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 .
This office action is in response to the amendments filed on 01/28/2026, in which claims 1-20 are pending and addressed below.
Response to Arguments
Applicant has appeared to submit arguments identical to the arguments filed on 09/10/2025. Applicant’s arguments have been rebutted in the non-final rejection dated 11/10/2025 and as appears below.
Applicant’s arguments with respect to claims 1-20 have been considered but are moot because the rejection does not rely on any reference applied in the rejection of record for any teaching or matter specifically challenged in the argument.
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Merwaday et al., U.S. Patent Application Publication No. 2021/0264794 A1 (hereinafter Merwaday), in view of Wang et al., U.S. Patent Application Publication No. 2022/0089164 A1 (hereinafter Wang), and further in view of Thompson et al., U.S. Patent Application Publication No. 2022/0242401 A1 (hereinafter Thompson).
Regarding claim 1, Merwaday discloses a method of controlling one or more vehicles of a platoon of vehicles (Merwaday Fig. 9), the method comprising:
determining a joint optimization of operating parameters of a first vehicle of the platoon and a second vehicle of the platoon (see at least Merwaday [0109]: “The optimization algorithm may be executed to determine any suitable number and/or type of optimization goal based upon the SDM parameters of all current platoon CAVs as well as the SDM parameters of one or more new vehicles requesting to join the platoon.”),
the second vehicle being positioned one of forward of and rearward of the first vehicle (see at least Merwaday [0058]: “As shown in FIG. 3, a vehicle platoon 300 includes any suitable number of vehicles 302, with four being shown, although the vehicle platoon 300 may include any suitable number of vehicles.”; Fig. 3 shows the second vehicle can be positioned forward or rearward of a first vehicle),
the operating parameters of the first vehicle including vehicle motion plan parameters for the first vehicle (see at least Merwaday [0054]: “generate a safety driving model (SDM) for the first vehicle to perform control functions using first vehicle SDM parameters comprising at least a defined safe longitudinal distance between the first vehicle and a second vehicle in a vehicle platoon of the first vehicle”),
the operating parameters of the second vehicle including suggested control actions for the second vehicle (see at least Merwaday [0053]: “Still further, and in addition or in alternative to and in any combination with the optional features previously explained in this paragraph, the platoon messages may comprise second vehicle SDM parameters that are generated and used by the second vehicle to perform control functions”);
wirelessly transmitting from the first vehicle the vehicle motion plan parameters for the first vehicle and the suggested control actions for the second vehicle (see at least Merwaday [0054]: “Still further, and in and in addition or in alternative to and in any combination with the optional features previously explained in this paragraph, the controller may include a communication interface configured to transmit one or more first platoon messages containing at least a portion of the first vehicle SDM parameters to the second vehicle to cause the second vehicle to transmit one or more second platoon messages to the first vehicle containing instructions of an organizational change to the vehicle platoon. In addition or in alternative to and in any combination with the optional features previously explained in this paragraph, the communication interface may be configured to receive one or more platoon messages transmitted by the second vehicle including at least a portion of second vehicle SDM parameters generated and used by the second vehicle to perform control functions, and the CACC controller may be configured to update the SDM for the first vehicle using the portion of the second vehicle SDM parameters.”);
wirelessly receiving at the first vehicle following vehicle capability parameters indicating capability of the second vehicle (see at least Merwaday [0045]: “Using the data received via the data interface 232, the one or more processors 102 may determine any suitable type of vehicle status information (vehicle data) such as the current drive gear, current engine speed, acceleration capabilities of the vehicle 100, etc. The one or more processors 102 (functioning as a CACC controller) may utilize the data received via the vehicle components 232, which may include kinematic parameters, to calculate a dynamic kinematics model associated with movement of the vehicle 100 in accordance with a set of kinematic parameters including engine power, engine speed, engine efficiency, a differential gear ratio, a diameter of tractive wheels, vehicle mass, etc.”; [0107]: “The SDM status data may then be received and decoded by one or more recipient vehicles 302 (such as via a recipient vehicle 302's one or more of the transceivers 208, 210, 212). In accordance with the present disclosure, one or more follower vehicles (such as the vehicles 302.2-302.4) may also transmit their SDM status data to the leader vehicle (such as the vehicle 302.4) in the vehicle platoon using such control messages.”; under broadest reasonable interpretation vehicle capability parameters includes vehicle status information or vehicle data);
receiving at the first vehicle look-ahead parameters indicating at least one of road conditions and environmental conditions over a look-ahead horizon (see at least Merwaday [0117]-[0118]: “To avoid any adverse effects of such major occlusions on the SDM model or the automated driving systems (ADS) of platoon CAVs, the platoon leader (such as vehicle 302.1) and the last follower CAV (such as vehicle 302.4) may multicast relevant information about the surrounding environment in both the forward (i.e. towards the front of the vehicle platoon 300 or towards vehicle 302.1) and rear directions (i.e. towards the rear of the vehicle platoon 300 or towards the vehicle 302.4)…Both the leader vehicle 302.1 and the rear-most following vehicle 302.4 may each respectively transmit platoon messages that may include any suitable type of information regarding the environment of the vehicle platoon 300. This may include one or more SDM parameters for each vehicle 302.1, 302.4 (ego SDM parameters) or other SDM parameters associated with other vehicles 302 in the vehicle platoon 300 (neighboring SDM parameters), as well as any other suitable type of data with respect to the environment in which the vehicle platoon is traveling. Parameters of the environment that may be detected in this context include perception information such as bounding boxes of nearby objects, video stream from a camera, etc. The platoon message transmitted by the vehicle 302.4 may then be received by the leader vehicle 302.1 (and optionally any other vehicles 302 within the vehicle platoon 300), and vice-versa.”; under broadest reasonable interpretation look-ahead parameters over a look-ahead horizon include parameters of the environment in front of the vehicle);
determining in response to the following vehicle capability parameters and the look ahead parameters an updated joint optimization including updated vehicle motion plan parameters for the first vehicle (see at least Merwaday [0109]: “The optimization algorithm may be executed to determine any suitable number and/or type of optimization goal based upon the SDM parameters of all current platoon CAVs as well as the SDM parameters of one or more new vehicles requesting to join the platoon. Additional optimization goals may include a maximization of overall platoon efficiency with respect to various parameters (such as fuel efficiency), a minimization of other parameters such as wind resistance, etc.”; [0102]: “Thus, each vehicle 302 within the vehicle platoon 300 may dynamically and/or continuously update its own SDM and accompanying SDM parameters based upon changes to the environment, which includes changes to the vehicle's speed and/or drive gear…A platoon vehicle 302.2 may utilize its CACC controller to calculate changes to its maximum acceleration value, update its SDM while travelling within the vehicle platoon 300, and update the calculation of the safe longitudinal distance between itself and the leader vehicle (such as vehicle 302.1) using the updated SDM (such as the updated SDM parameters).”; [0118]: “Both the leader vehicle 302.1 and the rear-most following vehicle 302.4 may each respectively transmit platoon messages that may include any suitable type of information regarding the environment of the vehicle platoon 300. This may include one or more SDM parameters for each vehicle 302.1, 302.4 (ego SDM parameters) or other SDM parameters associated with other vehicles 302 in the vehicle platoon 300 (neighboring SDM parameters), as well as any other suitable type of data with respect to the environment in which the vehicle platoon is traveling.”; Merwaday [0133] discloses using vehicle data to calculate the safe longitudinal distance using the SDM model parameters; under broadest reasonable interpretation vehicle capability parameters includes vehicle data; under broadest reasonable interpretation the look ahead parameters include SDM parameters of the environment in front of the vehicle;),
and controlling motion of the first vehicle in response to the updated vehicle motion plan parameters (see at least Merwaday [0086]: “A platoon vehicle 302.2 may utilize its CACC controller to update its SDM while travelling within the vehicle platoon 300, and update the calculation of the safe longitudinal distance between itself and the leader vehicle (such as vehicle 302.1) using the updated SDM (such as the updated SDM parameters).”; [0043]: “The one or more processors 102 may form a CACC controller that is configured to perform the CACC-based tasks as discussed further herein, such as the calculation and execution of minimum safe longitudinal distances for vehicles travelling within a platoon for instance.”).
Merwaday fails to expressly disclose minimizing a first cost function for the first vehicle and a second cost function for the second vehicle. However, Wang teaches
the updated joint optimization minimizing a first cost function for the first vehicle and a second cost function for the second vehicle accounting for the at least one of the road condition and the environmental condition (see at least Wang [0077]: “In this case, the P1 can collaborate with P2 to determine merge position assignments according to a sum cost based on the cost function associated with P1 and a second cost function associated with P2.”; [0046]: “As indicated in Table 1, to avoid a collision the ego vehicle 100 and the competitor vehicle 105 are not allowed to be leader or follower at the same time, thus the cost for these two cases are set to infinity or a very large number. At each timestep, the ego vehicle 100 will choose the option with the minimum expected cost, as described in Equation 9.”; [0042]-[0043]: “Accordingly, in one or more embodiments the vehicle merge control system 170 can define a cost function of a mainline vehicle (e.g., vehicle 105) as: Cost.sup.ML(v.sub.e,v.sub.c,a,Δt)=risk.sub.n.sup.ML+Mobility.sup.ML Eq. 7 Correspondingly, the vehicle merge control system 170 can define a cost function of a merge lane vehicle (e.g., vehicle 100) as…Eq. 8”; [0039]: “To consider the merging urgency of merge lane vehicles, the vehicle merge control system 170 can include a distance to the end of merge area 330 in the risk value of the merge lane vehicle, as shown in Equation 5. The closer the players are to the end of the merge area 330, the higher the cost the merge lane vehicle should estimate”; Wang teaches accounting for at least one of road condition and environmental condition for the look-ahead horizon because the cost function accounts for a distance of a merge area ahead of a vehicle).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the method disclosed by Merwaday with the cost functions taught by Wang with reasonable expectation of success. Wang is directed towards the related field of determining safe positions and accelerations for a vehicle merge maneuver. Therefore, one of ordinary skill in the art would be motivated to modify the method disclosed by Merwaday with the cost functions taught by Wang to improve safety and efficiency of a merging process (see at least Wang [0014]: “The disclosed strategy improves safety and efficiency of a merging process in multiple ways, for example, by ensuring a safe inter-vehicle distance among the involved vehicles and harmonizing the speed of CAVs in the traffic stream.”).
Merwaday in view of Wang fail to expressly disclose the look ahead horizon for the at least one of road conditions and environmental conditions including at least one of a plurality of positions, plurality of times, and a plurality of position and time pairs. However, Thompson teaches
the look ahead horizon including at least one of a plurality of positions, a plurality of times, and a plurality of position and time pairs (see at least Thompson [0170]-[0171]: “For the kth step in the prediction horizon, the variable timestep may be defined as follows…where T is the length of the time horizon (in steps) and tcorr is a correction time step at horizon step Tcorr that aligns the physical representation of the environment in a consistent manner from cycle to cycle (i.e. so the values of s at the long time steps are preserved in subsequent horizons and static obstacles don't look like they're moving).”);
accounting for the at least one of the road condition and the environmental condition for the at least one of the plurality of positions, the plurality of times, and the plurality of position and time pairs of the look-ahead horizon (see at least Thompson [0151]: “Environmental sensors or external data can be used to determine weather conditions for the current vehicle location. This information can be used to determine envelope conditions the vehicle is encountering or is about to encounter in a given time step of interest. For example, a subject vehicle will have certain limits negotiating a curve of a given radius on a paved roadway. In other words, there is a maximum speed beyond which the vehicle will not be able to safely negotiate the corner given expected vehicle performance specifications. That maximum safe speed is typically decreased for lower-friction road conditions such as gravel or dirt roads, wet roads, icy roads, or other environmental factors. Similarly, the tighter the radius of the corner, the lower the maximum safe speed. Accordingly, this may increase the level of risk predicted by the system.”; [0081]: “The future vehicle state may include what a driver of the vehicle is likely to do, a position on the roadway likely to be travelled towards, obstacles on the roadway and their movements, prior vehicle states determined, etc. Determination may occur at different levels of granularity, and may occur at varying time horizons. In some implementations, more than one future vehicle state may be determined at varying time horizons.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the method disclosed by Merwaday in view of Wang with the look-ahead horizon taught by Thompson with reasonable expectation of success. Thompson is directed towards the related field of optimizing parameters for a model predictive controller for vehicle navigation. Therefore, one of ordinary skill in the art would be motivated to modify the method disclosed by Merwaday in view of Wang with Thompson to improve current technology by accounting for changing parameters (see at least Thompson [0005]: “Embodiments of the systems and methods disclosed herein may be implemented to improve upon current technology by utilizing learned operational parameters (which include but are not limited to at least one of vehicle, external, and controls parameters), as opposed to fixed parameters that do not change. By utilizing learned vehicle parameters to consider changes to the vehicle (such as more or fewer passengers, wear and tear on the tires, new tires, etc.) the model predictive controller (MPC) can operate more effectively.”).
Regarding claim 2, Merwaday in view of Wang and Thompson teach all elements of the method according to claim 1 as explained above. Wang further teaches wherein the determining the updated joint optimization comprises:
operating a model predictive controller to jointly minimize the first cost function for the first vehicle and the second cost function for the second vehicle subject to a first set of permissible commands or states for the first vehicle and second set of permissible commands or states for the second vehicle (see at least Wang [0077]: “In this case, the P1 can collaborate with P2 to determine merge position assignments according to a sum cost based on the cost function associated with P1 and a second cost function associated with P2.”; [0046]: “As indicated in Table 1, to avoid a collision the ego vehicle 100 and the competitor vehicle 105 are not allowed to be leader or follower at the same time, thus the cost for these two cases are set to infinity or a very large number. At each timestep, the ego vehicle 100 will choose the option with the minimum expected cost, as described in Equation 9.”; [0042]-[0043]: “Accordingly, in one or more embodiments the vehicle merge control system 170 can define a cost function of a mainline vehicle (e.g., vehicle 105) as: Cost.sup.ML(v.sub.e,v.sub.c,a,Δt)=risk.sub.n.sup.ML+Mobility.sup.ML Eq. 7 Correspondingly, the vehicle merge control system 170 can define a cost function of a merge lane vehicle (e.g., vehicle 100) as…Eq. 8”).
Regarding claim 3, Merwaday in combination with Wang and Thompson teach all elements of the method according to claim 2 as explained above. Wang further teaches
wherein one or both of the first cost function for the first vehicle and the second cost function for the second vehicle includes one or more of a vehicle velocity term, a vehicle position term, an inter-vehicle separation distance objective term, and a slack term effective to allow for variation in the inter-vehicle separation distance objective term (see at least Wang [0038]: “where h.sub.predict, v.sub.e, and v.sub.c are the predicted time headway of ego vehicle 100, speed of ego vehicle 100, and speed of competitor vehicle 105, respectively,”; Wang teaches at least a vehicle velocity term; examiner notes cost function Eq. 7 and cost function Eq. 8 contain the risk term defined in Eq. 3 and Eq. 4).
Regarding claim 4, Merwaday in combination with Wang and Thompson teach all elements of the method according to claim 2 as explained above. Wang further teaches wherein one or both of the first cost function for the first vehicle and the second cost function for the second vehicle includes
a vehicle velocity term (see at least Wang [0038]: “where h.sub.predict, v.sub.e, and v.sub.c are the predicted time headway of ego vehicle 100, speed of ego vehicle 100, and speed of competitor vehicle 105, respectively,”; examiner notes cost function Eq. 7 and cost function Eq. 8 contain the risk term defined in Eq. 3 and Eq. 4),
a vehicle position term (see at least Wang [0047]: “The cost of being a follower for the ego vehicle 100 (Cost.sub.follow.sup.ego) is chosen from either Cost.sub.follow.sup.Ramp or Cost.sub.follow.sup.ML based on its position on the road, and likewise for the cost of the competitor vehicle 105 (Cost.sub.lead.sup.com).”),
an inter-vehicle separation distance objective term (see at least Wang [0035]: “In one or more embodiments, the predicted TTC for any pair of players (i.e., a preceding vehicle and following vehicle) can be formulated as Equation 1…where Gap is the size of the gap between the preceding vehicle and following vehicle”; examiner notes Eq. 3 contains TTC defined in Eq. 1; examiner further notes cost function Eq. 7 and cost function Eq. 8 contain the risk term defined in Eq. 3),
and a slack term effective to allow for variation in the inter-vehicle separation distance objective term (see at least Wang [0035]: “In one or more embodiments, the predicted TTC for any pair of players (i.e., a preceding vehicle and following vehicle) can be formulated as Equation 1…where Gap is the size of the gap between the preceding vehicle and following vehicle”; under broadest reasonable interpretation a slack term includes delta gap which allows for variation in the intervehicle gap; examiner notes Eq. 3 contains TTC defined in Eq. 1; examiner further notes cost function Eq. 7 and cost function Eq. 8 contain the risk term defined in Eq. 3).
Regarding claim 5, Merwaday in view of Wang and Thompson teach all elements of the method according to claim 1 as explained above. Merwaday further teaches
wherein the determining a joint optimization of operating parameters of a first vehicle of the platoon and a second vehicle of the platoon is subject to vehicle capability parameters of the second vehicle (see at least Merwaday [0093]: “For instance, in Equation 2 described above, the maximum acceleration a.sub.max,accel of a following vehicle (such as one of the following vehicles 302.2-302.4) represents the maximum acceleration as a variable quantity, which depends on the characteristics of the vehicle subsystems such as engine power, torque, gear ratio, mass, etc., and also on environmental characteristics such as air resistance, gravitational force, and other frictional forces. The disclosure as described herein implements a realistic modeling of the vehicle kinematics to determine the safe longitudinal distance between the platoon vehicles by calculating the maximum acceleration in Equation 2 above to determine the safe longitudinal distance between two vehicles travelling in the same direction, and then utilizing this value as the desired inter-vehicle spacing by the CACC controller system as represented in Equation 1 above.”; under broadest reasonable interpretation joint optimization of operating parameters includes determining a safe longitudinal distance between vehicles).
Regarding claim 6, Merwaday in view of Wang and Thompson teach all elements of the method according to claim 1 as explained above. Merwaday further teaches
wherein the determining a joint optimization of operating parameters of a first vehicle of the platoon and a second vehicle of the platoon is subject to motion plan parameters of a third vehicle (see at least Merwaday [0109]: “A platoon leader vehicle may perform SDM-aware organization of the follower CAVs by using their shared SDM parameters. Thus, when an external CAV (i.e. a vehicle not currently part of the vehicle platoon) transmits a platoon join request message to the platoon leader by including its SDM status data, the platoon leader may execute (via the one or more processors 102 executing computer-readable instructions stored in the memory 202) an optimization algorithm by considering the SDM parameters of all current platoon CAVs as well as the SDM parameters of one or more new vehicles requesting to join the platoon.”),
the third vehicle being positioned the other of forward of and rearward of the first vehicle (see at least Merwaday [0058]: “As shown in FIG. 3, a vehicle platoon 300 includes any suitable number of vehicles 302, with four being shown, although the vehicle platoon 300 may include any suitable number of vehicles.”; Fig. 3 shows the third vehicle can be positioned forward or rearward of a first vehicle).
Regarding claim 7, Merwaday in view of Wang and Thompson teach all elements of the method according to claim 1 as explained above. Merwaday further teaches
wherein the first vehicle is positioned one of immediately forward of and immediately rearward of the second vehicle (see at least Merwaday [0060]: “The disclosure as described herein implements a CACC controller which exploits the information received by the leader or frontmost vehicle 302.1 as well as each vehicle's immediate front (predecessor) vehicle 302 as illustrated in FIG. 3, which may be contained in the periodically-transmitted platoon messages.”; Fig. 3 shows the first vehicle can be positioned immediately forward or rearward of the second vehicle).
Regarding claim 8, Merwaday in view of Wang and Thompson teach all elements of the method according to claim 1 as explained above. Merwaday further teaches
wherein the following vehicle capability parameters include any one or more of: a current gear of a following vehicle, a current distance between a forward vehicle and the following vehicle, a current velocity of the following vehicle, a current traction of the following vehicle, engine power limitation of the following vehicle, and engine torque limitations of the following vehicle (see at least Merwaday [0045]: “Using the data received via the data interface 232, the one or more processors 102 may determine any suitable type of vehicle status information (vehicle data) such as the current drive gear, current engine speed, acceleration capabilities of the vehicle 100, etc.”; Merwaday discloses at least a current gear of a following vehicle).
Regarding claim 9, Merwaday in view of Wang and Thompson teach all elements of the method according to claim 1 as explained above. Merwaday further teaches wherein the following vehicle capability parameters include:
a current gear of a following vehicle (see at least Merwaday [0045]: “Using the data received via the data interface 232, the one or more processors 102 may determine any suitable type of vehicle status information (vehicle data) such as the current drive gear, current engine speed, acceleration capabilities of the vehicle 100, etc.”),
a current distance between a forward vehicle and the following vehicle (see at least Merwaday [0136]: “a Cooperative Adaptive Cruise Control (CACC) controller configured to…cause the first vehicle to use the determined safe longitudinal distance as an inter-vehicle distance between the first vehicle and the second vehicle in the vehicle platoon.”),
a current velocity of the following vehicle (see at least Merwaday [0092]: “This static value represents a vehicle's capability of maximum acceleration under ideal conditions or otherwise without consideration to other dynamic factors such as the vehicle's current speed and/or drive gear, both of which may influence the vehicle's actual maximum acceleration at a particular time.”),
engine power limitation of the following vehicle (see at least Merwaday [0045]: “The one or more processors 102 (functioning as a CACC controller) may utilize the data received via the vehicle components 232, which may include kinematic parameters, to calculate a dynamic kinematics model associated with movement of the vehicle 100 in accordance with a set of kinematic parameters including engine power”),
and engine torque limitations of the following vehicle (see at least Merwaday [0093]: “For instance, in Equation 2 described above, the maximum acceleration a.sub.max,accel of a following vehicle (such as one of the following vehicles 302.2-302.4) represents the maximum acceleration as a variable quantity, which depends on the characteristics of the vehicle subsystems such as engine power, torque, gear ratio, mass, etc.”).
Thompson further teaches
a current traction of the following vehicle (see at least Thompson [0150]: “Vehicle information can include, for example, information from vehicle sensors indicating vehicle operating parameters such as acceleration, speed, lateral acceleration, wheel traction, vehicle roll/pitch/yaw, and so on.”).
Regarding claim 10, Merwaday in view of Wang and Thompson teach all elements of the method according to claim 1 as explained above. Merwaday further teaches,
wherein the updated joint optimization further includes suggested control actions for the second vehicle (see at least Merwaday [0102]: “Thus, each vehicle 302 within the vehicle platoon 300 may dynamically and/or continuously update its own SDM and accompanying SDM parameters based upon changes to the environment, which includes changes to the vehicle's speed and/or drive gear…A platoon vehicle 302.2 may utilize its CACC controller to calculate changes to its maximum acceleration value, update its SDM while travelling within the vehicle platoon 300, and update the calculation of the safe longitudinal distance between itself and the leader vehicle (such as vehicle 302.1) using the updated SDM (such as the updated SDM parameters).”).
Regarding claim 11, this claim recites a system that performs the method of claim 1. Merwaday in view of Wang and Thompson also teach a system for performing the method of claim 1 as outlined in the rejection to claim 1 above. Specifically, Merwaday discloses the presence of processors configured to execute instructions stored in non-transitory media (Merwaday [0046]). Therefore, claim 11 is rejected for the same rationale as claim 1.
Regarding claim 12, this claim recites a system that performs the method of claim 2 as explained above. Therefore, claim 12 is rejected for the same rationale as claim 2.
Regarding claim 13, this claim recites a system that performs the method of claim 3 as explained above. Therefore, claim 13 is rejected for the same rationale as claim 3.
Regarding claim 14, this claim recites a system that performs the method of claim 4 as explained above. Therefore, claim 14 is rejected for the same rationale as claim 4.
Regarding claim 15, this claim recites a system that performs the method of claim 5 as explained above. Therefore, claim 15 is rejected for the same rationale as claim 5.
Regarding claim 16, this claim recites a system that performs the method of claim 6 as explained above. Therefore, claim 16 is rejected for the same rationale as claim 6.
Regarding claim 17, this claim recites a system that performs the method of claim 7 as explained above. Therefore, claim 17 is rejected for the same rationale as claim 7.
Regarding claim 18, this claim recites a system that performs the method of claim 8 as explained above. Therefore, claim 18 is rejected for the same rationale as claim 8.
Regarding claim 19, this claim recites a system that performs the method of claim 9 as explained above. Therefore, claim 19 is rejected for the same rationale as claim 9.
Regarding claim 20, this claim recites a system that performs the method of claim 10 as explained above. Therefore, claim 20 is rejected for the same rationale as claim 10.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ELIZABETH J SLOWIK whose telephone number is (571)270-5608. The examiner can normally be reached MON - FRI: 0900-1700.
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/ELIZABETH J SLOWIK/ Examiner, Art Unit 3662
/ANISS CHAD/ Supervisory Patent Examiner, Art Unit 3662
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