DETAILED ACTION
This non-final action is in response to the request for continued examination (RCE) and amendment, filed 25 November 2025, which was in response to the final action, dated 5 September 2025.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 25 November 2025 has been entered.
Response to RCE and Amendments
Claims 1, 5-8, 10-12, 14-15, 36-38 are pending. Claims 1, 14 and 15 have been amended, claims 9, 13 and 34 have been canceled.
With regard to the 35 U.S.C. 101 rejection of independent claims 1, 14 and 15 (pgs. 6-17, Final), Applicant contends that the independent claims 1, 14 and 15 are eligible because: (1) they are directed to a specific technical solution in the field of navigational systems (pgs. 9-10, Reply); (2) the claims require physical implementation by machines (pgs. 10, Reply); (3) every core step in the claims is explicitly tied to a specific structure or machine or inter-machine action, and thus is impossible to be performed in the human mind or a generic computer (pgs. 10-11, Reply); and (4) the claims satisfy the machine-or-transformation test and the “navigational system”, “route trace storage” and “parameter generation module” are not generic computers (pgs. 11-12). The 35 U.S.C. 101 analysis was updated below based on the amended claims. Applicants contentions are unpersuasive for the following reasons.
With regard to contention (1), per MPEP 2106.04(d)(1) and 2106.05(a), in determining integration into a practical application when the claimed invention improves the functioning of a computer or improves another technology or technical field, the specification must set forth an improvement in technology and the claim itself must reflect the disclosed improvement. Here, the examiner finds that applicant’s contended improvement and the recitations in the claims do not improve the functioning of a computer or another technology because the recitations merely recite abstract ideas and data processing, as discussed below.
Applicant further contends that the steps of “selecting road segments by a navigation system, transmitting a route trace from a storage to a module, and producing a signal and sending it through an interface to the vehicle to provide guidance”, cannot be performed in the human mind. As further discussed below the step of “selecting road segments” is abstract and the steps of “transmitting” and “providing” are insignificant extra solution activity. Further, although applicant contends the problem the application is attempting to solve is providing more accurate and relevant real-time route guidance, the claims do not recite temporal (i.e. real-time) or spatial limitations that would explicitly indicate that it cannot be performed in the mind.
With regard to contention (2) Applicant points to no authority in the MPEP supporting this contention. As discussed below, although the claims require physical implementation by machines (i.e. a navigational system, a route trace storage, a parameter regeneration module, communication links, interfaces), those recitations are insufficient to render the claims eligible. The nominal recitation that the “selecting”, “updating”, “detecting”, “determining” and “generating” steps, are executed by the navigational system, route trace storage and parameter generation modules does not take these limitations out of the mental process grouping.
With regard to contention (3) applicant reiterates contention (2) combined with the further contention that the steps of “selecting” (by a navigational system), “transmitting” (from “a route trace storage” to “a parameter generation module” over “a first communication link”), “updating” (parameter generation module), “transmitting” (from “the parameter generation module” to the “navigational system” over “second communication link”), “producing a signal” (by the navigational system” ), and “sending the signal” (via “an interface to the vehicle”) cannot be performed by a human or in a human mind. The “updating” step has been addressed above. As discussed below, with regard to the Step 2A (prong 2) analysis, the “transmitting”, “producing a signal” and “sending the signal” steps were determined to further limit the abstract idea without further integrated the abstract idea into practical application. The steps were determined to be insignificant extra solution activity, per MPEP 2106.05(g), as discussed below.
Further, the “parameter generation module”, “a route trace storage”, “navigation system”, “first communication link”, “a second communication link” and “interface to the vehicle” additional elements were found not to be sufficient to amount to significantly more than the judicial exception because they fail to integrate the exception into practical application because the abstract idea is merely implemented by a computer. These element merely describe how to generally apply the otherwise mental judgements in a generic or general purpose computing environment, as discussed below.
With regard to contention (4) see the reply to contention (3) with regard to noting that the additional elements “parameter generation module”, “a route trace storage”, “navigation system” perform the recited steps via computers. These additional elements are recited at a high level of generality and merely automate the transmitting, sending, receiving and providing steps. As further discussed below, the well-understood, routine, conventional activity of transmitting, sending, receiving and providing data are fundamental activities performed by computers such as the recited additional elements above, operating with data such as the navigation systems recited in claims 1, 14 and 15. Applicant has not indicated nor has the specification provided any indication that the transmitting, sending, receiving and providing data are performed by anything other than a conventional computer.
Accordingly, the 35 U.S.C. 101 rejection of claims 1, 5-8, 10-12, 14-15 and 36-38 has been maintained, as discussed below. The rejection of canceled claims 9, 13 and 34 have been rendered moot by their cancelation.
With regard to the 35 U.S.C. 103 rejection of claims 1, 14 and 15 (pgs. 17-49, Final), applicant’s amendments necessitated additional searching and consideration of new grounds of rejection. Accordingly, the new grounds of rejection under 35 U.S.C. 103 are: claims 1, 5, 8, 10-12, 14 and 15 in view of Cohen, Tennent, Guedalia and Golding; claims 6, and 7 in view of Cohen, Tennent, Guedalia, Golding and Jing; claims 36 and 37 in view of Cohen, Tennent, Guedalia, Golding and N; and claim 38 in view of Cohen, Tennent, Guedalia, Golding and Pedersen, as discussed below.
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, 5-8, 10-12, 14, 15 and 36-38 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
In January, 2019 (updated October 2019), the USPTO released new examination guidelines setting forth a two-step inquiry for determining whether a claim is directed to non-statutory subject matter. According to the guidelines, a claim is directed to non-statutory subject matter if:
• STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
• STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
o STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
o STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
o STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claims 1, 14 and 15 are directed toward non-statutory subject matter as shown below.
STEP 1: Do claims 1, 14 and 15 fall within one of the statutory categories? Yes, because claim 1 is directed toward a method, claim 14 is directed toward a system, and claim 15 is directed to a non-transitory computer-readable medium (a device), all of which fall within one of the statutory categories.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? Yes, claims 1, 14 and 15 are directed to abstract ideas.
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
1. Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
2. Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
3. Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
As per claim 1, 14, and 15, the method (claims 1) and system (claim 14) are mental processes that can be performed in the mind and, therefore, are abstract ideas. In particular, claims 1, 14 and 15 recite the abstract ideas:
“selecting, by a navigational system which is part or associated with a vehicle, road segments to generate a current recommended route between an initial location and a requested destination location based on an initial set of routing parameters” (claim 1, 14 and 15 ); ...
“updating, via the parameter generation module, an initial set of routing parameters of the navigational system based on attributes of the road segments of the previously travelled routes” (claims 1, 14 and 15); ...
“detecting a deviation from the current recommended route for which the navigational system is providing guidance” (claims 1, 14 and 15);
“determining a routing parameter update based on the attributes of the one or more road segments of the deviation,” (claims 1, 14 and 15) and
“generating, via the parameter generation module and based on the updated set of routing parameters, a route between a current location of the user and a requested destination location” (claims 1, 14, 15). These recitations merely consist of selecting road segments to generate a route from an initial location to a destination based on an initial set of routing parameters (i.e. a route from an initial location to a destination, based on route parameters), updating routing parameters based on the attributes of previously travelled routes, detecting a deviation from the current recommended route, determining a routing parameter update based on the attributes of one or more road segments of the deviation (the update being based on observations such as traffic, weather, type of segment), and generating updated routing parameters and a route between an initial location and the destination. This is equivalent to a person selecting road segments to generate a route, updating routing parameters based on the attributes (traffic, weather, road type, vehicle type, mode of transportation) of previously travelled routes, detecting (observing) a deviation from the current route, determining a routing parameter update based on the attributes of one or more road segments of the deviation and generating updated routing parameters and a route between an initial location and the destination. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same). As such, a person, updates routing parameters based on the attributes (traffic, weather, road type, vehicle type, mode of transportation) of previously travelled routes, and generating updated routing parameters and a route between an initial location and the destination. The mere nominal recitations that steps are executed for “a navigational system,” (claims 1 and 14), “a route trace storage” (claims , 14 and 15), and “a parameter generation module” (claims 1, 14, and 15), does not take the limitation out of the mental process grouping.
STEP 2A (PRONG 2): Do the claims recite additional elements that integrate the judicial exception into a practical application? No, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
• an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
• an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
• an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
• an additional element effects a transformation or reduction of a particular article to a different state or thing; and
• an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
• an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
• an additional element adds insignificant extra-solution activity to the judicial exception; and
• an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claims 1, 14 and 15 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into practical application. Claims 1, 14 and 15 further recite the additional elements:
“transmitting, from a route trace storage to a parameter generation module over a first communication link, a route trace of a previously travelled section of a current route of a user of the navigational system, the previously traveled section of the current route including a plurality of road segments,” (claim 1, 15),
“based on the generated route and the current location, producing a signal by the navigational system and sending the signal to an interface to the vehicle to provide navigational guidance to the user for following the generate route (claims 1, 15),
“the parameter guidance module receiving the route trace storage of the previously traveled section ... “ (claim 14);
“the navigation system receiving the updated set of routing parameter from the parameter generation module over a second communication link” (claim 14)’
“the navigation system using the generated route from the parameter generation module and the current location of the user by the navigational system to provide navigational guidance to the user for following the generated route” (claim 1, 14 and 15). These additional element further limits the abstract idea without integrating the abstract idea into practical application or significantly more. In particular, the “transmitting, from a route trace storage to a parameter generation module over a first communication link, a route trace “, “producing a signal”, “sending a signal”, “receiving route trace data”, “receiving the updated set of routing parameter” and “providing navigational guidance” steps are recited at a high level of generality (i.e., as a general means of gathering an electronic representation of previous traveled routes and navigation of current routes) and amount to mere data gathering, a form of insignificant extra-solution activity added to the judicial exception per MPEP 2106.05(g), because the steps characterize pre and post solution activity, such as an individual recalling previous routes and guiding oneself along the routes in the event of a deviation.
Claims 1, 14 and 15 still further include the additional elements “a parameter generation module”, “a route trace storage” “a navigational system”, “a first communication link”, “a second communication link” and “interface to the vehicle” (claim 1). These elements are not sufficient to amount to significantly more than the judicial exception because they fail to integrate the exception into practical application. The mere inclusion of instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea is indicative that the judicial exception has not been integrated into a practical application. In the instant case, the “parameter generation module”, “a route trace storage”, “navigation system”, “first communication link”, “a second communication link” and “interface to the vehicle” (claim 1) perform the steps, i.e. via computers. Thus, it is clear that the abstract idea is merely implemented on a computer, which is indicative of the abstract idea having not been integrated in the practical application. The “parameter generation module”, “navigational system,”, “route trace storage”, the “first communication link”, the “second communication link”, and the “interface to the vehicle” merely describes how to generally “apply” the otherwise metal judgements in a generic or general purpose computing environment. The navigational system, first communication link, second communication link and interface to the vehicle are recited at a high level of generality and merely automate the transmitting, sending, receiving, and providing steps.
STEP 2B: Do the claims recite additional elements that amount to significantly more than the judicial exception? No, claims 1, 14 and 15 do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
• adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
• simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Claims 1, 14 and 15 do not recite any specific limitation or combination of limitations that are well-understood, routine, conventional (WURC) activity in the field. Transmitting, sending, receiving, and providing data are fundamental, i.e. WURC, activities performed by systems, such as guidance systems, and computers operating with data such as the navigational systems recited in claims 1, 14 and 15. Further, applicant’s specification does not provide any indication that the obtaining or providing activities of the method are performed using anything other than a conventional computer. 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 performance of an action is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner.
Thus, since claims 1, 14 and 15 are: (a) directed toward abstract ideas; (b) do not recite additional elements that integrate the judicial exception into practical application; and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that claims 1, 14 and 15 are directed to non-statutory subject matter.
Dependent claims 5-8, 10-12, and 36-38 further limit the abstract idea without integrating the abstract idea into practical application or adding significantly more. For example, the additional elements in claims 6, 8 and 12 are further limitations that under their broadest reasonable interpretations are abstract using the analysis for independent claims 1 and 14. Further, the additional elements in claims 5, 7, 10-11, 34 and 36-38 are further limitations that under their broadest reasonable interpretations are limitations that limit the abstract idea without integrating it into practical application or significantly more.
As such, claims 1, 5-8, 10-12, 14-15 and 36-38 are rejected under 35 U.S.C. 101 as being drawn to an abstract idea without significantly more, and thus are ineligible.
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 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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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 non-obviousness.
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.
Claims 1, 5, 8, 10-12, 14 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Publication Number 2022/0187083 to Cohen et al. (hereafter Cohen) in view of U.S. Patent Publication Number 2017/0363433 to Tennent et al. (hereafter Tennent), U.S. Patent Publication Number 2014/0107816 to Guedalia et al. (hereafter Guedalia), and U.S. Patent Publication Number 2020/0109961 to Golding et al. (hereafter Golding).
As per claim 1, Cohen discloses [a] method of navigational guidance (see at least Cohen, Abstract), the method comprising:
selecting, by a navigational system which is part or associated with a vehicle, road segments to generate a current recommended route between an initial location and a requested destination location based on an initial set of routing parameters (see at least Cohen, [0038] disclosing that a user operates certain controls and/or installs certain applications to indicate that the server 104 may use his or her past routes data to determine the user's preferences regarding navigation, including a quantitative metric indicative of how the user assesses trade-offs between parameters of route segments; [0085] disclosing an example method for estimating the cost of a detour in terms of time or distance is discussed with reference to FIG. 8C and the schematic representation of several route options of FIG. 8B. According to an example scheme 830 of FIG. 8B, a user can travel between an origin 832 and a destination 834 directly (along route R.sub.D) or indirectly via one or more pick-up and drop-off locations (along route R.sub.I). In this example, the user can travel from the origin 832 to a pick-up location 842 to pick up a passenger, drop off the passenger at a drop-off location 844, and continue on to the destination 834. More generally, the indirect route R.sub.I can include any suitable number of pick-up locations and drop-off locations),
transmitting, from a route trace storage to a parameter generation module over a first communication link, a route trace of a previously travelled section of a current route of a user of the navigational system, by a parameter generation module, by a parameter generation module, the previously traveled section of the current route including a plurality of road segments (see at least Cohen, [0032] disclosing that communication system 100 that can implement these techniques is discussed first with reference to Fig. 1, followed by a discussion of example subsystems in which a trade-off controller generates and ranks candidate navigation routes, with reference to Figs. 2A and 2B; [0036]; [0037]; [0039] disclosing Fig. 2, showing smart phone 202 <navigation device> transmitting to server 208 <first communication link>; [0078] disclosing that At block 702 (Fig. 7), the routing engine 130 obtains route data indicative of routes previously traversed by the user <interpreted as route traces of previously traveled routes>. To this end, the routing engine can use the past routes database 144. For a certain route, the route data can specify the starting location, the destination, the sequence of route segments <interpreted as road segments> between the starting location and the destination, etc.), ... (1) ...
, ... (2) ... (3) ... ;
generating, via the parameter generation module and based on the updated set of routing parameters, a route between a current location of the user and a requested destination location (see at least Cohen, [0032]; [0041]; [0046] disclosing that the module 172 can estimate the financial cost of traversing several road segments associated with toll collection, or estimate the overall difficulty of route that includes several segments for which drivers reported difficulties in the past. The routing engine 170 generates navigation routes for specified starting locations and destinations using the trade-off controller 174 to constraint selection of navigation routes in view of a relationship between road parameters (e.g., time and difficulty, time and cost) <interpreted as updated routing parameters>; [0082]; [0094] disclosing that the user of the client computing device 102 can operate certain controls to allow the geographic application 160 to determine the user's current location); ... (4) ...
based on the generated route and the current location of the user, producing a signal by the navigational system and sending the signal via an interface to the vehicle to provide navigational guidance to the user for following the generated route (see at least Cohen, [0043] disclosing that a user operates certain controls and/or installs certain applications to indicate that the server 104 may use his or her past routes data to determine the user's preferences regarding navigation, including a quantitative metric indicative of how the user assesses trade-offs between parameters of route segments; [0045] disclosing that the server 104, the third-party road information provider 106, and the payment system 108 can interconnect via a network 110, which can be a wide area network such as the Internet, for example, and include wired and/or wireless communication links; [0046]; [0058] disclosing that the geographic data server 104 then can transmit the ranked candidate routes to a device, such as client computing device 102, for display to a user <interpreted as navigational guidance to the user for following the generated route>, for example by the geographic application 160) ... (5) ... , ... (6) ... , ... (7). But the difference between the claimed invention and Cohen is that Cohen does not explicitly teach the following limitation taught in Guedalia, a comparable method where is was known to:
(1) updating, by the parameter generation module, the initial set of routing parameters of the navigational system based on attributes of the road segments of the previously travelled routes (see at least Guedalia, [0033] disclosing that the server may identify a previously traveled route that is similar to a current route by comparing segments of a previously traveled route to the new current route; [0035] disclosing that a combination of point comparisons and segment comparisons of previous routes to new current positions may be used by the server to select a string of segments having distance and grade characteristics similar to a training route of a user of the electronic device. In the various embodiments, the previously traveled routes may be previously traveled routes of the user of the electronic device and/or previously traveled routes of one or more other individuals)
(2) wherein the updating is carried out in response to detecting a deviation from the current recommended route for which the navigational system is providing guidance (see at least Guedalia, [0029] disclosing that the server may be configured to identify paths and routes with characteristics similar to a user's previously traveled (i.e., biked, run, walked, etc.) training routes. The identification of similar routes may enable users to continue to pace themselves while in a different location or following an alternative route. And disclosing that when a server detects the user has deviated from a suggested route, the server may dynamically and in real time adjust to the change in direction and predict where the user may be heading and propose an alternative training route. In proposing the alternative training route, the server may take into account the user's normal training routines, previous training performances (e.g., times vs. distance and grade) and the training performances of other athletes in order to propose an alternative route consistent with the user's goals and preferences ; [0035] disclosing that a combination of point comparisons and segment comparisons of previous routes to new current positions may be used by the server to select a string of segments having distance and grade characteristics similar to a training route of a user of the electronic device. In the various embodiments, the previously traveled routes may be previously traveled routes of the user of the electronic device and/or previously traveled routes of one or more other individuals; [0062] disclosing that the server may compare the GPS coordinates of the series of real-time positions to the GPS coordinates of the previously identified string of segments to determine whether the GPS coordinates match. GPS coordinates that may not match may indicate the user of the electronic training device may have deviated from a previously identified route of training segments. In this manner, the server may recognize that a new current location of the electronic training device does not correspond to the previously identified string of segments);
(3) the step of updating comprises determining a routing parameter update based on the attributes of the one or more road segments of the deviation (see at least Guedalia, [0035] disclosing that a combination of point comparisons and segment comparisons of previous routes to new current positions may be used by the server to select a string of segments having distance and grade characteristics similar to a training route of a user of the electronic device. In the various embodiments, the previously traveled routes may be previously traveled routes of the user of the electronic device and/or previously traveled routes of one or more other individuals),
(5) wherein the previously traveled section differs from the respective recommended route by one or more deviation road segments (see at least Guedalia, [0033] disclosing that the server may assign values to each segment of the previously traveled routes and the current route based on characteristics, such as grade, and may compare the difference between the values of each previously traveled route segment to the values of each current route segment. The server may determine that the previously traveled route with the overall least amount of difference between the values of its respective segments and the segments of the current route is most similar to the new current route ; [0035]); and
(6) wherein the previously traveled section differs from the respective recommended route by one or more deviation road segments (see at least Guedalia, [0033]; [0035]). But the difference between the claimed invention and the combination of Cohen and Guedalia is that the combination does not explicitly teach the following limitation taught in Tennent, a comparable method where it was known to:
(4) using the generated route, from the parameter generation module and based on the generated route and a current location of the user by the navigation system to provide navigational guidance to the user for following the generated route (see at least Tennent, [0006]; [0033] disclosing that user action may trigger a request for a trip cost determination to be provided (e.g., transmitted via a network) to a broker apparatus 10. The broker apparatus 10 may determine and/or identify one or more cost model parameters. For example, the cost model parameters may comprise current and/or predicted real-word conditions (e.g., weather, driving, and/or traffic conditions) at the user's current location and/or one or more locations along a route the user is expected to travel along; [0072] disclosing that geographic data is compiled (such as into a platform specification format (PSF) format) to organize and/or configure the data for performing navigation-related functions and/or services, such as route calculation, route guidance, map display, speed calculation, distance and travel time functions, and other functions). But, the difference between the claimed invention and Cohen as modified by Guedalia and Tennent is that neither Cohen, Guedalia nor Tennent explicitly teach the following limitations taught in Golding, a comparable method where is was known to:
(7) wherein the routing parameter update includes a weighted combination of the road attributes of the difference (see at least Golding, [0096] disclosing that with, with regard to the method in Fig. 4a and 4b, computing 440 a value of the target attribute based on the conditional variant model having highest probability. In one particular embodiment, once probabilities have been assigned to each conditional variant, the expected value of the attribute for a candidate route can be calculated as a weighted average (e.g., sum over the conditional variants, and collect the probability of the ith conditional variant multiplied by the attribute value predicted by the ith conditional variant). This yields the value for the attribute as predicted by the combination of all of the conditional variants of the model for the attribute. The method may further include determining 445 if there are more attribute; [0098] disclosing that the method continues with computing 460 a desirability score for each candidate route, using the attribute weights and attribute values computed for that route, as previously explained (e.g., Score.sub.r=SUM w.sub.i x.sub.i). The method continues with sorting 465 the candidate routes based on their desirability scores, and providing 470 the top n high scoring routes for user selection (which may include all or a subset of the candidate routes). The user can preview the scored routes via a user interface, if so desired. The method continues with receiving 475 a selected route from the user, and then determining 480 if the attribute weights need to be adjusted based on that user selection. If so, the method continues with adjusting 485 the attribute weights based on the user selection, as previously explained).
Cohen, Tennent, Guedalia and Gold are analogous art to claim 1 because they are in the same field of navigational guidance and determining routing restrictions. Cohen relates to a technique for generating navigation routes includes obtaining route data indicative of multiple routes between respective starting locations and destinations, previously traversed by a user (see at least Cohen, Abstract). Tennent relates to determining cost model parameters for determining a usage-based cost for a trip and providing a user with an indication of the usage-based cost for the trip (see at least Tennent, [0001]). Guedalia relates to a device identifying a string of segments from a current location of the electronic device based on a previous route, transmitting training information related to the string of segments to the electronic training device and displayed at the electronic device (see Guedalia, Abstract). Golding relates to an adaptive navigation system that learns from a user's driving history (see Golding, [0002]).
Therefore, it would have been prima facie obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method, as disclosed in Cohen, to provide the benefit of (1) updating, by the parameter generation module, the initial set of routing parameters of the navigational system based on attributes of the road segments of the previously travelled routes, (2) having the updating be carried out in response to detecting a deviation from the current recommended route for which the navigational system is providing guidance, (3) having the step of updating comprise determining a routing parameter update based on the attributes of the one or more road segments of the deviation, (5) having the previously traveled section differ from the respective recommended route by one or more deviation road segments, and (6) having the previously traveled section differ from the respective recommended route by one or more deviation road segments, as disclosed in Guedalia, with a reasonable expectation of success. It would further be obvious to provide the benefit of (4) using the generated route, from the parameter generation module and based on the generated route and a current location of the user by the navigation system to provide navigational guidance to the user for following the generated route, as disclosed in Tennent, with a reasonable expectation of success. It would still further be obvious to provide the benefit of (7) having the routing parameter update include a weighted combination of the road attributes of the difference, as disclosed in Golding, with a reasonable expectation of success. The results would have been predicable to one of ordinary skill.
As per claim 5, the combination of Cohen, Tennent, Guedalia and Golding discloses all of the limitations of claim 1, as shown above. Cohen further discloses the following limitation:
wherein generating the route comprises using a penalty function to penalize, in accordance with the route parameters, the inclusion of a road segment in the route based on the attributes of the road segment (see at least Cohen, [0080] disclosing that the routing engine 130 can use the route data and the route segment data to generate a quantitative metric of the trade-off between selecting route segments of these different types. The trade-off can correspond to properties of the resulting navigation routes such as the overall time, cost, difficulty, etc. <interpreted as penalty functions>. As a more particular example, the quantitative metric of the trade-off can be a function F.sub.1 of route difficulty the user tends to accept to save time, F.sub.1 (difficulty, time). As another example, the quantitative metric of the trade-off can be a function F.sub.2 of cost the user is willing to pay to similarly reduce the time of travel, F.sub.2 (difficulty, time). The routing engine 130 can implement machine learning techniques such as those discussed with reference to FIG. 5, a suitable algorithm, or explicit user input to generate the quantitative metric. More generally, the quantitative metric can describe the relationship between any pair of properties of navigation routes.) ... .
The examiner notes, referring to the claim interpretation section above, that the limitations after the term “optionally” have not been mapped, because the term has been constructed as having the limitations following be “optional”.
As per claim 8, the combination of Cohen, Tennent, Guedalia and Golding discloses all of the limitations of claim 1, as shown above. Tennent further discloses the following limitations:
wherein the step of updating comprises: generating, based on an initial set of routing parameters, one or more recommended routes corresponding to the previously travelled routes (see at least Tennent, [0037]; [0039]),
wherein each previously travelled route and the corresponding recommended route has a respective common start location and a respective common end location (see at least Tennent, [0012] disclosing that he route comprises a navigation path for driving from an origin location to a destination location );
determining a routing parameter update based on a difference between attributes of the road segments of the previously travelled routes and attributes of the road segments of the corresponding recommended routes (see at least Tennent, [0059] disclosing that a representation of a trip cost may be presented to a user (e.g., through a user interface of a user apparatus 20) when a trip is being planned, before a trip has started, at the beginning of a trip (e.g., in the first few minutes of the trip), during a trip, and/or if the cost of the trip has changed due to the actual trip being different from the planned/expected trip).
As per claim 10, the combination of Cohen, Tennent, Guedalia and Golding discloses all of the limitations of claim 1, as shown above. Cohen further discloses the following limitation:
wherein the attributes of a road segment comprise one or more of: a length of the road segment; a measure of congestion for the road segment; a vehicle restriction for the road segment; a speed limit for the road segment; a Functional Road Class; an indication that the road segment includes a toll road; a road segment gradient; a width of the road segment; a turn radius for a turn of the road segment; an average time for traversing a junction of the road segment; an average travel time for the road segment; and an average speed for the road segment (see at least Cohen, [0039] disclosing that the data in the database 144 can indicate that a user travels between locations L.sub.1 and L.sub.2 along a navigation route that includes several toll segments S.sub.toll1, S.sub.toll2, . . . S.sub.tollN <interpreted as an indication that the road segment includes a toll road>, and that the user spends an average time T to traverse the navigation route. Using this data along with the map database 140 and possibly other sources of relevant data (e.g., traffic data) <interpreted as a measure of congestion for the road segment>, the geographic data server 104 can determine that an alternative navigation route between the L.sub.1 and L.sub.2 includes no toll segments but requires on average a different amount of time, T′, to traverse <interpreted as an average time travel time for the road segment>).
As per claim 11, the combination of Cohen, Tennent, Guedalia and Golding discloses all of the limitations of claim 1, as shown above. Cohen further discloses the following limitation:
wherein the one or more route traces are selected from a plurality of route traces as indicative of a required change in routing parameters (see at least Cohen, [0053]; [0055]; [0058] disclosing that the geographic data server 104 then generates and ranks the candidate routes in view of the one or more metrics, at block 308. The geographic data server 104 then can transmit the ranked candidate routes to a device, such as client computing device 102, for display to a user, for example by the geographic application 160) ... .
The examiner notes, referring to the claim interpretation section above, that the limitations after the term “optionally” have not been mapped, because the term has been constructed as having the limitations following be “optional”.
As per claim 12, the combination of Cohen, Tennent, Guedalia and Golding discloses all of the limitations of claim 11, as shown above. Cohen further discloses the following limitation:
wherein said selection comprises selecting a route trace where the previously travelled route is shorter and/or quicker than a corresponding recommended route of the navigational system according to the current routing parameters (see at least Cohen, [0052] disclosing that the model 230 generates a set of context-specific metrics as a part the user metric 232. For example, the model 230 can generate one metric for a trade-off between time and cost when the user traverses relatively long paths (e.g., 50 miles or more), and another metric for the trade-off between time and cost when the user traverses relatively short distances. These multiple metrics can better reflect, for a certain example user, the preference to reduce the cost when the trip is long on the one hand, and the preference to reduce the time when the trip is short on the other hand).
As per claim 14, similar to claim 1, Cohen discloses [a] system arranged to carry out a method of navigational guidance (see at least Cohen, Abstract), the system comprising:
a navigation system configured select road segments to generate a current recommended route between an initial location and a requested destination location based on an initial set of routing parameters (see at least Cohen, [0038]; [0074]; [0075] disclosing that the geographic application 160 can provide the user interface screen 612 before the user submits a request for navigation directions or in connection with a specific navigation route. In the latter case, the geographic application 160 can determine which of the knobs 620-626 to display, and with which initial settings in view of the context of the request; [0085]);
a route trace storage configured to store at least one route trace of previously travelled section of a current route of a user of the navigational system (see at least Cohen, [0078] disclosing that the routing engine 130 obtains route data indicative of routes previously traversed by the user <interpreted as route traces of previously traveled routes>. To this end, the routing engine can use the past routes database 144. For a certain route, the route data can specify the starting location, the destination, the sequence of route segments between the starting location and the destination, etc.);
parameter generation module connected to the route trace storage through a first communication link, the parameter generation module receiving the route trace of the previously travelled section, the previously traveled section including a plurality of road segments (see at least Cohen, [0032]; [0036]; [0037]; [0039]; [0078]), ... (1) ... , ... (2) ... , ... (3) ... ;
the navigation system receiving the updated set of routing parameters from the parameter generation module over a second communication link, the navigation system generating, based on the updated set of routing parameters, a route between a current location of the user a current location and the requested destination location; and (see at least Cohen, [0032]; [0041]; [0046]; [0082]) ... (4) ... . But the difference between the claimed invention and Cohen is that Cohen does not explicitly teach the following limitation taught in Guedalia, a comparable method where is was known to:
(1) the parameter generation module updating the initial set of routing parameters of the navigational system based on attributes of the road segments of the previously travelled section, (see at least Guedalia, [0033]; [0035]);
(2) wherein the updating is carried out in response to detecting a deviation from the current recommended route for which the navigational system is providing guidance (see at least Guedalia, [0029] ; [0035]; [0062]);
(3) the step of updating comprises determining a routing parameter update based on the attributes of the one or more road segments of the deviation (see at least Guedalia, [0035]),
(5) wherein the previously traveled section differs from the respective recommended route by one or more deviation road segments (see at least Guedalia, [0033]; [0035]); and
(6) wherein the previously traveled section differs from the respective recommended route by one or more deviation road segments (see at least Guedalia, [0033]; [0035]). But the difference between the claimed invention and the combination of Cohen and Guedalia is that the combination does not explicitly teach the following limitation taught in Tennent, a comparable method where it was known to:
(4) the navigation system using the generated route and the current location of the user to produce and send a signal to the vehicle to provide navigational guidance to the user for following the generated route (see at least Tennent, [0006]; [0033]; [0072]). But, the difference between the claimed invention and Cohen as modified by Guedalia and Tennent is that neither Cohen, Guedalia nor Tennent explicitly teach the following limitations taught in Golding, a comparable method where is was known to:
(7) wherein the routing parameter update includes a weighted combination of the road attributes of the difference (see at least Golding, [0096]; [0098]).
Cohen, Tennent, Guedalia and Gold are analogous art to claim 14 because they are in the same field of navigational guidance and determining routing restrictions. Cohen relates to a technique for generating navigation routes includes obtaining route data indicative of multiple routes between respective starting locations and destinations, previously traversed by a user (see at least Cohen, Abstract). Tennent relates to determining cost model parameters for determining a usage-based cost for a trip and providing a user with an indication of the usage-based cost for the trip (see at least Tennent, [0001]). Guedalia relates to a device identifying a string of segments from a current location of the electronic device based on a previous route, transmitting training information related to the string of segments to the electronic training device and displayed at the electronic device (see Guedalia, Abstract). Golding relates to an adaptive navigation system that learns from a user's driving history (see Golding, [0002]).
Therefore, it would have been prima facie obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method, as disclosed in Cohen, to provide the benefit of (1) updating, by the parameter generation module, the initial set of routing parameters of the navigational system based on attributes of the road segments of the previously travelled routes, (2) having the updating be carried out in response to detecting a deviation from the current recommended route for which the navigational system is providing guidance, (3) having the step of updating comprise determining a routing parameter update based on the attributes of the one or more road segments of the deviation, (5) having the previously traveled section differ from the respective recommended route by one or more deviation road segments, and (6) having the previously traveled section differ from the respective recommended route by one or more deviation road segments, as disclosed in Guedalia, with a reasonable expectation of success. It would further be obvious to provide the benefit of (4) using the generated route, from the parameter generation module and based on the generated route and a current location of the user by the navigation system to provide navigational guidance to the user for following the generated route, as disclosed in Tennent, with a reasonable expectation of success. It would still further be obvious to provide the benefit of (7) having the routing parameter update include a weighted combination of the road attributes of the difference, as disclosed in Golding, with a reasonable expectation of success. The results would have been predicable to one of ordinary skill.
As per claim 15, similar to claim 1, Cohen discloses [a] non-transitory computer-readable medium storing a computer program which, when executed by a processor, causes the processor to carry out a method (see at least Cohen, Abstract; [0042] disclosing that the client computing device 102 can include processing hardware such as one or more processors 152, a non-transitory memory 150 (e.g., a hard disk, a flash drive to implement persistent and/or non-persistent storage components), and a user interface 154 that can include any suitable combination of input devices such as a touchscreen, a keyboard, a microphone, etc. and output devices such as screens, speakers, etc. The memory 150 stores instructions that implement a geographic application 160 configured to receive navigation routes and other navigation data from the server 104 and provide navigation directions including the navigation routes via the user interface 154; [0098] disclosing that certain embodiments are described herein as including logic or a number of components, modules, or mechanisms. Modules may constitute either software modules (e.g., code stored on a machine-readable medium) or hardware modules. A hardware module is a tangible unit capable of performing certain operations and may be configured or arranged in a certain manner. In example embodiments, one or more computer systems (e.g., a standalone, client or server computer system) or one or more hardware modules of a computer system (e.g., a processor or a group of processors) may be configured by software (e.g., an application or application portion) as a hardware module that operates to perform certain operations as described herein; [0102]), the method comprising:
selecting, by a navigational system which is part or associated with a vehicle, road segments to generate a current recommended route between an initial location and a requested destination location based on an initial set of routing parameters (see at least Cohen, [0038]; [0085]),
transmitting, from a route trace storage to a parameter generation module over a first communication link, a route trace of a previously travelled section of a current route of a user of the navigational system, by a parameter generation module, by a parameter generation module, the previously traveled section of the current route including a plurality of road segments (see at least Cohen, [0032]; [0036]; [0037]; [0039] disclosing Fig. 2, showing smart phone 202 <navigation device> transmitting to server 208 <first communication link>; [0078]), ... (1) ... , ... (2) ... , ... (3) ... ;
generating, via the parameter generation module and based on the updated set of routing parameters, a route between a current location of the user and a requested destination location (see at least Cohen, [0032]; [0041]; [0046]; [0082]) ... (4) ...
based on the generated route and the current location of the user, producing a signal by the navigational system and sending the signal via an interface to the vehicle to provide navigational guidance to the user for following the generated route (see at least Cohen, [0043]; [0045]; [0058] disclosing that the geographic data server 104 then can transmit the ranked candidate routes to a device, such as client computing device 102, for display to a user <interpreted as navigational guidance to the user for following the generated route>, for example by the geographic application 160) ... (5) ... , ... (6) ... , ... (7) ... . But the difference between the claimed invention and Cohen is that Cohen does not explicitly teach the following limitation taught in Guedalia, a comparable method where is was known to:
(1) updating, by the parameter generation module, the initial set of routing parameters of the navigational system based on attributes of the road segments of the previously travelled routes (see at least Guedalia, [0033]; [0035])
(2) wherein the updating is carried out in response to detecting a deviation from the current recommended route for which the navigational system is providing guidance (see at least Guedalia, [0029] ; [0035]; [0062]);
(3) the step of updating comprises determining a routing parameter update based on the attributes of the one or more road segments of the deviation (see at least Guedalia, [0035]),
(5) wherein the previously traveled section differs from the respective recommended route by one or more deviation road segments (see at least Guedalia, [0033]; [0035]); and
(6) wherein the previously traveled section differs from the respective recommended route by one or more deviation road segments (see at least Guedalia, [0033]; [0035]). But the difference between the claimed invention and the combination of Cohen and Guedalia is that the combination does not explicitly teach the following limitation taught in Tennent, a comparable method where it was known to:
(4) using the generated route, from the parameter generation module and based on the generated route and a current location of the user by the navigation system to provide navigational guidance to the user for following the generated route (see at least Tennent, [0006]; [0033]; [0072]). But, the difference between the claimed invention and Cohen as modified by Guedalia and Tennent is that neither Cohen, Guedalia nor Tennent explicitly teach the following limitations taught in Golding, a comparable method where is was known to:
(7) wherein the routing parameter update includes a weighted combination of the road attributes of the difference (see at least Golding, [0096]; [0098]).
Cohen, Tennent, Guedalia and Gold are analogous art to claim 15 because they are in the same field of navigational guidance and determining routing restrictions. Cohen relates to a technique for generating navigation routes includes obtaining route data indicative of multiple routes between respective starting locations and destinations, previously traversed by a user (see at least Cohen, Abstract). Tennent relates to determining cost model parameters for determining a usage-based cost for a trip and providing a user with an indication of the usage-based cost for the trip (see at least Tennent, [0001]). Guedalia relates to a device identifying a string of segments from a current location of the electronic device based on a previous route, transmitting training information related to the string of segments to the electronic training device and displayed at the electronic device (see Guedalia, Abstract). Golding relates to an adaptive navigation system that learns from a user's driving history (see Golding, [0002]).
Therefore, it would have been prima facie obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method, as disclosed in Cohen, to provide the benefit of (1) updating, by the parameter generation module, the initial set of routing parameters of the navigational system based on attributes of the road segments of the previously travelled routes, (2) having the updating be carried out in response to detecting a deviation from the current recommended route for which the navigational system is providing guidance, (3) having the step of updating comprise determining a routing parameter update based on the attributes of the one or more road segments of the deviation, (5) having the previously traveled section differ from the respective recommended route by one or more deviation road segments, and (6) having the previously traveled section differ from the respective recommended route by one or more deviation road segments, as disclosed in Guedalia, with a reasonable expectation of success. It would further be obvious to provide the benefit of (4) using the generated route, from the parameter generation module and based on the generated route and a current location of the user by the navigation system to provide navigational guidance to the user for following the generated route, as disclosed in Tennent, with a reasonable expectation of success. It would still further be obvious to provide the benefit of (7) having the routing parameter update include a weighted combination of the road attributes of the difference, as disclosed in Golding, with a reasonable expectation of success. The results would have been predicable to one of ordinary skill.
Claims 6 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Cohen, Tennent, Guedalia and Golding as applied to claim 1 above, and further in view of U.S. Patent Publication Number 2021/0403032 to Jing et al. (hereafter Jing).
As per claim 6, the combination of Cohen, Tennent, Guedalia and Golding discloses all of the limitations of claim 1, as shown above. But, neither Cohen, Tennent, Guedalia nor Golding explicitly disclose the following limitation disclosed in Jing:
wherein the step of updating comprises applying a trained machine learning algorithm to the attributes of a plurality of road segments of the one or more previously travelled routes to determine one or more routing parameters updates (see at least Jing, Fig. 5a, [0083] disclosing that Fig. 5A depicts an illustration at 510 of a family of arc paths originating at an ending location for an autonomous vehicle. Shown at 512 is an example of an ending location for an autonomous vehicle which is also the starting location for searching optimal paths that lead to the designated ending location for all nodes on the state space in the reverse direction. Fanning out from ending location 512 are a family of possible arc (or path) segments. Each arc segment begins at a node and ends at another node. Arc segments are pruned to remove nodes that cannot be reached <interpreted as updating the routing> based on limitations of the vehicle such as a tractor-trailer <interpreted as routing parameter updates> ; [0138] disclosing and updating process, a confidence checker module may perform a confidence checking operation 1006 using online algorithm results (1002) and offline algorithm results (1004) obtained from previous operation of the autonomous vehicle; [0142] disclosing that changes may include updates to the machine learning model used by the existing autonomous driving software or updates to image processing techniques to better identify moving objects (e.g., other cars, pedestrians) or static obstacles (e.g., speed bumps, stop signs, etc.) located in an area surrounding the autonomous vehicle).
The examiner notes, referring to the claim interpretation section above, that the limitations after the term “optionally” have not been mapped.
Cohen, Tennent, Guedalia, Golding and Jing are analogous art to claim 6 because they are in the same field of navigational guidance and determining routing restrictions. Cohen relates to a technique for generating navigation routes includes obtaining route data indicative of multiple routes between respective starting locations and destinations, previously traversed by a user (see at least Cohen, Abstract). Tennent relates to determining cost model parameters for determining a usage-based cost for a trip and providing a user with an indication of the usage-based cost for the trip (see at least Tennent, [0001]). Guedalia relates to a device identifying a string of segments from a current location of the electronic device based on a previous route, transmitting training information related to the string of segments to the electronic training device and displayed at the electronic device (see Guedalia, Abstract). Golding relates to an adaptive navigation system that learns from a user's driving history (see Golding, [0002]). Jing relates to a two-level optimal path planning process for autonomous tractor-trailer trucks which incorporates offline planning, online planning, and utilizing online estimation and perception results for adapting a planned path to real-world changes in the driving environment (see at least Jing, Abstract).
Therefore, it would have been prima facie obvious for someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method as disclosed in Cohen, as modified by Tennent, and further modified by Guedalia and Golding, to provide the benefit of having the step of updating comprise applying a trained machine learning algorithm to the attributes of a plurality of road segments of the one or more previously travelled routes to determine one or more routing parameters updates, as disclosed in Jing, with a reasonable expectation of success. Doing so would provide the benefit of improving the safety of the navigation (see at least Jing, [0008]).
As per claim 7, the combination of Cohen, Tennent, Guedalia, Golding and Jing discloses all of the limitations of claim 6, as shown above. Jing further discloses the following limitation:
wherein the routing parameter updates comprise, for a previously travelled route, the respective probability that one or more routing parameter values correspond to said route (see at least Jing, [0138] a confidence checker module may perform a confidence checking operation 1006 using online algorithm results (1002) and offline algorithm results (1004) obtained from previous operation of the autonomous vehicle).
Claims 36 and 37 are rejected under 35 U.S.C. 103 as being unpatentable over Cohen, Tennent, Guedalia and Golding as applied to claim 1 above, and further in view of U.S. Patent Publication Number 2019/0242716 to N et al. (hereafter N).
As per claim 36, the combination of Cohen, Tennent, Guedalia and Golding discloses all of the limitations of claim 1, as shown above. But neither Cohen, Tennent, Guedalia nor Golding explicitly teach the following limitation taught in N:
wherein the initial set of routing parameters define constraints or requirements on attributes of the current route (see at least N, [0040] disclosing that the route parameters 81 may also include a route time completion window. For example, the route time completion window may depict the earliest time that the perishable goods 34 may be picked up at the origination location 206 and the latest time that the perishable goods 34 may be delivered to the destination location 208. A departure time 212 may be chosen in order to satisfy the route time completion window. Route parameters 81 may also include information regarding traffic conditions along the potential routes 102 of the vehicle 12).
Cohen, Tennent, Guedalia, Golding and N are analogous art to claim 36 because they are in the same field of navigational guidance and determining routing restrictions. Cohen relates to a technique for generating navigation routes includes obtaining route data indicative of multiple routes between respective starting locations and destinations, previously traversed by a user (see at least Cohen, Abstract). Tennent relates to determining cost model parameters for determining a usage-based cost for a trip and providing a user with an indication of the usage-based cost for the trip (see at least Tennent, [0001]). Guedalia relates to a device identifying a string of segments from a current location of the electronic device based on a previous route, transmitting training information related to the string of segments to the electronic training device and displayed at the electronic device (see Guedalia, Abstract). Golding relates to an adaptive navigation system that learns from a user's driving history (see Golding, [0002]). N relates to an apparatus and a method for determining potential routes to transport perishable goods (see at least N, [0002]).
Therefore, it would have been prima facie obvious for someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method as disclosed in Cohen, as modified by Tennent, and further modified by Guedalia and Golding, to provide the benefit of having the initial set of routing parameters define constraints or requirements on attributes of the current route, as disclosed in N, with a reasonable expectation of success. Doing so would provide the benefit of considering the attributes of distance, time and energy efficiency in the routing (see at least N, [0006]).
As per claim 37, the combination of Cohen, Tennent, Guedalia, Golding and N discloses all of the limitations of claim 1, as shown above. N further discloses the following limitation:
wherein the constraints or requirements relate to vehicle weight, vehicle size, travel time, travel distance, and/or traffic density (see at least N, [0040] disclosing that the route parameters 81 may also include a route time completion window. For example, the route time completion window may depict the earliest time that the perishable goods 34 may be picked up at the origination location 206 and the latest time that the perishable goods 34 may be delivered to the destination location 208. A departure time 212 may be chosen in order to satisfy the route time completion window. Route parameters 81 may also include information regarding traffic conditions along the potential routes 102 of the vehicle 12. Vehicle parameters 82 may include the range capabilities of the vehicle 12 transporting the perishable goods including but not limited to vehicle size, vehicle capacity, vehicle equipment, vehicle capability, driver availability, energy source capacity, energy source type, estimated energy source consumption, wind skirts, wind fairings, or other similar vehicle information. For example, a vehicle with a long range may be able to travel along routes with fewer places to refuel its energy source (e.g. gas stations or recharging stations)).
Claims 38 is rejected under 35 U.S.C. 103 as being unpatentable over Cohen, Tennent, Guedalia and Golding as applied to claim 1 above, and further in view of U.S. Patent Publication Number 2018/0238698 to Pedersen.
As per claim 38, the combination of Cohen, Tennent, Guedalia and Golding discloses all of the limitations of claim 1, as shown above. But, neither Cohen, Tennent, Guedalia nor Golding explicitly teach the following limitation taught in Pedersen:
wherein each routing parameter of the initial set of routing parameters has a value in a range from 0.0 to 1.0, which indicates the importance of the requirement of the routing parameter (see at least Pedersen, Fig. 7, [0105] disclosing that FIG. 7 depicts in matrix form artificial intelligence expert system relationships (700) between two selected parameters, energy needed and travel time that may be used in some embodiments of the present invention to assist in selecting a particular route for the electric vehicle to travel from its current position to its ultimate destination. As indicated in FIG. 7 the range of the parameters for energy needed and travel time are divided into exemplary subranges corresponding to very low, low, medium, high and very high. For each combination of such values for the two parameters being considered in FIG. 7, an artificial intelligence expert decision rating is provided indicating the desirability of traveling along a specific specified route having the corresponding values of the energy needed and travel time parameters <interpreting very high in Fig. 7 and 1, and very low in Fig. 7 as 0>; Fig. 9, [0129]-[0133]).
Cohen, Tennent, Guedalia, Golding and Pedersen are analogous art to claim 38 because they are in the same field of navigational guidance and determining routing restrictions. Cohen relates to a technique for generating navigation routes includes obtaining route data indicative of multiple routes between respective starting locations and destinations, previously traversed by a user (see at least Cohen, Abstract). Tennent relates to determining cost model parameters for determining a usage-based cost for a trip and providing a user with an indication of the usage-based cost for the trip (see at least Tennent, [0001])). Guedalia relates to a device identifying a string of segments from a current location of the electronic device based on a previous route, transmitting training information related to the string of segments to the electronic training device and displayed at the electronic device (see Guedalia, Abstract). Golding relates to an adaptive navigation system that learns from a user's driving history (see Golding, [0002]). Pedersen relates to systems, methods and algorithms based on artificial intelligence expert system technology for determination of preferred routes of travel for electric vehicles (EVs) (see at least Pedersen, Abstract).
Therefore, it would have been prima facie obvious for someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method as disclosed in Cohen, as modified by Tennent, and further modified by Guedalia and Golding, to provide the benefit of having each routing parameter of the initial set of routing parameters have a value in a range from 0.0 to 1.0, which indicates the importance of the requirement of the routing parameter, as disclosed in Pedersen, with a reasonable expectation of success. Doing so would provide the benefit of improving efficient routing through the use of algorithms employed in real-time without excessive and complex computation and that consider multiple factors such as battery charging-replacement station locations, required time of travel, roadway conditions, traffic congestion, including congestion for charging stations and minimization of required energy usage to travel between EV changing positions and destination locations ( see at least Pedersen, [0024]).
Conclusion
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PATRICK M. BRADY III
Examiner
Art Unit 3665
/PATRICK M BRADY/Examiner, Art Unit 3665
/Erin D Bishop/Supervisory Patent Examiner, Art Unit 3665