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 .
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.
Joint Inventors
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Response to Arguments and Amendments
Applicant’s arguments and amendments, filed June 22nd, 2026, have overcome each and every claim objection and 35 U.S.C. 112(b) rejection previously set forth in the Non-Final Office Action sent on March 27th, 2026 because the Applicant has cancelled claims 2-4 and 6-8.
Applicant’s arguments and amendments, with respect to the rejections of claims 1 and 5 under 35 U.S.C. 102(a)(1)/(a)(2) have been fully considered and are persuasive. Therefore, the rejections have been withdrawn. However, upon further search and consideration, a new ground(s) of rejection is made in view of Uchiumi (JP Patent Pub. No. 2014-225167A) for claim 1 and Ballantine et al. (US Patent Pub. No. 2023/0322109 A1) for claim 5. Examiner notes both the limitations of including “a day of the week and a time of day” in the congestion status database and the energy filling station being a “hydrogen station” are being interpreted by the Examiner as either well-known and commonly understood in the art, or a simple design choice. Just as an example, Tesla charging stations fully teach every single limitation in claim 1, and the Examiner is not relying upon it for support; therefore, the Examiner suggests for the Applicant to pursue narrowing other claim limitations in light of the specification in order to potentially overcome the prior art.
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.
Claim 1 is rejected under 35 U.S.C. 103 as being obvious over Mariyasagayam (EP Patent Pub. No. 2 717 016 A1) in view of Hiruta et al. (US Patent Pub. No. 2011/0224900 A1), herein “Hiruta”, and Uchiumi (JP Patent Pub. No. 2014-225167A).
Regarding Claim 1, Mariyasagayam discloses a route guidance system comprising:
a navigation device that searches for a driving route to a destination based on the destination and a transit point, and provides route guidance using the searched driving route, the navigation device including a processor that performs information processing (See 0002, “[…] providing route assistance services for electric vehicles […] taking into account a navigation route from a start location to a destination location being traveled by the respective electric vehicle based on shortest distances towards available charging stations […]” See also 0079, “[…] navigation may be managed by the service center SC server(s) when there is no or limited navigation capability. Also, when devices have navigation capabilities, a navigation device can be included in the user system and can be interfaced with the in-vehicle network control means […]”); and
a management server that manages an operational status of a plurality of energy filling stations, and stores, in a memory that stores information, a congestion status database storing a congestion status of each of the plurality of energy filling stations (See 0011, “[…] providing charging station data for a plurality of charging stations indicative of respective locations of a plurality of charging stations […]” See also 0032-0033, “[…] determination of the risk parameter may be further based on a number of currently occupied charging spots at the first charging station indicated in the charging station data […] may be further based on a total number of charging spots at the first charging station in the charging station data […]” See also 0061, “[…] service center SC may comprise one or more connected server computers and databases and is configured to provide route assistance […]” See also 0069, “[…] charging station or charging station provider provides data information to the service center SC server(s) via the communication network NTW about the current charging conditions such as maximum number of charging spots, currently occupied spots, rate at which charging is happening […]” See also 0082, “[…] memory unit 130 stores user data 131, charging station data 132 and traffic data […]” See also 0088, “Charging station data 132 further includes data such as number of vehicles arriving over a period of time and also the number of vehicles leaving the charging station […]” Examiner notes there is clear support for a management server storing information regarding the congestion status at a plurality of charging stations, which is an energy filling station), and
a service information database storing a location and service information of each of the plurality of energy filling stations (See 0064-0065, “[…] service center SC is configured to communicate via the communication network NTW with the one or more traffic centers TC, the one or more power stations PS, the one or more charging stations and the one or more electric vehicles […] configured to exchange data with the one or more traffic centers TC, the one or more power stations PS, the one or more charging stations and the one or more electric vehicles […] may store location information indicating locations of the charging stations CS pre-loaded into a memory means or a database or the location information on locations of charging stations may be received, automatically or upon request, from directly from charging stations or from a charging station service provider providing services in connection with one or more charging stations, such as e.g. reservation services. Charging station data may therefore be pre-stored at the service center SC and/or received (upon request or automatically on a regular basis) from charging stations and/or charging station service providers.” See also 0105, “[…] the server-side apparatus/system receives the current position of the electric vehicle of the user, the travelling direction thereof and/or the final destination. This information may be obtained, for example, in two ways, i.e. the vehicle may send travel information details during request for service provision […]”),
wherein the processor
searches for a reference driving route to the destination based on the destination and the transit point (See 0002 and 0079 as referenced above),
obtains the location of each of the plurality of enemy filling stations from the service information database of the management server (See 0011 and 0064-0065 as referenced above),
searches for a plurality of energy filling stations located around the reference driving route (See 0035-0036, “[…] travelling in the direction of the first charging station (the risk parameter preferably increasing with increasing number electric vehicles located in the perimeter of the first charging station and travelling in the direction of the first charging station) […] a perimeter region for the first charging station, the first charging station being located in the perimeter region […] travelling towards the first charging station. Preferably, the deciding, whether to re-route one or more first electric vehicles, is then based on electric vehicle data for electric vehicles located in the perimeter region and travelling towards the first charging station […]”),
sets the searched plurality of energy filling stations as a plurality of filling station candidates (See 0011, 0032-0033 and 0069 as referenced above. See also 0019, “[…] a new route based on other subsequent charging stations may then be selected and proposed […]” See also 0022, “[…] respective risk parameter (risk factor) exceeds the threshold value can be decided to be re-routed to one or more other charging stations for avoiding overloading of the first charging station.” Examiner notes subsequent charging stations being potential destinations for new routes due to information regarding issues at an initial charging station means every other charging station in the plurality of charging stations is a candidate),
obtains the service information of each of the plurality of filling station candidates from the service information database of the management server (See 0011, 0064-0065 and 0105 as referenced above),
searches a driving route to the plurality of reset filling station candidates and estimates an arrival time at each of the plurality of reset filling station candidates (See 0011, 0032-0033, 0048-0050 and 0069 as referenced above),
estimates a waiting time period at each of the plurality of reset filling station candidates by referring to the congestion status associated with the day of the week and the time of day in the congestion status database at the estimated arrival time, (See 0048-0050, “[…] determining an expected minimal queuing time based on a minimal value of the determined liberation times (or expected remaining charging durations) and the estimated travel time […] comparison of the estimated travel time of the first electric vehicle to the second charging station and the sum of the estimated travel time of the first electric vehicle to the first charging station and the expected minimal queuing time […]”)
for each of the plurality of reset filling station candidates, searches for a filling station inclusive driving route incorporating one of the plurality of reset filling station candidates as the transit point (See 0019-0022, “[…] assist route selection by associating a risk parameter (risk factor) for charging at a charging station along a planned route of a first electric vehicle […] a new route based on other subsequent charging stations may then be selected and proposed […] to determine associated risk parameters (risk factors) for charging at a specific first charging station along the travel route […] when the risk parameter (risk factor) for a certain first electric vehicle exceeds a pre- determined threshold value, a suitable alternative route towards another charging station can re-calculated and advised […]”), and
calculates a required time period to reach the destination, including the estimated waiting time period at the estimated arrival time, for each of the searched filling station inclusive driving routes (See Fig. 8 shown below and 0119, “[…] a time-to-reach-factor TTRF (auxiliary parameter) is calculated.” See also 0127-0129, “[…] the server -side apparatus/system determines an estimate of a number FCS of available charging spots at the time of arrival of the assisted electric vehicle EVEGO at the identified charging station based on the number FC - OC of currently available charging spots and the number OC of currently occupied charging spots […] may determine, for each currently occupied charging spot for which the estimated travel time ETREGO of the assisted electric vehicle EVEGO to the identified charging station is shorter than the respective expected remaining charging duration […]” See also 0130, “[…] estimating a number FCS of available charging spots at a charging station and for determining one or more liberations times LT and an expected minimal queuing time MQT.”), and
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provides the route guidance using the filling station inclusive driving route with the shortest required time period (See 0002 and 0048 as referenced above. See also 0084, “[…] suggest the best route with least amount of charging necessary (e.g. depending on the charging stations present along the route). The best route need not necessarily be the fastest or the shortest route - and at such situations, if the user desires only the shortest or fastest route, the server may provide assistance for that route […]”).
But does not explicitly disclose the congestion status associated with a day of the week and a time of day, and
the processor resets the plurality of filling station candidates by excluding out-of-service filling station candidates from the plurality of filling station candidates.
Uchiumi, in a similar field of endeavor, teaches the congestion status associated with a day of the week and a time of day (See 0014-0016, “[…] include an operation status on the same day of the same day as the estimated arrival time in a predetermined period of the selected charging station stored in the operation status database. According to this invention, the accuracy of the operation forecast information can be enhanced to further improve the operation efficiency of the charging station […] the operation prediction information may include the charge reservation on the same day of the same day as the estimated arrival time in the predetermined period of the selected charging station stored in the operation status database.” See also 0025, “[…] storage unit 15 stores the charging station database 16 in which information such as the position information of the charging stations 21A to 21E and the names for identifying the charging stations 21A to 21E is stored, and information about the operation status […]”).
Hiruta, in a similar field of endeavor, teaches the processor resets the plurality of filling station candidates by excluding out-of-service filling station candidates from the plurality of filling station candidates (See 0049, “[…] charging station information acquisition device 170 obtains, from an external provider 175, charging station position information and information indicating availability conditions at the charging stations.” See also 0087-0088, “[…] display information indicating the availability conditions of the individual charging stations, obtained from an external source […] a display of charging station availability conditions. The availability condition information is obtained from an external operation management center responsible for managing charging station availability conditions […] the charging station with the shortest wait time, based upon the charging station availability conditions […]” Examiner notes the availability conditions being zero is the same as that respective charging station being out-of-service).
In view of Uchiumi and Hiruta’s teachings, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include, with the route assistance device corresponding between a plurality of charging stations and congestion-derived waiting times for travel time determination as disclosed by Mariyasagayam, a database including time and day of week information, along with exclusion of out-of-service station candidates, with a reasonable expectation of success, since all three references are directed towards providing route assistance for vehicles and include charging/filling station data parameters for route evaluation and comparison. Furthermore, time-relevant information related to the plurality of charging/filling stations is a common and well-known concept (i.e., Tesla charging stations), while removing unavailable stations in the candidate selection process improves system efficiency and routing accuracy; and as an additional function of the existing system, involves only routine skill in the art.
Claim 5 is rejected under 35 U.S.C. 103 as being obvious over Mariyasagayam (EP Patent Pub. No. 2 717 016 A1) in view of Hiruta et al. (US Patent Pub. No. 2011/0224900 A1) and Uchiumi (JP Patent Pub. No. 2014-225167A) as applied to claim 1 above, and further in view of Ballantine et al. (US Patent Pub. No. 2023/0322109 A1), herein “Ballantine”.
Regarding Claim 5, Mariyasagayam does not explicitly disclose the route guidance system according to claim 1, wherein the energy filling station is a hydrogen station.
Ballantine, in a similar field of endeavor, teaches the energy filling station is a hydrogen station (See Abstract, “[…] hydrogen generating system may also produce and provide hydrogen to the vehicle network. In some implementations, the vehicle network may include one or more electrical vehicles, hydrogen fuel-based vehicles, or hybrid hydrogen/electrical vehicles.”).
In view of Ballantine’s teachings, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include, with the route assistance device corresponding between a plurality of charging stations and congestion-derived waiting times for travel time determination as disclosed by Mariyasagayam, the filling station to be a hydrogen station, with a reasonable expectation of success, since there is only a limited amount of energy types that an energy refilling station for a vehicle can include, and claiming the specific type of energy for the filling station is a simple and conventional design choice.
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 Bryant Tang whose telephone number is (571)270-0145. The examiner can normally be reached M-F 8-5 CST.
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/BRYANT TANG/Examiner, Art Unit 3658
/THOMAS E WORDEN/Supervisory Patent Examiner, Art Unit 3658
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