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 .
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. 12,146,749 (hereinafter, “the ‘749 patent”). Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1-20 of the application are anticipated by claims 1-20 of the ‘749 patent.
Regarding claim 1, the ‘749 patent recites a system, comprising: a server computer comprising a processor and a memory storing instructions that, when executed by the processor, cause the processor to perform steps comprising (column 23, lines 43-46): identifying a plurality of routes connecting a start location and a destination among historical route information collected over a period of time from one or more vehicles, wherein the plurality of routes are traveled by the one or more vehicles and reported to the server computer during the period of time to get from the start location to the destination (column 23, lines 51-57); determining an estimated time for arrival associated with a selected route among the plurality of routes, wherein the selected route includes a plurality of waypoints (column 23, lines 58 and 61-63), determining comprising: identifying a time duration for each waypoint (column 23, line 65); determining an adjustment factor for at least one waypoint (column 23, lines 66-67); determining an augmented time duration based on the adjustment factor and the time duration associated with the at least one waypoint (column 24, lines 1-3); determining the estimated time for arrival based on at least the time duration for each waypoint and the augmented time duration for the at least one waypoint (column 24, lines 4-5); and outputting the estimated time of arrival for the selected route (column 24, lines 6-7).
Regarding claim 2, the ‘749 patent recites the system of claim 1, wherein each element of the historical route information is associated with a coefficient indicative of an age of the element of the historical route information, wherein the element of the historical route information is weighed using the coefficient (column 25, lines 5-9).
Regarding claim 3, the ‘749 patent recites the system of claim 1, wherein the adjustment factor is based on at least one of a time of day for servicing the selected route, the day for servicing the selected route, a road condition along the selected route, traffic data, weather data, or local events data (column 24, lines 8-12).
Regarding claim 4, the ‘749 patent recites the system of claim 1, wherein the adjustment factor is determined based on the historical route information to add or subtract from the time duration for each waypoint (column 24, lines 13-15).
Regarding claim 5, the ‘749 patent recites the system of claim 1, wherein the time duration is a baseline time duration which is obtained from the historical route information (column 24, lines 16-18).
Regarding claim 6, the ‘749 patent recites the system of claim 1, wherein the instructions, when executed by the processor, cause the processor to perform steps further comprising (column 24, lines 19-23): receiving a routing update from a vehicle servicing the selected route, wherein the routing update includes a new waypoint that was not a part of the selected route (column 24, lines 22-24); updating a route selection algorithm based on the routing update (column 24, lines 25-26); and determining a new estimated time of arrival based on the waypoints identified in the routing update (column 24, lines 27-28).
Regarding claim 7, the ‘749 patent recites the system of claim 1, wherein the instructions, when executed by the processor, cause the processor to perform steps further comprising (column 24, lines 31-34): training a machine learning algorithm based on the plurality of routes followed by one or more vehicles assigned to travel between the starting location and the destination in one or more past instances (column 24, lines 32-35); and implementing the machine learning algorithm to identify the selected route among the plurality of routes for a current instance to travel between the starting location and the destination (column 24, lines 36-39).
Regarding claim 8, the ‘749 patent recites the system of claim 7, wherein each route is formed of a plurality of waypoints, wherein the instructions, when executed by the processor, cause the processor to perform steps further comprising (column 24, lines 40-43): calculating, using the machine learning algorithm, a probability for each route among the plurality of routes, wherein the probability represents a likelihood that the route will be followed by a vehicle based on the historical route information, calculating the probability for each route further comprising (column 24, lines 44-49): calculating a probability at each waypoint, and aggregating probabilities of the plurality of waypoints forming the route (column 24, lines 50-51); and selecting the route with highest probability as the selected route (column 24, lines 52-53).
Regarding claim 9, the ‘749 patent recites the system of claim 8, wherein calculating the probability for each route further comprises: for each waypoint along the route, determining a ratio of datapoints in the historical route information where the waypoint was connected to a subsequent waypoint along the route by a total count of all available datapoints where the waypoint was connected to a subsequent waypoint along all routes incorporating the waypoint (column 24, lines 54-62).
Regarding claim 10, the ‘749 patent recites the system of claim 1, wherein identifying the time duration at the waypoint associated with the starting location is adjusted in view of an embarkation data determined based on historical route information to account for time spent on a passenger boarding a vehicle, wherein identifying the time duration at the waypoint associated with the destination is adjusted in view of a disembarkation data determined based on historical route information to account for time spent on one or more passengers exiting the vehicle (column 24, line 63 through column 25 line 4).
Regarding claim 11, the ‘749 patent recites a method, comprising: identifying, by a server computer, a plurality of routes connecting a start location and a destination among historical route information collected over a period of time from one or more vehicles, wherein the plurality of routes are traveled by the one or more vehicles and reported to the server computer during the period of time to get from the start location to the destination (column 25, lines 17-23); determining, by the server computer, an estimated time for arrival associated with a selected route among the plurality of routes, wherein the selected route includes a plurality of waypoints, determining comprising: identifying a time duration for each waypoint (column 25, line 31); determining an adjustment factor for at least one waypoint (column 25, lines 32-33); determining an augmented time duration based on the adjustment factor and the time duration associated with the at least one waypoint (column 25, lines 34-36); determining the estimated time for arrival based on at least the time duration for each waypoint and the augmented time duration for the at least one waypoint (column 25, lines 29-30, 34-37); and outputting, by the server computer, the estimated time of arrival for the selected route.
Regarding claim 12, the ‘749 patent recites the method of claim 11, wherein the adjustment factor is based on at least one of a time of day for servicing the selected route, the day for servicing the selected route, a road condition along the selected route, traffic data, weather data, or local events data (column 25, lines 41-45).
Regarding claim 13, the ‘749 patent recites the method of claim 11, wherein the adjustment factor is determined based on the historical route information to add or subtract from the time duration for each waypoint, wherein the time duration is a baseline time duration which is obtained from the historical route information (column 25, lines 46-50).
Regarding claim 14, the ‘749 patent recites the method of claim 11, further comprising: receiving a routing update from a vehicle servicing the selected route, wherein the routing update includes a new waypoint that was not a part of the selected route; updating a route selection algorithm based on the routing update; and determining a new estimated time of arrival based on the waypoints identified in the routing update (column 25, lines 51-58).
Regarding claim 15, the ‘749 patent recites the method of claim 11, further comprising: training a machine learning algorithm based on the plurality of routes followed by one or more vehicles assigned to travel between the starting location and the destination in one or more past instances; and implementing the machine learning algorithm to identify the selected route among the plurality of routes for a current instance to travel between the starting location and the destination (column 25, lines 59-67).
Regarding claim 16, the ‘749 patent recites the method of claim 15, wherein each route is formed of a plurality of waypoints, the method further comprising: calculating, using the machine learning algorithm, a probability for each route among the plurality of routes, wherein the probability represents a likelihood that the route will be followed by a vehicle based on the historical route information, calculating the probability for each route further comprising: calculating a probability at each waypoint, and aggregating probabilities of the plurality of waypoints forming the route; and selecting the route with highest probability as the selected route (column 26, lines 1-13).
Regarding claim 17, the ‘749 patent recites the method of claim 16, wherein calculating the probability for each route further comprises: for each waypoint along the route, determining a ratio of datapoints in the historical route information where the waypoint was connected to a subsequent waypoint along the route by a total count of all available datapoints where the waypoint was connected to a subsequent waypoint along all routes incorporating the waypoint (column 26, lines 14-22).
Regarding claim 18, the ‘749 patent recites the method of claim 11, wherein identifying the time duration at the waypoint associated with the starting location is adjusted in view of an embarkation data determined based on historical route information to account for time spent on a passenger boarding a vehicle, wherein identifying the time duration at the waypoint associated with the destination is adjusted in view of a disembarkation data determined based on historical route information to account for time spent on one or more passengers exiting the vehicle (column 26, lines 23-32).
Regarding claim 19, the ‘749 patent recites a non-transitory computer-readable medium storing instructions that, when executed on a server computer, cause the server computer to perform steps comprising (column 26, lines 33-35): identifying a plurality of routes connecting a start location and a destination among historical route information collected over a period of time from one or more vehicles, wherein the plurality of routes are traveled by the one or more vehicles and reported to the server computer during the period of time to get from the start location to the destination (column 26, lines 40-46); determining an estimated time for arrival associated with a selected route among the plurality of routes, wherein the selected route includes a plurality of waypoints (column 26, lines 50-52), determining comprising: identifying a time duration for each waypoint (column 26, line 54); determining an adjustment factor for at least one waypoint (column 26, lines 55-56); determining an augmented time duration based on the adjustment factor and the time duration associated with the at least one waypoint (column 26, lines 57-61); determining the estimated time for arrival based on at least the time duration for each waypoint and the augmented time duration for the at least one waypoint (column 26, lines 60-61); and outputting the estimated time of arrival for the selected route (column 26, lines 62-63).
Regarding claim 20, the ‘749 patent recites the non-transitory computer-readable medium of claim 19, wherein the instructions, when executed on the server computer, further cause the server computer to perform steps comprising: receiving a routing update from a vehicle servicing the selected route, wherein the routing update includes a new waypoint that was not a part of the selected route; updating a route selection algorithm based on the routing update; and determining a new estimated time of arrival based on the waypoints identified in the routing update (column 26, line 1 through column 27, line 7).
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-6, 10-14 and 18-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Regarding Claims 1, 11 and 19:
Claim 1 recites: “A system, comprising: a server computer comprising a processor and a memory storing instructions that, when executed by the processor, cause the processor to perform steps comprising: identifying a plurality of routes connecting a start location and a destination among historical route information collected over a period of time from one or more vehicles, wherein the plurality of routes are traveled by the one or more vehicles and reported to the server computer during the period of time to get from the start location to the destination; determining an estimated time for arrival associated with a selected route among the plurality of routes, wherein the selected route includes a plurality of waypoints, determining comprising: identifying a time duration for each waypoint; determining an adjustment factor for at least one waypoint; determining an augmented time duration based on the adjustment factor and the time duration associated with the at least one waypoint; determining the estimated time for arrival based on at least the time duration for each waypoint and the augmented time duration for the at least one waypoint; and outputting the estimated time of arrival for the selected route.”
Claim 11 recites: “A method, comprising: identifying, by a server computer, a plurality of routes connecting a start location and a destination among historical route information collected over a period of time from one or more vehicles, wherein the plurality of routes are traveled by the one or more vehicles and reported to the server computer during the period of time to get from the start location to the destination; determining, by the server computer, an estimated time for arrival associated with a selected route among the plurality of routes, wherein the selected route includes a plurality of waypoints, determining comprising: identifying a time duration for each waypoint; determining an adjustment factor for at least one waypoint; determining an augmented time duration based on the adjustment factor and the time duration associated with the at least one waypoint; determining the estimated time for arrival based on at least the time duration for each waypoint and the augmented time duration for the at least one waypoint; and outputting, by the server computer, the estimated time of arrival for the selected route.”
Claim 19 recites: “A non-transitory computer-readable medium storing instructions that, when executed on a server computer, cause the server computer to perform steps comprising: identifying a plurality of routes connecting a start location and a destination among historical route information collected over a period of time from one or more vehicles, wherein the plurality of routes are traveled by the one or more vehicles and reported to the server computer during the period of time to get from the start location to the destination; determining an estimated time for arrival associated with a selected route among the plurality of routes, wherein the selected route includes a plurality of waypoints, determining comprising: identifying a time duration for each waypoint; determining an adjustment factor for at least one waypoint; determining an augmented time duration based on the adjustment factor and the time duration associated with the at least one waypoint; determining the estimated time for arrival based on at least the time duration for each waypoint and the augmented time duration for the at least one waypoint; and outputting the estimated time of arrival for the selected route.”
Claim analysis via 2019 PEG
Step 1: Statutory Category – Yes
Claim 1 recites a system comprising a server. Thus, the claim falls within one of the four statutory categories because the claim is directed to a machine. See MPEP 2106.03(I).
Claim 11 recites a method including at least one step. The claim falls within one of the four statutory categories because the claim is to a process. See MPEP 2106.03(I).
Claim 19 recites a non-transitory computer readable medium. Thus, the claim falls within one of the four statutory categories because the claim is to a manufacture. See MPEP 2106.03(I).
Step 2A Prong One Evaluation: Judicial Exception – Yes – Mental processes
Claims are to be analyzed to determine whether it recites subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) mental processes, and/or c) certain methods of organizing human activity.
The Office submits that the foregoing bolded limitation(s) constitutes judicial exceptions in terms of “mental processes” because under its broadest reasonable interpretation, each claim covers performance of the limitation in the human mind.
Each of the claims 1, 11 and 19 recite the limitations requiring “identifying a plurality of routes connecting a start location and a destination…” and “determining an estimated time for arrival associated with a selected route among the plurality of routes, wherein the selected route includes a plurality of waypoints, determining comprising: identifying a time duration for each waypoint; determining an adjustment factor for at least one waypoint; determining an augmented time duration based on the adjustment factor and the time duration associated with the at least one waypoint; determining the estimated time for arrival based on at least the time duration for each waypoint and the augmented time duration for the at least one waypoint”. The limitations reciting identifying…, determining…., identifying…, determining…, determining… and determining…, as drafted cover performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting generic computer components, nothing in the claims precludes the steps from being performed in the mind. For example, but for the “server” language the “identifying, determining, identifying, determining, determining and determining” encompasses a human performing the steps in his mind. If a claim limitation, under the broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, the limitation falls within the “Mental Process” grouping of abstract ideas. Accordingly, claims 1, 11 and 19 are directed to an abstract idea.
Step 2A Prong Two Evaluation: Practical Application - No
The claims are evaluated whether as a whole they integrate the recited judicial exception into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the foregoing underlined portions are the “additional limitations” while the foregoing bolded portions continue to represent the “abstract idea”).
Claim 1 recites additional elements/steps requiring “a server computer comprising a processor and a memory storing instructions that, when executed by the processor, cause the processor to perform steps” and “…among historical route information collected over a period of time from one or more vehicles, wherein the plurality of routes are traveled by the one or more vehicles and reported to the server computer during the period of time to get from the start location to the destination” and “outputting the estimated time of arrival for the selected route.”
Claim 11 recites additional elements/steps requiring “A non-transitory computer-readable medium storing instructions that, when executed on a server computer, cause the server computer to perform steps comprising” and “among historical route information collected over a period of time from one or more vehicles, wherein the plurality of routes are traveled by the one or more vehicles and reported to the server computer during the period of time to get from the start location to the destination;” and “outputting, by the server computer, the estimated time of arrival for the selected route.”
Claim 19 recites additional elements/steps requiring “by a server” and “among historical route information collected over a period of time from one or more vehicles, wherein the plurality of routes are traveled by the one or more vehicles and reported to the server computer during the period of time to get from the start location to the destination” and “outputting the estimated time of arrival for the selected route.”
The “server” limitations merely describe how to generally “apply” the otherwise mental judgements in a generic or general purpose sever environment. The server is recited at a high level of generality and it merely automates the “identifying, determining, identifying, determining, determining and determining” steps. See MPEP 2106.04(d)(I).
The limitations requiring collection of historical route information are recited at a high level of generality (i.e., as a general means of gathering the historical route information for use with the abstract idea steps.) and amounts to mere data gathering which is a form of insignificant extra-solution activity. The outputting steps are also recited at a high level of generality (i.e., as a general means of outputting the estimate from the abstract idea steps), and amounts to mere data outputting, which is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Accordingly, the claims are directed to an abstract idea.
Step 2B Evaluation: Inventive concept - No
The claim(s) is evaluated whether each claim as a whole amount to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A Prong Two, the additional elements in the claims amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. As discussed with respect to Step 2A Prong Two, for the additional elements in the claims in which the “server” is merely a tool being used to perform the abstract idea, the same analysis applies here as above. Merely using a computer as a tool to perform an abstract idea cannot integrate a judicial exception into a practical application or provide an inventive concept.
Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the data gathering and outputting steps were considered to be insignificant extra-solution activity in Step 2A, and thus they are re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field.
The specification does not provide any indication that the server is anything other than a conventional computer equipment. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). Further, the Federal Circuit in Trading Techs. Int’l v. IBG LLC, 921 F.3d 1084, 1093 (Fed. Cir. 2019), and Intellectual Ventures I LLC v. Erie Indemnity Co., 850 F.3d 1315, 1331 (Fed. Cir. 2017), for example, indicated that the mere displaying (i.e., outputting) of data is a well understood, routine, and conventional function. Claims 1, 11 and 19 are not patent eligible.
Dependent claims 2-6, 10, 12-14, 18 and 20 do not recite any further limitations that cause the claims to be patent eligible via practical integration. Rather, the limitations of the dependent claims are directed toward additional elements that perform insignificant extra solution activity and to not integrate the judicial exception into a practical application. Therefore, dependent claims 2-6, 10, 12-14, 18 and 20 are not patent eligible under the same rational as provided for the rejection of independent claims 1, 11 and 19.
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.
Claim(s) 1, 3-5, 11-13 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over O’Neill (US 2008/0234927 A1) in view of Fino (US 2014/0129121 A1).
Regarding claim 1, O’Neill teaches a system, comprising: a server (Fig. 1, element 105) computer comprising a processor and a memory storing instructions that, when executed by the processor (paragraph 0006-0007, 0026), cause the processor to perform steps comprising: identifying (Fig. 2, step 215) a plurality of routes (Figs. 1, element 185) connecting a start location and a destination (Fig. 1, element 170 via Fig. 2, step 205) among historical route information (Fig. 1, element 120) collected over a period of time from one or more vehicles (paragraph 0007, 0010, 0028, 0030-0031), wherein the plurality of routes are traveled by the one or more vehicles and reported to the server computer (Fig. 1, elements 115, 120, 125, 130) during the period of time (various times of day) to get from the start location to the destination (paragraphs 0009-0017); determining (Fig. 2, step 220) an estimated time for arrival (Fig. 1, element 190, normal and unadjusted) associated with a selected route (Fig. 1, element 185, unadjusted route via Fig. 2, step 215) among the plurality of routes (paragraphs 0007, 0031), wherein the selected route implicitly includes a plurality of waypoints, [the] determining comprising: identifying a time duration for each waypoint (travel times for each segment; paragraph 0001-0002, 0031); determining (Fig. 2, step 225) an adjustment factor (Fig., 1, element 195) for at least one waypoint (paragraph 0006, 0013-0018, 0032-0034); determining (Fig. 2, step 230) an augmented time duration based on the adjustment factor and the time duration associated with the at least one waypoint (paragraph 0032-0033); determining (Fig. 2, step 230) the estimated time for arrival (Fig. 1, element 190) based on at least the time duration for each waypoint and the augmented time duration for the at least one waypoint (paragraphs 0032-0034); and outputting (Fig. 2, step 240) the estimated time of arrival for the selected route (paragraph 0036).
O’Neill is silent regarding identifying “a plurality of routes” connecting a start location and a destination. Fino teaches a technique for identifying a plurality of routes from a start location to a destination (Fig. 6, step 654; paragraph 0065). It would have been obvious to a person having ordinary skill in the art prior to Applicant’s effective filing date to apply the well-known technique taught by Fino to the prior art system taught by O’Neill. That is, it would have been obvious to configure the prior art system taught by O’Neill to identify a plurality of routes connecting start location and destination 170 by applying the well-known technique taught by Fino. Application of the well-known technique to the prior art system would have been obvious because such application would have been well within the level of skill of the person having ordinary skill in the art and because such application would have yielded predictable results. The predictable results including the system being configured to identify a plurality of routes from the start location to destination 170 and to select a route from the plurality of routes at step 215.
Regarding claim 3, O’Neill teaches the system of claim 1, wherein the adjustment factor is based on at least one of a time of day (Table 2, Time) for servicing the selected route, the day for servicing the selected route, a road condition along the selected route (Fig. 1, element 130), traffic data (Fig. 1, element 125), weather data (Fig. 1, element 115), or local events data (paragraph 0009-0017).
Regarding claim 4, O’Neill teaches the system of claim 1, wherein the adjustment factor is determined based on the historical route information to add (Table 2, Factor) or subtract from the time duration for each waypoint (paragraphs 0013-0014).
Regarding claim 5, O’Neill teaches the system of claim 1, wherein the time duration is a baseline (prior to adjusting for weather 115, current traffic 125 and construction 130) time duration which is obtained from the historical route information (paragraphs 0010, 0013-0014, 0031).
Regarding claim 11, O’Neill teaches a method, comprising: identifying (Fig. 2, step 215), by a server computer (Fig. 1, element 105), a plurality of routes connecting a start location and a destination (Fig. 1, element 170 via Fig. 2, step 205) among historical route information (Fig. 1, element 120) collected over a period of time from one or more vehicles (paragraph 0006-0007, 0010, 0026, 0028, 0030-0031), wherein the plurality of routes are traveled by the one or more vehicles and reported to the server computer (Fig. 1, elements 115, 120, 125, 130) during the period of time to get from the start location to the destination (paragraphs 0009-0017); determining (Fig. 2, step 220), by the server computer, an estimated time for arrival (Fig. 1, element 190, normal and unadjusted) associated with a selected route (Fig. 1, element 185, unadjusted route via Fig. 2, step 215) among the plurality of routes (paragraphs 0007, 0031), wherein the selected route implicitly includes a plurality of waypoints, determining comprising: identifying a time duration for each waypoint (travel times for each segment; paragraph 0001-0002, 0031); determining (Fig. 2, step 225) an adjustment factor (Fig., 1, element 195) for at least one waypoint (paragraph 0006, 0013-0018, 0032-0034); determining (Fig. 2, step 230) an augmented time duration based on the adjustment factor and the time duration associated with the at least one waypoint (paragraph 0032-0033); determining (Fig. 2, step 230) the estimated time for arrival (Fig. 1, element 190) based on at least the time duration for each waypoint and the augmented time duration for the at least one waypoint (paragraphs 0032-0034); and outputting (Fig. 2, step 240), by the server computer, the estimated time of arrival for the selected route (paragraph 0036).
O’Neill is silent regarding identifying “a plurality of routes” connecting a start location and a destination. Fino teaches a technique for identifying a plurality of routes from a start location to a destination (Fig. 6, step 654; paragraph 0065). It would have been obvious to a person having ordinary skill in the art prior to Applicant’s effective filing date to apply the well-known technique taught by Fino to the prior art method taught by O’Neill. That is, it would have been obvious to configure the prior art method to identify a plurality of routes connecting start location and destination 170 by applying the well-known technique taught by Fino to the prior art method taught by O’Neill. Application of the well-known technique to the prior art system would have been obvious because such application would have been well within the level of skill of the person having ordinary skill in the art and because such application would have yielded predictable results. The predictable results including: the method being configured to identify a plurality of routes from the start location to destination 170 and to select a route from among the plurality of routes at step 215.
Regarding claim 12, O’Neill teaches the method of claim 11, wherein the adjustment factor is based on at least one of a time of day (Table 2, Time) for servicing the selected route, the day for servicing the selected route, a road condition along the selected route (Fig. 1, element 130), traffic data (Fig. 1, element 125), weather data (Fig. 1, element 115), or local events data (paragraph 0009-0017).
Regarding claim 13, O’Neill teaches the method of claim 11, wherein the adjustment factor is determined based on the historical route information to add (Table 2, Factor) or subtract from the time duration for each waypoint, wherein the time duration is a baseline (prior to adjusting for weather 115, current traffic 125 and construction 130) time duration which is obtained from the historical route information (paragraph 0010, 0013-0014, 0031).
Regarding claim 19, O’Neill teaches a non-transitory computer-readable medium storing instructions that, when executed on a server computer (Fig. 1, element 105; paragraph 0006-0007, 0026), cause the server computer to perform steps comprising: identifying (Fig. 2, step 215) a plurality of routes (Figs. 1, element 185) connecting a start location and a destination (Fig. 1, element 170 via Fig. 2, step 205) among historical route information (Fig. 1, element 120) collected over a period of time from one or more vehicles (paragraph 0007, 0010, 0028, 0030-0031), wherein the plurality of routes are traveled by the one or more vehicles and reported to the server computer (Fig. 1, elements 115, 120, 125, 130) during the period of time (various times of day) to get from the start location to the destination (paragraphs 0009-0017); determining (Fig. 2, step 220) an estimated time for arrival (Fig. 1, element 190, normal and unadjusted) associated with a selected route (Fig. 1, element 185, unadjusted route via Fig. 2, step 215) among the plurality of routes (paragraphs 0007, 0031), wherein the selected route implicitly includes a plurality of waypoints, [the] determining comprising: identifying a time duration for each waypoint (travel times for each segment; paragraph 0001-0002, 0031), determining (Fig. 2, step 225) an adjustment factor (Fig., 1, element 195) for at least one waypoint (paragraph 0006, 0013-0018, 0032-0034); determining (Fig. 2, step 230) an augmented time duration based on the adjustment factor and the time duration associated with the at least one waypoint (paragraph 0032-0033); determining (Fig. 2, step 230) the estimated time for arrival (Fig. 1, element 190) based on at least the time duration for each waypoint and the augmented time duration for the at least one waypoint (paragraphs 0032-0034); and outputting (Fig. 2, step 240) the estimated time of arrival for the selected route (paragraph 0036).
O’Neill is silent regarding identifying “a plurality of routes” connecting a start location and a destination. Fino teaches a technique for identifying a plurality of routes from a start location to a destination (Fig. 6, step 654; paragraph 0065). It would have been obvious to a person having ordinary skill in the art prior to Applicant’s effective filing date to apply the well-known technique taught by Fino to the prior art system taught by O’Neill. That is, it would have been obvious to configure the prior art system taught by O’Neill to identify a plurality of routes connecting start location and destination 170 by applying the well-known technique taught by Fino. Application of the well-known technique to the prior art system would have been obvious because such application would have been well within the level of skill of the person having ordinary skill in the art and because such application would have yielded predictable results. The predictable results including the system being configured to identify a plurality of routes from the start location to destination 170 and to select a route from the plurality of routes at step 215.
Claim(s) 6, 14 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over O’Neill and Fico as applied to claims 1, 11 and 19 above, and further in view of Horihata et al. (US 2016/0091324 A1, hereinafter referred to as “Horihata”).
Regarding claims 6, 14 and 20, O’Neill and Fico teach the combination as applied of claims 1, 11 and 19 above. The combination of O’Neill and Fico are silent regarding the processor to perform steps further comprising: receiving a routing update from a vehicle servicing the selected route, wherein the routing update includes a new waypoint that was not a part of the selected route;
Horihata teaches a technique for receiving (Fig. 2, step S101) at a server (Fig. 1, element 2) a routing update from a vehicle (Fig. 1, element 1) servicing a route, wherein the routing update includes a new waypoint (Fig. 3, element T1, T2, T3, T4) that was not part of a selected route (Fig. 3, element R1, R2); and updating (update with route R3, Figs. 4-5 and 8, element R3 via Fig. 2, step S102) a route selection database (via Fig. 1, element 22, 23) based on the routing update (paragraph 0024, 0033-0049, 0067). It would have been obvious to a person having ordinary skill in the art prior to Applicant’s effective filing date to apply the well-known technique taught by Horihata to the prior art combination taught by O’Neill and Fico. That is, it would have been obvious to configure the prior art combination to update the server with the routing update by applying the well-known technique taught by Horihata. Application of the well-known technique to the prior art combination would have been obvious because scuh application would have been well within the level of skill of the person having ordinary skill in the art and because such combination would have yielded predictable results. The predictable results including: the combination being further configured for receiving a routing update from a vehicle servicing the selected route, wherein the routing update includes a new waypoint that was not a part of the selected route; updating a route selection algorithm based on the routing update; and determining a new estimated time of arrival based on the waypoints identified in the routing update.
Claim(s) 7 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over O’Neill and Fico as applied to claims 1 and 11 above, and further in view of Fu et al. (US 2019/0226855 A1, hereinafter referred to as “Fu”).
Regarding claims 7 and 15, O’Neill and Fico teach the combination as applied to claims 1 and 11 above. However, O’Neill and Fico are silent regarding training a machine learning algorithm based on the plurality of routes followed by one or more vehicles assigned to travel between the starting location and the destination in one or more past instances; and implementing the machine learning algorithm to identify the selected route among the plurality of routes for a current instance to travel between the starting location and the destination.
Fu teaches a technique for training (Fig. 4, steps 401-402, 452) a machine learning algorithm based on a plurality of routes followed by one or more vehicles (Fig. 2, element 111) assigned to travel between a starting location and a destination in one or more past instances; and implementing (Fig. 4A, step 404, 484) the machine learning algorithm to identify a route (paragraphs 0065-0072).
It would have been obvious to a person having ordinary skill in the art prior to Applicant’s effective filing date to apply the well-known machine learning technique taught by Fu to the prior art combination taught by O’Neill and Fico. Application of the well-known machine learning technique to the prior art combination would have been obvious because such application would have been well within the level of skill of the person having ordinary skill in the art and because the results of such application would have been predictable. The predictable results including: the combination being configured for training a machine learning algorithm based on the plurality of routes followed by one or more vehicles assigned to travel between the starting location and the destination in one or more past instances; and implementing the machine learning algorithm to identify the selected route among the plurality of routes for a current instance to travel between the starting location and the destination.
Allowable Subject Matter
Claims 2, 8-10 and 16-18 are objected to as being dependent upon a rejected base claim, but would be allowable with Terminal Disclaimer and if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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/Dale Moyer/Primary Examiner, Art Unit 3656