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 .
Remarks
The claims being considered in this application are those submitted on 09/26/2025. Claims 1-20 are pending.
The present application is a continuation of application 17/991,771 (Published as US20240167831A1 and also issued patent No. US12/449,268).
Information Disclosure Statement
The information disclosure statement filed on 12/18/2025 has been annotated and considered.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 12,449,268. Although the claims at issue are not identical, they are not patentably distinct from each other because as shown by the chart below, the claim language is very similar if not identical, and is merely rearranged in a different chain/dependency order.
The instant application 19/341,035 ‘s Claim 1 encompasses all of the limitations of US 12,449,268 ‘s Claim 6 (which includes the limitations of its parent Claim 1). Furthermore, Instant Application 19/341,035 ‘s Claim 1 is broader than the combination of Claim 6 and Claim 1 of the parent US 12,449,268, causing this application’s Claim 1 to be anticipated by ‘268’s Claim 6.
The application’s other claims in the chart below are also covered by ‘268’s claim 6 or a combination of claim 6 and other claims. For example, this instant application’s Claim 2 is covered by ‘26’s Claim 6 and Claim 2. Thus, this would be an obvious modification and is not patentably distinct from parent US 12,449,268.
US Patent No. 12,449,268
Claim #
Claim Language
Instant Application 19/341,035
Claim #
Claim Language
Claim 1
A method, comprising:
receiving, from a vehicle, a request for a charge, wherein one or more preferences are associated with the vehicle;
…
routing the vehicle to the charging location.
Claim 1
A method, comprising:
receiving, from a vehicle, a request for a charge, wherein one or more preferences are associated with the vehicle;
determining an area having a high charging demand;
altering the one or more preferences based on at least one characteristic of the area; and
routing the vehicle to a charging location based on the altered one or more preferences.
Claim 6
determining an area having a high charging demand
altering the preference based on a characteristic of the area.
Claim 2
wherein the receiving the request for the charge comprises: determining a battery level of the vehicle is below a threshold; and including the one or more preferences and the battery level in the request.
Claim 2
wherein the receiving the request for the charge comprises: determining a battery level of the vehicle is below a threshold; and including the one or more preferences and the battery level in the request.
Claim 3
wherein the routing comprises: routing the vehicle to the charging station based on the vehicle and the other vehicle being proximate.
Claim 3
wherein the routing comprises: routing the vehicle to the charging location based on the vehicle and another vehicle being proximate.
Claim 4
wherein the routing of the vehicle to the charging location comprises: determining a route to the charging location from a current location of the vehicle; and transferring the route to the vehicle.
Claim 4
wherein the routing of the vehicle to the charging location comprises: determining a route to the charging location from a current location of the vehicle; and transferring the route to the vehicle.
Claim 5
comprising: comparing the one or more preferences to one or more historical preferences related to the vehicle; modifying the one or more preferences based on the one or more historical preferences; and
selecting the charging location based on the one or more modified preferences.
Claim 5
comparing the one or more preferences to one or more historical preferences related to the vehicle; modifying the one or more preferences based on the one or more historical preferences.
Claim 6
comprising: selecting the charging location based on the one or more modified preferences.
Claim 7
comprising: determining that the vehicle has been rerouted to a different charging location that is different than the charging location; determining a change in a vehicle charging preference based on the different charging location; and storing the changed vehicle charging preference.
Claim 7
comprising: determining that the vehicle has been rerouted to a different charging location that is different than the charging location; determining a change in a vehicle charging preference based on the different charging location; and storing the change in the vehicle charging preference.
Claim 8
A system, comprising: a processor that, when executing instructions stored in a memory, is configured to: receive, from a vehicle, a request for a charge, wherein one or more preferences are associated with the vehicle;
…
route the vehicle to the charging location
Claim 8
A system, comprising: a processor that, when executing instructions stored in a memory, is configured to:
receive, from a vehicle, a request for a charge, wherein one or more preferences are associated with the vehicle;
determine an area having a high charging demand;
alter the one or more preferences based on at least one characteristic of the area; and
route the vehicle to a charging location based on the altered one or more preferences.
Claim 13
wherein the processor is configured to: determine an area that has a high charging demand proximate to the vehicle; and
alter the preference based on a characteristic of the area
Claim 9
wherein when the processor receives the request for the charge, the processor is configured to: determine a battery level of the vehicle is below a threshold; and include the one or more preferences and the battery level in the request.
Claim 9
wherein when the processor receives the request for the charge, the processor is configured to: determine a battery level of the vehicle is below a threshold; and include the one or more preferences and the battery level in the request.
Claim 10
wherein when the processor routes the vehicle, the processor is configured to: route the vehicle to the charging station based on the vehicle and the other vehicle being proximate to one another.
Claim 10
wherein when the processor routes the vehicle, the processor is configured to: route the vehicle to the charging location based on the vehicle and another vehicle being proximate to one another.
Claim 11
wherein the processor routes the vehicle, the processor is configured to: determine a route to the charging location from a current location of the vehicle; and transfer the route to the vehicle.
Claim 11
wherein the processor routes the vehicle, the processor is configured to: determine a route to the charging location from a current location of the vehicle; and transfer the route to the vehicle.
Claim 12
wherein the instructions are configured to: compare the one or more preferences related to the vehicle to one or more historical preferences related to the vehicle; modify the one or more preferences based on to the one or more historical preferences;
select the charging location of one or more charging locations based on the one or more modified preferences.
Claim 12
wherein the instructions are configured to: compare the one or more preferences related to the vehicle to one or more historical preferences related to the vehicle;
modify the one or more preferences based on the one or more historical preferences.
Claim 13
wherein the processor is configured to: select the charging location of one or more charging locations based on the one or more modified preferences.
Claim 14
wherein the processor is configured to: determine that the vehicle has been rerouted to a different charging location that is different than the charging location; determine a change in a vehicle charging preference based on the different charging location; and store the changed vehicle charging preference.
Claim 14
wherein the processor is configured to: determine that the vehicle has been rerouted to a different charging location that is different than the charging location; determine a change in a vehicle charging preference based on the different charging location; and store the change in the vehicle charging preference.
Claim 15
A non-transitory computer-readable medium comprising instructions that, when executed by a processor, cause the processor to perform: receiving, from a vehicle, a request for a charge, wherein one or more preferences are associated with the vehicle;
…
routing the vehicle to the charging location.
Claim 15
A non-transitory computer-readable storage medium comprising instructions that, when executed by a processor, cause the processor to perform:
receiving, from a vehicle, a request for a charge, wherein one or more preferences are associated with the vehicle;
determining an area having a high charging demand;
altering the one or more preferences based on at least one characteristic of the area; and
routing the vehicle to a charging location based on the altered one or more preferences.
Claim 20
wherein the instructions cause the processor to perform: determining an area having a high charging demand proximate to the vehicle; and altering the preference based on a characteristic of the area.
Claim 16
wherein the receiving the request for the charge comprises: determining a battery level of the vehicle is below a threshold; and including the one or more preferences and the battery level in the request.
Claim 16
wherein the receiving the request for the charge comprises: determining a battery level of the vehicle is below a threshold; and including the one or more preferences and the battery level in the request.
Claim 17
wherein the routing comprises: routing the vehicle to the charging station based on the vehicle and the other vehicle being proximate to one another.
Claim 17
wherein the routing comprises: routing the vehicle to the charging location based on the vehicle and another vehicle being proximate to one another.
Claim 18
wherein routing the vehicle to the charging location comprises: determining a route to the charging location from a current location of the vehicle; and transferring the route to the vehicle.
Claim 18
wherein routing the vehicle to the charging location comprises: determining a route to the charging location from a current location of the vehicle; and transferring the route to the vehicle.
Claim 19
wherein the instructions cause the processor to perform: comparing the one or more preferences to one or more historical preferences related to the vehicle; modifying the one or more preferences based on the one or more historical preferences; and selecting the charging location based on the one or more modified preferences
Claim 19
wherein the instructions cause the processor to perform: comparing the one or more preferences to one or more historical preferences related to the vehicle; modifying the one or more preferences based on the one or more historical preferences; and selecting the charging location based on the one or more modified preferences.
Claim 15
A non-transitory computer-readable storage medium comprising instructions that, when executed by a processor, cause the processor to perform:
Claim 20
wherein the instructions cause the processor to perform: determining that the vehicle has been rerouted to a different charging location that is different than the charging location; determining a change in a vehicle charging preference based on the different charging location; and storing the change in the vehicle charging preference
Claim 14
wherein the processor is configured to: determine that the vehicle has been rerouted to a different charging location that is different than the charging location; determine a change in a vehicle charging preference based on the different charging location; and store the changed vehicle charging preference.
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 1-4, 8-11, and 15-18 are rejected under 35 U.S.C. 103 as being unpatentable over Zhong et. al. (CN108688503A, Translation Attached) in view of Karri et. al. (US 20220089043 A1, IDS).
Regarding Claim 1, Zhong discloses:
A method, comprising: (See at least ¶0007 via "this invention provides a highly feasible auxiliary decision-making method for electric vehicle users' charging choices, taking into account transmission congestion" and ¶0101 via "Step 1: Determine if the electric vehicle has a charging need. If so, select a set of alternative charging stations and proceed to Step 2" as well as ¶103 via "the first step is to determine the charging demand of the electric vehicle…When the remaining charge (SOC) of the electric vehicle is lower than the remaining charge threshold (S) at which the user usually starts charging…the charging demand is triggered" and ¶0206 via "Suppose that the electric vehicle is currently triggering a charging demand…")
wherein one or more preferences are associated with the vehicle; (See at least ¶0107 via "The threshold S is determined by each car owner's charging habits and preferences, and is derived from statistical analysis of historical charging data recorded by the electric vehicle terminal equipment" and also ¶0168 via "Based on the different preferences for the three indicators according to the questionnaire survey and historical case data…a binary comparison method is used to compare and assign values to related indicators at the same level to obtain the judgment matrix…Based on the different preferences for the three indicators according to the questionnaire survey and historical case data…comparing two factors, if they have the same importance…the importance of road condition information compared to charging time" **Wherein the one or more preferences associated with the vehicle is interpreted under BRI and comprises preference weights that correspond to importance of specific attributes such as charging time, electricity price [which is dynamically set based on the load/power congestion of charging areas], and the distance.)
determining an area having a high charging demand; (See at least ¶0115 via "Step 2: Collect and analyze traffic information on routes from the location of the electric vehicle to each alternative charging station…which in turn will affect the spatial distribution of electric vehicle load" as well as ¶0129 via "The electric vehicle charging station monitoring system monitors the usage of charging piles and the number of electric vehicles in the queue in real time, and obtains the estimated value of electric vehicle charging queuing time T<sub>p< /sub>" and ¶0135 via "Step 4: Based on the congestion situation of the distribution network…formulate corresponding guiding electricity prices for each alternative charging station" and ¶0155 via "The formulation of Cd takes into account two factors: the relative level g and the absolute level e of the load of the node where the charging station is located" and ¶0158 via "When g>0, it means that the load of the charging station node exceeds its optimal compensation load, and g is added to the guiding electricity price as a penalty factor." as well as ¶0161 via "When e > 0, it indicates that the power sensitivity of the charging station node is positive and the load is relatively high" **Wherein the charging location having a relatively high charging load is interpreted as corresponding to the area having a high charging demand)
altering the one or more preferences based on at least one characteristic of the area; and (See at least ¶0168-¶0176 via "5-1) Constructing the Judgment Matrix: Based on the different preferences for the three indicators…road condition information, with charging time and electricity price ratings…5-2) Calculate attribute weights…normalize W to obtain the weights of each factor…5-3) Entropy weight method to correct weights: AIIJJ is the attribute index matrix of charging stations. The index data of each charging station is standardized…" as well as ¶0209 via "The charging selection decision analysis method based on AHP-TOPSIS is calculated step by step; based on user questionnaires and historical case data" and ¶0182 via "A positive ideal solution is one where all attributes of the charging station are optimal, namely, the shortest charging time, the lowest electricity price, and the closest distance." and ¶0212 via "After correcting the weight matrix and entropy weight matrix using the formula, the comprehensive weight matrix W is obtained". Additionally, this is illustrated through the disclosed example: See at least ¶0206 via "the three nearest charging stations are 2, 3, and 5…If charging station 5 has a positive power sensitivity to the over-limit branch and the predicted load exceeds the optimal compensation by the most, then a higher guiding electricity price will be used to reduce the load demand at that point", as well as ¶0222 via "Due to the widespread "range anxiety" among electric vehicle users, based on their past decision-making habits, they will prioritize charging at charging station 2, which has good road conditions and the lowest time-of-use electricity price. In this scheme, the time-of-use electricity price is closest to the ideal solution, while the benefit values of other attributes are relatively low. Considering the performance of all attributes, it is not the optimal choice. The optimal decision provided by this method is charging station 3. This solution achieves the highest benefit for some relatively important individual attributes while being closest to the positive ideal solution and far from the negative ideal solution based on user preferences. It also improves the closeness by 0.2652 compared to charging station 2, indicating that charging station 3 is closer to the overall interests of users in all aspects." **Wherein under BRI, the preferences are being interpreted as the relative weights representing a user's charging preferences that are used in the decision making of selecting a charging station. The preferences/weights are corrected [altered] and the guiding electricity price is dynamically changed (See ¶0152) based on the load at the nodes/charging stations, which are characteristics of the area, and the guiding electricity price is used as a preference when determining the optimal charging station)
(See at least ¶0165 via "Step 5: Combining road condition information, charging time, and the guiding electricity price of alternative charging stations, establish a comprehensive evaluation index system for charging selection using the analytic hierarchy process (AHP), entropy weight method, and approximation ideal solution ranking method to achieve the optimal charging selection for electric vehicle users" and ¶0166 via "…evaluate each candidate charging station, rank them according to their merits, and then select the best one…" as well as ¶0222 via "The optimal decision provided by this method is charging station 3. This solution achieves the highest benefit for some relatively important individual attributes while being closest to the positive ideal solution and far from the negative ideal solution based on user preferences. It also improves the closeness by 0.2652 compared to charging station 2, indicating that charging station 3 is closer to the overall interests of users in all aspects.").
However, Zhong discloses the vehicle's indication of needing a charge, Zhong does not explicitly disclose the "receiving". Additionally, although Zhong discloses calculating distances to each candidate charging station (See Zhong ¶0219 via "The calculated distances from each charging station"), and Zhong discloses selecting the ideal charging station (See Zhong ¶0222); Zhong does not explicitly disclose the active routing to the station.
Nevertheless, Karri-who is directed towards routing and charging of electric powertrain vehicle(s)--discloses: receiving, from a vehicle, a request for a charge (See at least ¶0024 via "For example, the EAVN may be configured to retrieve a current range of a first electric vehicle in response to receiving a request to find a place to charge.")
routing the vehicle to a charging location (See at least ¶0027 via “The EAVN may be configured to update the guidance or routing of vehicles based on the electric vehicle parameters. The EAVN may also be configured to update the guidance or routing of vehicles based on congestion in an environment” and Figures 5-6).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Zhong in view of Karri's EAVN receiving a request from a vehicle in order to solve the identified problem of uncoordinated/overcrowded charging, which is in line with Zhong's goal of improving the load balance and power distribution: "Users will make different decisions based on their behavioral preferences and different environmental conditions, which makes the load on electric vehicles highly random and affects the load balance of the power distribution network" [Zhong ¶0005]. Thus, it would be obvious to incorporate Karri's EAVN, and would provide more coordinated and holistic system of coordinating multiple vehicles that need charging: "Electricity aware vehicle navigation (EAVN) may overcome the many drawbacks associated with uncoordinated and overcrowded vehicle usage. The EAVN may operate to provide guidance and route planning such that electric vehicles are recharged in an effective manner…provide a charge in a coordinated fashion…observe and react to traffic conditions of other electric vehicle…observe the flow of traffic generally through an environment, and to determine that various routes should be used to reduce the wait time, and the charge time…operate on a holistic level, to provide electric vehicles with access to charge points for the route they are trying to travel, and to ultimately reach an end point, while also prioritizing other vehicles that are also trying to reach other end points." [Karri ¶0022]. Additionally, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Zhong in view of providing directions or actively routing the vehicle, such as in Karri, to the optimal charging station that was already determined by Zhong, as a predictable step for a vehicle that has both determined it needs to charge and has determined/selected the optimal charging station (See Zhong ¶0222).
Regarding Claim 8, Zhong discloses:
(Regarding the steps performed, see Claim 1 rejection as the steps are the same).
However, Zhong does not explicitly disclose the processor or memory.
Nevertheless, Karri discloses: A system, comprising: a processor that, when executing instructions stored in a memory, is configured to: (See at least ¶0032 via "The computer system 100 may include a processor 110, memory 120…" and ¶0033 via " The processor 110 may additionally include one or more memory buffers or caches (not depicted) that provide temporary storage of instructions and data for the cores 112").
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Zhong in view of the processor and memory such as disclosed by Karri, to provide a computer system for executing the method disclosed by Modified Zhong.
Regarding Claim 15, Zhong discloses:
(Regarding the steps performed, see Claim 1 rejection as the steps are the same).
However, Zhong does not explicitly disclose the non-transitory computer-readable medium.
Nevertheless, Karri discloses: A non-transitory computer-readable storage medium comprising instructions that, when executed by a processor, cause the processor to perform: (See at least ¶0089 via "The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing…" and ¶0032-¶0033).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Zhong in view of including a non-transitory computer-readable storage medium such as in Karri in order to provide a memory that can be used in the computer system to execute the instructions for the method disclosed by Modified Zhong.
Regarding Claims 2, 9, and 16 respectively, Modified Zhong discloses the method of Claim 1, the system of Claim 8, and the non-transitory computer-readable storage medium of Claim 15.
Furthermore, Zhong discloses: (See at least ¶0014 via "when the remaining power SOC of the electric vehicle is lower than the remaining power threshold S at which the user usually starts charging or when the remaining power SOC cannot reach the destination, the charging demand is triggered").
However, although Zhong discloses one or more preferences (See at least Zhong ¶0107 and ¶0168) and the battery level (See Zhong ¶0014), Zhong does not disclose the receiving the request or including the preferences/battery level in the request.
Nevertheless, Karri discloses: wherein the receiving the request for the charge (See at least ¶0024 via "For example, the EAVN may be configured to retrieve a current range of a first electric vehicle in response to receiving a request to find a place to charge.")
including the one or more preferences and the battery level(See at least ¶0070 via "The request may be based on a need of vehicle 412-1 to receive a charge, e.g., vehicle 412-1 may currently have a low amount of charge" and ¶0072 via " method 500 of performing vehicle routed in concert with assigning vehicle charging…method 500 may be executed responsive to only electric vehicles that are below a certain charging threshold, such as below 75% charge". Also see ¶0073 via "Responsive to the request, an EAVN may request additional information, such as the make and model of the requesting vehicle" ¶0075 via "If the vehicle is an electric vehicle at 520:Y, one or more parameters of the vehicle may be retrieved at 530. The one or more parameters of the vehicle may be retrieved by a request directly to the vehicle. The one or more parameters of the vehicle may be retrieved from a storage").
However, although Karri discloses both a battery level and one or more preferences, Karri does not disclose this information is included in the request itself. Nevertheless, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Zhong in view of including this information in the request since Karri's EAVN already retrieves information in response to the request in order to determine charging and routing decisions, and providing it in the initial request would enable the EAVN to process relevant information in the initial request, which reduces the amount of back and forth communication needed between the vehicle and the EAVN : "Responsive to the request, an EAVN may request additional information, such as the make and model of the requesting vehicle…" [Karri ¶0073] and uses the battery being below a threshold to initialize the method 500: "method 500 may be executed responsive to only electric vehicles that are below a certain charging threshold" [Karri ¶0072].
Regarding Claims 3, 10, and 17 respectively, Modified Zhong discloses the method of Claim 1, the system of Claim 8, and the non-transitory computer-readable storage medium of Claim 15.
However, Zhong does not explicitly disclose, but Karri discloses: wherein the routing comprises: routing the vehicle to the charging location based on the vehicle and another vehicle being proximate (See at least ¶0078 via "At 560 a second route may be generated…The second route may be generated based on additional vehicles. For example, one or more additional vehicles proximate to one or more of the potential routes may be detected. The additional vehicles may have other requirements such as battery parameters (e.g., a charge that the second vehicle needs to receive from a charger, a compatibility with only certain chargers). The second route may be updated based on the additional vehicles…a second route may be selected that permits a reduced total time of both the first electric vehicle and additional electric vehicles to charge at a plurality of electric chargers that are adjacent to the routes of the vehicles, even if some of the electric chargers may be shared or if the routes may overlap". Also see ¶0079 and Figure 6 in combination with ¶0083-¶0087).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Zhong in view of Karri's second route that considers other proximate vehicles in order to increase the coordination of multiple vehicles needing a charge while efficiently distributing the vehicles across multiple charging locations, thus reducing overcrowding and operating with considerations for multiple vehicles in a holistic manner. This also facilitates Zhong's goal of improving the load balance and power distribution: "Users will make different decisions based on their behavioral preferences and different environmental conditions, which makes the load on electric vehicles highly random and affects the load balance of the power distribution network" [Zhong ¶0005]. Thus, it would be obvious to incorporate Karri's EAVN that provides a second route based on other proximate vehicles that need charging: "Electricity aware vehicle navigation (EAVN) may overcome the many drawbacks associated with uncoordinated and overcrowded vehicle usage. The EAVN may operate to provide guidance and route planning such that electric vehicles are recharged in an effective manner…provide a charge in a coordinated fashion…observe and react to traffic conditions of other electric vehicle…observe the flow of traffic generally through an environment, and to determine that various routes should be used to reduce the wait time, and the charge time…operate on a holistic level, to provide electric vehicles with access to charge points for the route they are trying to travel, and to ultimately reach an end point, while also prioritizing other vehicles that are also trying to reach other end points." [Karri ¶0022].
Regarding Claims 4, 11, and 18 respectively, Modified Zhong discloses the method of Claim 1, the system of Claim 8, and the non-transitory computer-readable storage medium of Claim 15.
Furthermore, although Zhong discloses calculating the distance to available chargers (See Zhong ¶0024 via "For electric vehicles with charging needs, the location of charging stations within their remaining mileage range is calculated through intelligent transportation systems and in-vehicle navigation systems, and they are arranged in ascending order of distance between the electric vehicle and the charging station"), Zhong does not explicitly transfer the route to the charging location from the current location of the vehicle.
Nevertheless, Karri discloses: wherein the routing of the vehicle to the charging location comprises: determining a route to the charging location from a current location of the vehicle; and transferring the route to the vehicle (See at least ¶0073 via "The route detection may be from a vehicle that is already moving, e.g., during movement an autonomous vehicle may send out a status update along with its current route." and ¶0076 via "The identification of the chargers may be based on the location or roadways of the route. Specifically, based on a start point (where a vehicle currently is located) and to the endpoint (all the roads that may be able to reach the end point, including the current route that is being driven is or about to be driven by the vehicle). For example, the EAVN may be configured to identify all chargers that are proximate to a first route that is a current route of the vehicle.". Additionally see Figure 5 and ¶0080 via "At 570 the second route may be provided. The second route may be provided by replacing the first route of the electric vehicle with the second route. The second route may be provided by updating or otherwise modifying the first route" and also ¶0024 via "For example, an EAVN may be configured to receive a request for routing of a vehicle that is already on a roadway and is moving towards an end point.").
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Zhong in view of providing the route to the vehicle such as in Karri, in order to increase the holistic coordination of multiple vehicles, by providing a given electric vehicle with an updated route that considers the other proximate vehicles: "The second route may be generated despite not decreasing the time or distance of the electric vehicle. …While a second route may be generated that increases the distance or the time it takes for the first electric vehicle to traverse to the end point, the second route may permit two other electric vehicles to arrive at other destinations more quickly…By routing the first electric vehicle on a second route that avoids the restaurant and associated electric charger, the second electric vehicle may not have to wait, and a third electric vehicle may also be able to receive charge in the same time that the first electric vehicle may have taken at the charger near the restaurant." [Karri ¶0079] while also considering current traffic conditions and use of charging infrastructure: " The EAVN may be configured to update guidance and routing for use of charging infrastructure based on traffic conditions and various points during a route from a start point to an end point." [Karri ¶0028], so the vehicles can navigate based on updated information and conditions.
Claims 5-6, 12-13, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Zhong et. al. (CN108688503A, Translation Attached) and Karri et. al. (US 20220089043 A1, IDS) in view of Kreifeldt (US 20160195405 A1).
Regarding Claims 5, 12, and 19 respectively, Modified Zhong discloses the method of Claim 1, the system of Claim 8, and the non-transitory computer-readable storage medium of Claim 15.
Furthermore, Zhong discloses: comprising: comparing the one or more preferences (See at least ¶0068 via "5-1) Constructing the Judgment Matrix: Based on the different preferences for the three indicators according to the questionnaire survey and historical case data, and based on the scaling and judgment principle of pairwise comparison, the binary comparison method is used to compare and assign values to related indicators at the same level to obtain the judgment matrix.")
modifying the one or more preferences (See at least ¶0076 via "5-3) Entropy weight method to correct weights: AIIJJ is the attribute index matrix of charging stations. The index data of each charging station is standardized and denoted as xIIJJ. …the comprehensive weight of the sample is calculated" *Wherein the correction of the preference based weight matrix is considered under BRI as modifying preferences).
However, although Zhongs preferences/weights are derived from historical case data, and Zhong corrects weights associated with preferences; Zhong does not explicitly compare current preferences to historical preferences and modify the preferences based on the historical preferences.
Nevertheless, Kreifeldt--who is directed towards a learning and predictive navigation system--discloses: (See at least ¶0035 via "Moreover, the logic on the navigation system 100 could consider the user's preferences and historical behavior with respect to parking at the POI or other POIs (e.g., POIs in the same general location, POIs of the same type, etc.)" as well as ¶0017 via "The user information 130 includes a destination history 135 for the user 120, parking preference data 140 for the user 120, social media data 145 for the user 120 and driving preference data 147 for the user 120…The parking preference data 140 generally represents the user's 120 parking preferences…if the user frequently arrives at the destination (e.g., a restaurant), pauses briefly at the front door, and then begins travelling again to a nearby parking location, the navigation component 115 could determine that the user 120 has used valet parking and could update the parking preference data 140 accordingly…parking preference data 140 could be learned based on the user's behavior with respect to the navigation device 110. For instance, if the user frequently searches for parking garages as a destination, the navigation component 115 could update the parking preference data 140 to indicate that the user 120 has a preference for public parking facilities.").
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Zhong in view of the consideration of user preferences and historical behavior to facilitate the modification of preferences such as in Kreifeldt in order to personalize/customize the navigation system with respect to a specific user: "Additionally, the navigation component 115 can use user profile data for the user to predictively select destinations and routes that best match the user's preferences and intended meaning. Doing so provides an improved interface that enables the user to more naturally converse with the navigation device 400." [Kreifeldt ¶0058] and "The navigation component 115 could also receive historical driving and destination information from the navigation device 110, describing previous destinations visited by the user and previous routes taken by the user, for use in improving the driver's profile information and geospatial command model…monitoring the user's behavior and feedback in order to refine the driver's profile and geospatial command model." [Kreifeldt ¶0024].
Regarding Claims 6, and 13 respectively, Modified Zhong discloses the method of Claim 5 and the system of Claim 12.
Furthermore, Zhong discloses: comprising: selecting the charging location based on (See at least ¶0168-¶0176 via "…5-3) Entropy weight method to correct weights…" and ¶0165 via "Step 5: Combining road condition information, charging time, and the guiding electricity price of alternative charging stations, establish a comprehensive evaluation index system for charging selection using the analytic hierarchy process (AHP), entropy weight method, and approximation ideal solution ranking method to achieve the optimal charging selection for electric vehicle users" and ¶0166 via "…evaluate each candidate charging station, rank them according to their merits, and then select the best one…" as well as ¶0222 via "The optimal decision provided by this method is charging station 3. This solution achieves the highest benefit for some relatively important individual attributes while being closest to the positive ideal solution and far from the negative ideal solution based on user preferences. It also improves the closeness by 0.2652 compared to charging station 2, indicating that charging station 3 is closer to the overall interests of users in all aspects.").
However, Zhong does not disclose the modified preferences that are based on the historical preferences (as stated in parent claim 5).
Nevertheless, Kreifeldt discloses selecting the (See at least ¶0035 via the consideration of user preferences and historical data, and ¶0017 via the updating. Additionally see ¶0058 via "Additionally, the navigation component 115 can use user profile data for the user to predictively select destinations and routes that best match the user's preferences and intended meaning").
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Zhong in view of the modified preferences with respect to the historical behavior/preferences such as in Kreifeldt in order to personalize/customize the navigation system with respect to a specific user: "Additionally, the navigation component 115 can use user profile data for the user to predictively select destinations and routes that best match the user's preferences and intended meaning. Doing so provides an improved interface that enables the user to more naturally converse with the navigation device 400." [Kreifeldt ¶0058] and "The navigation component 115 could also receive historical driving and destination information from the navigation device 110, describing previous destinations visited by the user and previous routes taken by the user, for use in improving the driver's profile information and geospatial command model…monitoring the user's behavior and feedback in order to refine the driver's profile and geospatial command model." [Kreifeldt ¶0024]
Claims 7, 14, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Zhong et. al. (CN108688503A, Translation Attached) and Karri et. al. (US 20220089043 A1, IDS) in view of Ravi et. al. (US 20190087759 A1).
Regarding Claims 7, 14, and 20 respectively, Modified Zhong discloses the method of Claim 1, the system of Claim 8, and the non-transitory computer-readable storage medium of Claim 15.
Furthermore, Karri discloses: comprising: determining that the vehicle has been rerouted to a different charging location that is different than the charging location; (See at least ¶0086 via " If there is a route conflict that is determined at 630:Y, then updated guidance may be issued at 640. The updated guidance may be issued to a first vehicle. For example, if an electric charger is no longer working, the updated guidance may be to instruct the first vehicle that had a route that would include charging at the electric charger to reroute to another charger…the updated guidance may be to instruct a first vehicle to reroute to a second electric vehicle charger…").
However, Karri does not explicitly disclose changing the vehicle preferences based on the different charging location.
Nevertheless, Ravi--who is directed towards monitoring a charging pattern to identify a customer--discloses: determining a change in a vehicle charging preference based on the different charging location; and storing the change in the vehicle charging preference (See at least Claim 14 via "storing a charging station location when a user connects the vehicle to a new charging station and to store a charging preferences for the new charging station" as well as ¶0028 via "a first user prefers a first charging mode while charging the vehicle 102 at a first location and a second charging mode while charging the vehicle at a second location…" and ¶0029 via " store information related to each of the users indicating preferred charging locations other than a home location or a work location…prompt the user, via the display, to store a charging station location when the user connects the vehicle 102 to the charging station for the first time. Additionally, the manufacturer system 230 may store preferences for this charging station, such as cost savings based on time of use rates, preferred charging mode, desired range, desired costs, etc").
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Zhong in view of storing an updated vehicle preference based on a different charging station such as in Ravi in order to maintain and update charging preferences associated with a new/different location, which increases personalization for a given user: "…when the user connects to the same charging station in the future, the manufacturer system 230 already has a profile stored for the charging station...Based on the driving schedule for the vehicle 102, the manufacturer system 230 may store a charging pattern for a given charging location based on the driver identified by the driving schedule" [Ravi ¶0029-¶0030].
Conclusion
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/K.R.D./Examiner, Art Unit 3657
/ABBY LIN/Supervisory Patent Examiner, Art Unit 3657
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