are supplied to strategy generating components of the system to generate parameters that may be used in control actions to better serve a transportation.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the traffic strategy and management system as disclosed in David to include the feature of utilizing initial states comprising persistent data and real time data as taught by Bouillet, with a reasonable expectation of success, in order to generate a set of system parameters to increase the efficiency of the supply of the strategy and network as specified in [0044] of Bouillet.
Claim 43 is rejected under 35 U.S.C. 103 as being unpatentable over David in view of Bouillet, Green, Mantalvanos, Dhondse, and Tourrilhes, as applied to claim 1 above, and further in view of Chang et al. US 20130297769 (“Chang”).
For claim 43, David fails to specifically disclose characterized in that the strategy generator works in two phases, a pre- processing phase and a heuristic phase.
However, Chang, in the same field of endeavor teaches characterized in that the strategy generator works in two phases, a pre- processing phase and a heuristic phase (See at least [0069] of Chang – “… The activities performed by simulator 36 may be prompted by user instructions on user interface 63, or according to pre-determined logic, heuristics, and other suitable methods”). Thus, David discloses a traffic control system that utilizes sensor information and a system server that generates instructions for vehicles to avoid traffic congestion, while Chang teaches a simulation network that uses pre-processing logic and heuristics to test a service policy effectiveness.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the traffic strategy and management system as disclosed in David to include the feature of a strategy generator working in two phases, a pre- processing phase and a heuristic phase as taught by Chang, with a reasonable expectation of success, in order to test if desired enforcement actions are being triggered according to a policy as described in [0069] of Chang.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/M.J.H./Examiner, Art Unit 3668
/Fadey S. Jabr/Supervisory Patent Examiner, Art Unit 3668