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 .
Status of Claims
This Office action is in reply to filing by applicant on 04/21/2026.
Claims 1, 15, and 20 were amended by Applicant.
Claims 2 – 14 and 16 – 19 remain as original.
Claims 1 – 20 are currently pending and have been examined.
The prior 35 USC 101 claim rejections set forth in the Non-Final rejection of 12/23/2025 as to claims 1 – 20 are maintained in view of Applicant's arguments and amendments.
The prior 35 USC 103 claim rejections set forth in the Non-Final rejection of 12/23/2025 as to claims 1 – 3, 8 – 15, and 18 – 20 are maintained in view of Applicant's arguments and amendments.
THIS ACTION IS MADE FINAL.
Response to Arguments
There are no new grounds of rejection herein as to any of the claims.
With regard to the limitations of claims 1 – 20, Applicant argues that the claims as amended are patent eligible under 35 USC 101 because they meet the analysis set forth by the Supreme Court. Remarks 10 - 12. Examiner respectfully disagrees. The subject claims noted were analyzed pursuant to MPEP 2106, et seq., and are still considered ineligible. Step 1 is met because the claims are directed towards one of the four statutory categories; Part 2A-Prong1 of the test is trying to evaluate if the claims recite a judicial exception (an abstract idea enumerated in the MPEP 2106.04(a)); Part 2A-Prong 2 is to evaluate whether the subject claims recite additional elements that integrate the exception into a practical application, and, lastly, Part 2B checks whether the claims amount to significantly more than the abstract idea. A detailed and formal analysis pursuant to 35 USC 101 as the same applies to the amended claim set will follow below.
As respects 35 USC 101, Applicant specifically argues the amended sections of the claims of the claims as a whole amount to a drafting effort designed to monopolize the exception. The additional limitations when taken individually and in combination are not sufficient to amount to significantly more than the judicial exception because the claims do not provide improvements to another technology or technical field nor improvements to the function of the computer itself. Accordingly, the claim(s) recite an abstract idea. A detailed and formal analysis pursuant to 35 USC 101 as the same applies to the specifics of the claims follows below.
Applicant argues per 35 USC 101 that the claims of 04/21/2026 as amended no longer recite a judicial exception at Step 2A, Prong One. Remarks 8 – 9. Examiner respectfully disagrees. To wit:
Although Applicant respectfully disagrees with the rejections, the independent claims have been amended to advance prosecution. The independent claims now recite, inter alia, "instantiating, in a road segment datastore comprising a data structure, a plurality of segments" and "creating, in the road segment datastore, a connection between each segment in each pair of segments, wherein the connection between each pair of segments in the road segment datastore is instantiated as an entry of the data structure such that each pair of physical road segments that intersect corresponds to at least one connection within entries of the data structure and comprises connectivity attributes derived from the digital map data, wherein the connectivity attributes identify one or more permanent or semi-permanent characteristics of physical intersections between pairs of physical road segments." Support for the amendments can be found throughout the originally filed application, for example, in paragraph [0035] of the Specification and in FIGS. 5A-5C of the drawings.
See Remarks 10.
The above noted amended language that Applicant argues per 35 USC 101 has not yet been specifically addressed by examiner. That said, the above amended portion does not aid in taking the previous claim set out of the previous 35 USC 101 rejection of a “mental process” grouping of abstract ideas. The recent amendments as above are simply a long winded way of specifically claiming that the road sections intersect at intersections, and that those intersections have unique markers, notions which can easily be part of the mental process embodied in these claims detailed previously. Please see detailed 35 USC 101 analysis following.
Applicant argues per 35 USC 103 that the citations provided by examiner (Konrardy and Leonard) do not adequately serve to analyze the claims as amended. Examiner respectfully disagrees. Once again, Applicant’s arguments deal exclusively with the amended sections of the claims, not yet addressed by examiner. Those amended sections as to these specific amended limitations have therefore been specifically analyzed in the following 35 USC 103 analyses.
Generally as to obviousness, examiner submits that it is determined on the basis of the evidence as a whole and the relative persuasiveness of the arguments. See In re Oetiker, 977 F.2d 1443, 1445, 24 USPQ2d 1443, 1444 (Fed. Cir. 1992); In re Hedges, 783 F.2d 1038, 1039, 228 USPQ 685,686 (Fed. Cir. 1992); In re Piasecki, 745 F.2d 1468, 1472, 223 USPQ 785,788 (Fed. Cir. 1984); and In re Rinehart, 531 F.2d 1048, 1052, 189 USPQ 143,147 (CCPA 1976). Using this standard, examiner submits that the burden of presenting a prima facie case of obviousness was successfully established in the prior Office Action of 12/23/2025, and also respecting the pending amended claim set of 04/21/2026, as seen below.
Examiner recognizes that references cannot be arbitrarily altered or modified, and that there must be some reason why a person having ordinary skill in the relevant art would be motivated to make the proposed modifications. Although the motivation or suggestion to make modifications must be articulated, it is respectfully submitted that there is no requirement that the motivation to make modifications must be expressly articulated within the references themselves. References are evaluated by what they suggest to one versed in the art, rather than by their specific disclosures, In re Bozek, 163 USPQ 545 (CCPA 1969).
Examiner also notes that the motivation to combine the applied references is, where appropriate in the below detailed analysis pursuant to 35 USC 103, additionally accompanied by select passages from the respective references which specifically support that particular motivation. It is also respectfully submitted that motivation based on the logic and scientific reasoning of one ordinarily skilled in the art at the time of the invention, which evidence can also support a finding of obviousness, is otherwise provided in the detailed 35 USC 103 analysis of the claim set below. In re Nilssen, 851 F.2d 1401, 1403, 7 USPQ2d 1500, 1502 (Fed. Cir. 1988) (references do not have to explicitly suggest combining teachings); Ex parte Clapp, 227 USPQ 972 (Bd. Pat. App. & Inter. 1985) (examiner must present convincing line of reasoning supporting rejection); and Ex parte Levengood, 28 USPQ2d 1300 (Bd. Pat. App. & Inter. 1993) (reliance on logic and sound scientific reasoning).
Examiner recognizes that obviousness can only be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to a person of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988) and In re Jones, 958 F.2d 347.
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.
Independent claims 1, 15, and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Analysis of Independent claims 1, 15, and 20:
A method (claim 1), a system (claim 15), and a non-transitory machine-readable storage medium comprising (claim 20), (note that claim 1 is used here as being representative):
Examiner notes that the below preamble of the claim gives life / context to, and is therefore considered as, claim language. Otherwise the context of the claim interpretation would be unclear as to what the computer generated things in the body of the claim refer to.
Independent claim 1 -
A computer-implemented method of mapping driving risk in a geographic area,
the computer-implemented method comprising: instantiating, in a road segment datastore, comprising a data structure a plurality of segments, wherein each segment of the plurality of segments has a corresponding physical road segment of a plurality of physical road segments in the geographic area, and
wherein each segment of the plurality of segments comprises: segment attributes derived from digital map data for the corresponding physical road segment; and
a risk attribute;
determining, from the digital map data, pairs of physical road segments that intersect, wherein each pair of physical road segments that intersect has a corresponding pair of segments in the road segment datastore, and
each segment of the plurality of segments is included in at least one pair of segments;
creating, in the road segment datastore, a connection between each segment in each pair of segments, wherein the connection between each pair of segments in the road segment datastore is instantiated as an entry of the data structure such that each pair of physical road segments that intersect corresponds to at least one connection within entries of the data structure and comprises connectivity attributes derived from the digital map data, wherein the connectivity attributes identify one or more permanent or semi-permanent characteristics of physical intersections between pairs of physical road segments; and
updating, in the road segment datastore, the risk attribute for each segment of the plurality of segments that is connected to one or more paired segments based on:
the segment attributes for the segment;
the segment attributes for the one or more paired segments; and
the connectivity attributes between the segment and the one or more paired segments.
101 Analysis - Step 1: Statutory category – Yes
The claims recite a method (claim 1), a system (claim 15),and a non-transitory machine-readable storage medium (claim 20). Thus, these claims all fall within one of the four statutory categories. MPEP 2106.03
101 Analysis - Step 2A Prong one evaluation: Judicial Exception – Yes – Mental processes
In Step 2A, Prong one of the 2019 Patent Eligibility Guidance (PEG), a claim is 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, the limitations can be “performed in the human mind, or by a human using a pen and paper”. See MPEP 2106.04(a)(2)(III).
The claim recites the limitation(s) of: mapping driving risk in a geographic area, … comprising …a plurality of segments, wherein each segment of the plurality of segments has a corresponding physical road segment of a plurality of physical road segments in the geographic area, and wherein each segment of the plurality of segments comprises: segment attributes derived from digital map data for the corresponding physical road segment; and a risk attribute; determining, from the digital map data, pairs of physical road segments that intersect, wherein each pair of physical road segments that intersect has a corresponding pair of segments in the road segment datastore, and each segment of the plurality of segments is included in at least one pair of segments; creating, … a connection between each segment in each pair of segments … such that each pair of physical road segments that intersect corresponds to at least one connection … wherein the connectivity attributes identify one or more permanent or semi-permanent characteristics of physical intersections between pairs of physical road segments; and updating, the risk attribute for each segment of the plurality of segments that is connected to one or more paired segments based on: the segment attributes for the segment; the segment attributes for the one or more paired segments; and the connectivity attributes between the segment and the one or more paired segments. These limitations, as drafted, and under their broadest reasonable interpretation, cover performance of the limitation in the mind, but for the recitation of being performed using a computer-implemented method and a road segment datastore. That is, other than reciting a computer-implemented method and a road segment datastore, nothing in the claim elements preclude the step from practically being performed in the mind. For example, the claim encompasses a person knowing where they going to drive to, then conceiving a mental image of the risk related to a certain route selection and its location (e.g., a driver might want to avoid a risky intersection along a certain route on the way to a destination), including the above outlined amendments relating to intersecting paths and markers at those intersections (e.g., also contemplating in the mind that there’s a bank at the corner of Elm and Main). The mere nominal recitations of using a computer-implemented method and a road segment datastore do not take the claim limitations out of the mental process grouping. Thus, the claims recite a mental process.
101 Analysis - Step 2A Prong two evaluation: Practical Application – No
In Step 2A, Prong two of the 2019 PEG, a claim is to be evaluated whether, as a whole, it integrates the recited judicial exception into a practical application. As noted in MPEP 2106.04(d), 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, such that the claim is more than a drafting effort designed to monopolize the judicial exception. The courts have indicated that additional elements such as: 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.”
The Office submits that the foregoing underlined limitations recite additional elements that do not integrate the recited judicial exception into a practical application.
The independent claims 1 (15, and 20) recite additional elements or steps of using a generic computer and datastore (and the memories / processors / non-transitory computer readable media of independent claims 15 and 20) to perform the abstract idea. These above mentioned additional elements are recited at a high level of generality (i.e. as a general means for gathering of the status of route selection / information) and amount to mere data gathering, which is a form of insignificant extra-solution activity. Moreover, these limitations merely describe generally “applying” the otherwise mental judgements using a generic or general-purpose computer controller, as noted above. The generic computer and datastore (and the memories / processors / non-transitory computer readable media of independent claims 15 and 20) are all recited with a high level of generality and they merely automate the above several steps of the above bolded abstract idea.
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.
101 Analysis - Step 2B evaluation: Inventive concept - No
In Step 2B of the 2019 PEG, a claim is to be evaluated as to whether the claim, as a whole, amounts 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. See MPEP 2106.05.
As discussed with respect to Step 2A Prong Two, the additional elements in the claim 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 using generic devices, processors, memories, and/or generic computer-readable media, cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
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 several instantiating, determining and connecting 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. There is nothing in the disclosure that recites that the processors, memories, sensors, and/or generic computer-readable media are anything other than a conventional, generic, computer and/or computer controlled components. 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 of data is a well understood, routine, and conventional function. Accordingly, a conclusion that the above underlined several elements / steps regarding the several instantiating, determining and connecting steps amount to well-understood, routine, conventional activity and are supported under Berkheimer.
Thus, independent claims 1, 15, and 20 are ineligible.
Dependent Claims
Dependent claims 2 – 14 and 16 – 19 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of these dependent claims are directed toward additional aspects of the judicial exception. As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component(s). 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.
Dependent claims 2 – 14 and 16 – 19 are not patent eligible under the same rationale as provided for in the above rejection of independent claims 1, 15, and 20.
Given the above analysis, all claims 1 – 20 are ineligible under 35 USC §101.
Claim Rejections – 35 USC 103
In the event the determination of the status of the application as subject to AIA 35 USC 102 and 103 is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 USC 103 which forms the basis for all obviousness rejections set forth in this Office Action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 USC 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating
obviousness or nonobviousness.
Claims 1 – 3, 8 – 15, and 18 – 20 are rejected pursuant to 35 USC 103 as being unpatentable over Konrardy (US20200317216A1) in view of Leonard (US20190283756A1).
Regarding claims 1, 15, and 20:
Konrardy discloses:
a method of mapping driving risk in a geographic area, the computer-implemented method comprising: instantiating, in a road segment datastore comprising a data structure, a, a plurality of segments, wherein each segment of the plurality of segments has a corresponding physical road segment of a plurality of physical road segments in the geographic area, and Examiner reads the claim term “instantiate” broadly to include the meanings of embody, illustrate, express, and/or represent (instantiate is cited in normal usage in Specification a total of ten (10) times); that said, examiner interprets the foregoing limitation to include the meaning that a representation of multiple parts or segments of a physical road may be stored in a database, each of which part / segment has a geographic area / driving risk associated with it, … (“The present embodiments may be related to autonomous or semi-autonomous vehicle operation, including driverless operation of fully autonomous vehicles. The embodiments described herein relate particularly to various aspects of route determination and navigation of autonomous vehicles. This may include determining suitability of roads or road segments for varying levels of autonomous operation, which may include generating maps indicating roadway suitability for autonomous operation. This may further include route planning, adjustment, or optimization, including risk management by avoidance of road segments associated with high risk levels for vehicle accidents involving autonomous vehicles.”, [006]) and (“At block 504, the external computing device 186 (such as a server 140) may similarly receive map data indicating a plurality of known road segments. The map data may be obtained upon requesting such data from a map database storing roadway data. For example, a map database may include a plurality … of line segments indicated by geopositioning coordinates of the endpoints of the segments. The road segments may individually include only portions of a stretch of roadway (e.g., a block, a quarter mile, etc.), which interconnect to form a representation of a roadway system or network. … The map data (and the operating data discussed above) may be received for a limited geographic area for which road segments are to be evaluated.”, [0123]) and (“In some embodiments of the system 100, the front-end components 102 may communicate with the back-end components 104 via a network 130. Either the on-board computer 114 or the mobile device 110 may communicate with the back-end components 104 via the network 130 to allow the back-end components 104 to record information regarding vehicle usage. The back-end components 104 may use one or more servers 140 to receive data from the front-end components 102, store the received data, process the received data, and/or communicate information associated with the received or processed data.”, [031]) and (“Regardless of the source, the data received may be associated with geographic locations. Such associations may be indicated by geospatial coordinates (e.g., GPS position), relative location data (e.g., street addresses, intersections, etc.), or area indications (e.g., cities, counties, types of roads, etc.)”, [0122]), risks for geographically located segments of roadway for an autonomous vehicle to traverse are determined and stored;
wherein each segment of the plurality of segments comprises: segment attributes derived from digital map data for the corresponding physical road segment; and (“The various software applications on the server 140 may include an autonomous operation information monitoring application 141 for receiving information regarding the vehicle 108 and its autonomous operation features … and/or determining operating condition of autonomous operation features or components, a risk mapping application 143 for determining the risks associated with autonomous operation feature use along a plurality of road segments associated with an electronic map, a route determination application 144 for determining routes suitable for autonomous or semi-autonomous vehicle operation … .”, [045]) and (“This may include determining suitability of roads or road segments for varying levels of autonomous operation, which may include generating maps indicating roadway suitability for autonomous operation”, [006]) and (“wherein whether the one or more current usage levels of the autonomous operation features comply with the allowable usage levels may be determined for each of one or more road segments along a route traversed by the vehicle during operation. Additionally or alternatively, the method may further include the following: identifying a location of the vehicle using a geolocation component; accessing map data containing map information regarding a plurality of road segments, which map information may include location data associated with each road segment and an indication of suitability for autonomous operation feature use associated with each road segment;”, [009]), road segment data / attributes (e.g., location) may be derived from digital maps for this or that road;
a risk attribute; (“Risk category or price may be determined based upon factors relating to the evaluated effectiveness of the autonomous vehicle features. The risk or price determination may also include traditional factors, such as location, vehicle type, and level of vehicle use. … For vehicles with autonomous communication features that obtain information from external sources (e.g., other vehicles or infrastructure), the risk level and/or price determination may also include an assessment of the availability of external sources of information. Location and/or timing of vehicle use may thus be monitored and/or weighted to determine the risk associated with operation of the vehicle.”, [029]);
creating, in the road segment datastore, a connection between each segment in each pair of segments, Examiner broadly interprets this limitation to include the meaning that data pertaining to connecting road segments (e.g., at an intersection) may be stored, … (“The road segments may individually include only portions of a stretch of roadway (e.g., a block, a quarter mile, etc.), which interconnect to form a representation of a roadway system or network. In some embodiments, such map data may be obtained from a third party as a copy of a database or via access through an Application Program Interface (API). The map data (and the operating data discussed above) may be received for a limited geographic area for which road segments are to be evaluated.”, [0123]);
wherein the connection between each pair of segments in the road segment datastore is instantiated as an entry of the data structure such that each pair of physical road segments that intersect corresponds to at least one connection within entries of the data structure and Examiner broadly interprets this amended language consistent with the Disclosure to include the meaning that a “connection” between two roads is simply an “intersection” between two roads … (“ For example, part of the operating data may include street addresses or intersections, which may be converted into GPS coordinates for matching with the road segment data. In some embodiments, some road segments may be grouped or combined into relevant segments. For example, several segments of a long and winding road between intersections may be combined to facilitate more efficient analysis”, [0124]);
comprises connectivity attributes derived from the digital map data; and (“The various software applications on the server 140 may include an autonomous operation information monitoring application 141 for receiving information regarding the vehicle 108 and its autonomous operation features … and/or determining operating condition of autonomous operation features or components, a risk mapping application 143 for determining the risks associated with autonomous operation feature use along a plurality of road segments associated with an electronic map, a route determination application 144 for determining routes suitable for autonomous or semi-autonomous vehicle operation … .”, [045]) and (“This may include determining suitability of roads or road segments for varying levels of autonomous operation, which may include generating maps indicating roadway suitability for autonomous operation”, [006]) and (“Additionally or alternatively, the method may further include the following: identifying a location of the vehicle using a geolocation component; accessing map data containing map information regarding a plurality of road segments, which map information may include location data associated with each road segment and an indication of suitability for autonomous operation feature use associated with each road segment;”, [009]), road segment data / attributes (e.g., location) may be derived from digital maps for this or that road and (“The various software applications on the server 140 may include an autonomous operation information monitoring application 141 for receiving information regarding the vehicle 108 and its autonomous operation features (which may include control commands or decisions of the autonomous operation features), a feature evaluation application 142 for determining the effectiveness of autonomous operation features under various conditions and/or determining operating condition of autonomous operation features or components, a risk mapping application 143 for determining the risks associated with autonomous operation feature use along a plurality of road segments associated with an electronic map, … “, [045]);
wherein the connectivity attributes identify one or more permanent or semi-permanent characteristics of physical intersections between pairs of physical road segments; and (“Additionally or alternatively, the method may further include the following: identifying a location of the vehicle using a geolocation component; accessing map data containing map information regarding a plurality of road segments, which map information may include location data associated with each road segment and an indication of suitability for autonomous operation feature use associated with each road segment; and/or identifying a current road segment from the plurality of road segments based upon the identified location of the vehicle. In such instances, the allowable usage levels may be determined at least in part based upon the indication of suitability for autonomous operation feature use associated with the current road segment.”, [009]);
updating, in the road segment datastore, the risk attribute for each segment of the plurality of segments that is connected to one or more paired segments based on: the segment attributes for the segment; (“For example, part of the operating data may include street addresses or intersections, which may be converted into GPS coordinates for matching with the road segment data.”, [0124]) and (“A collision risk factor may be assigned to each version of computer instructions. The insurance provider may then adjust or update insurance policies, premiums, rates, discounts, and/or other insurance-related items based upon the collision risk factor “, [084]) and ("For example, the on-board computer 114 may store suitability data for a plurality of road segments in an area of frequent operation of the vehicle 108 for repeated use over a period of time, which stored suitability data may be updated periodically by communication with a server 140. The on-board computer 114 may then access the map data as needed.”, [0149]);
the segment attributes for the one or more paired segments; and (“A collision risk factor may be assigned to each version of computer instructions. The insurance provider may then adjust or update insurance policies, premiums, rates, discounts, and/or other insurance-related items based upon the collision risk factor “, [084]) and ("For example, the on-board computer 114 may store suitability data for a plurality of road segments in an area of frequent operation of the vehicle 108 for repeated use over a period of time, which stored suitability data may be updated periodically by communication with a server 140. The on-board computer 114 may then access the map data as needed.”, [0149]);
the connectivity attributes between the segment and the one or more paired segments. Examiner broadly interprets this limitation to include the meaning that data indicating a road “segment” is related to data pertaining to an intersection connecting those segments, … (“For example, the vehicle 108 may be proceeding along a route between origin and destination locations, which route may include a plurality of connecting road segments.”, [0151]).
Konrardy does not expressly disclose, but Leonard teaches:
determining, from the digital map data, pairs of physical road segments that intersect, (“The location determination system 140 may include a location sensor 142 configured to output an output signal indicative of the location of the vehicle 100. Based on the output signal of the location determination system 140, the electronic control unit 102 may execute logic to determine a vehicle location. The location sensor 142 may include, but is not limited to, a camera, a GPS unit, and the like.”, [033]), … note that digital map data is a part of the received GPS data, and (“The behavioral profile of a particular intersection may indicate characteristics such as, but not limited to, the specific number and type of road segments, the presence of any traffic signals, weather conditions based on the season, elevational attributes that may affect the driver's ability to view cross-traffic, geographical location, congestion, accident statistics, and the like.”, [039]), locations / other details of roads that intersect may be determined;
wherein each pair of physical road segments that intersect has a corresponding pair of segments in the road segment datastore, and examiner notes that “a pair of segments” in light of the specification [003] may include in its meaning the storage of data regarding the intersection’s (at least two) intersecting roads, … (“The electronic control unit 102 may also access a plurality of predetermined behavioral profiles that are each representative of a particular intersection. For example, in the embodiment as shown in FIG. 2 the corresponding behavioral profile indicates the intersection 200 is a four-way intersection. The behavioral profile of a particular intersection may indicate characteristics such as, but not limited to, the specific number and type of road segments, the presence of any traffic signals, weather conditions based on the season, elevational attributes that may affect the driver's ability to view cross-traffic, geographical location, congestion, accident statistics, and the like.”, [039]); and (“The processors store machine-readable instructions that, when executed, cause the one or more processors to receive a signal indicating a driver of the vehicle is attempting to make a turn at an intersection. The processors are further caused to access a behavioral profile that is representative of the intersection. The processors are also caused to develop a perception as well as a risk associated with the intersection based on the plurality of operational signals from the plurality of sensors and the behavioral profile of the intersection.”, [004]) and (“For example, the vehicle 100 may be in wireless communication (e.g., using a wireless communication system) with a remote server storing logic and data that is configured to perform at least some of the functionalities described herein.”, [026]);
each segment of the plurality of segments is included in at least one pair of segments; Examiner broadly interprets this limitation to include the meaning that (intersecting) roads are made up of segments, … (“The behavioral profile of a particular intersection may indicate characteristics such as, but not limited to, the specific number and type of road segments, the presence of any traffic signals, weather conditions based on the season, elevational attributes that may affect the driver's ability to view cross-traffic, geographical location, congestion, accident statistics, and the like. The road segments indicate if a particular intersection is a three-way intersection, a four-way intersection, a five-way intersection, a T-junction, Y-junction, and the like.”, [039]) and (“The processors are also caused to develop a perception as well as a risk associated with the intersection based on the plurality of operational signals from the plurality of sensors and the behavioral profile of the intersection.”, [004]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of this application to have modified Konrardy to incorporate the teachings of Leonard because Konrardy would be more efficient regarding the odd intersection encountered by the vehicle, then weighing the risks of that intersection in the driver’s route selection calculus, as done in Leonard (“The method also includes developing a perception as well as a risk associated with the intersection based on a plurality of operational signals from a plurality of sensors and the behavioral profile of the intersection”, see [005] of Leonard).
Regarding claims 2 and 10:
The combination of Konrardy and Leonard disclose the limitations of claims 2 and of claim 9:
Konrardy further teaches:
wherein the connectivity attributes include one or more of a ramp direction attribute, a speed limit differential attribute, a number of segments in proximity to an intersection attribute, an intersection angle attribute, movement restriction attributes, a cross traffic attribute, or a cross traffic protection attribute. (“For example, part of the operating data may include street addresses or intersections, which may be converted into GPS coordinates for matching with the road segment data. In some embodiments, some road segments may be grouped or combined into relevant segments. For example, several segments of a long and winding road between intersections may be combined to facilitate more efficient analysis”, [0124]) and (“Additionally or alternatively, the method may further include the following: identifying a location of the vehicle using a geolocation component; accessing map data containing map information regarding a plurality of road segments, which map information may include location data associated with each road segment and an indication of suitability for autonomous operation feature use associated with each road segment; and/or identifying a current road segment from the plurality of road segments based upon the identified location of the vehicle.”, [009]), a “plurality” read broadly includes a pair of (“a number of”) road segments.
Regarding claim 3:
The combination of Konrardy and Leonard disclose the limitations of claim 1:
Konrardy further teaches:
wherein the risk attribute for each segment of the plurality of segments is updated by a segment-level crash-risk prediction model executed on the plurality of segments and the connection between each pair of segments in the road segment datastore. Examiner notes that any generic, risk based, model for autonomous driving being updated reads on this, … (“The user profile may then be updated based upon the determined adjustment. Additionally or alternatively, the method may monitor operating data regarding operation of the vehicle by the autonomous operation features of the vehicle in order to determine the usage level change at least in part based upon one or more risk levels associated with the operating data”, [008]), a risk factored model may be updated.
Regarding claim 8:
The combination of Konrardy and Leonard disclose the limitations of claim 1:
Konrardy further teaches:
further comprising generating an aggregate risk attribute for the geographic area based on one or more risk attributes in the road segment datastore. Examiner notes that any autonomous vehicle which considers a plurality of risks for an area / road segment in light of the relevant geographical area reads on this (“In some embodiments, information regarding the risks associated with vehicle operation with and without the autonomous operation features may be used to determine risk categories or premiums for a vehicle insurance policy covering a vehicle with autonomous operation features, as described elsewhere herein.”, [029]) and (“a risk mapping application 143 for determining the risks associated with autonomous operation feature use along a plurality of road segments associated with an electronic map, a route determination application 144 for determining routes suitable for autonomous or semi-autonomous vehicle operation”, [045]).
Regarding claim 9:
The combination of Konrardy and Leonard disclose the limitations of claim 1:
Konrardy further teaches:
wherein the segment attributes for each segment of the plurality of segments comprise static segment attributes and dynamic segment attributes, and wherein the dynamic segment attributes comprise traffic risk attributes and a traffic volume attribute. (“The sensors (not shown) may generate data relating to weather conditions, traffic conditions, or operating status of the smart infrastructure component 188.”, [060]) and (“The optimal route may be the safest route, the route associated with a least amount of pedestrian traffic or cross walks, the quickest route, the shortest route, or the route with most highway driving.”, [0143]), “a least amount” clearly relates to traffic volume.
Regarding claims 11 and 18
The combination of Konrardy and Leonard disclose the limitations of claims 9 and 15, respectively:
Konrardy further teaches:
receiving sensor data collected by a telematics device disposed in a vehicle during a traversal of a physical road segment of the plurality of physical road segments for each traversal of a plurality of traversals of the physical road segment; and updating the traffic volume attribute for a segment in the road segment datastore that corresponds to the physical road segment based on the sensor data received for each traversal of the plurality of traversals. Examiner notes that any AV which uses sensors to update the traffic volume factor during route operation reads on this claim (“For example, part of the operating data may include street addresses or intersections, which may be converted into GPS coordinates for matching with the road segment data.”, [0124]) and (“A collision risk factor may be assigned to each version of computer instructions. The insurance provider may then adjust or update insurance policies, premiums, rates, discounts, and/or other insurance-related items based upon the collision risk factor “, [084]) and ("For example, the on-board computer 114 may store suitability data for a plurality of road segments in an area of frequent operation of the vehicle 108 for repeated use over a period of time, which stored suitability data may be updated periodically by communication with a server 140. The on-board computer 114 may then access the map data as needed.”, [0149]) and (“The optimal route may be the safest route, the route associated with a least amount of pedestrian traffic or cross walks, the quickest route, the shortest route, or the route with most highway driving.”, [0143]).
Regarding claims 12 and 19
The combination of Konrardy and Leonard disclose the limitations of claims 11 and 18, respectively:
Konrardy further teaches:
detecting, for each respective traversal of the plurality of traversals, risk-related driving attributes from the sensor data; and updating the traffic risk attributes for the segment in the road segment datastore based on the risk-related driving attributes derived for each respective traversal of the plurality of traversals. (“For example, part of the operating data may include street addresses or intersections, which may be converted into GPS coordinates for matching with the road segment data.”, [0124]) and (“A collision risk factor may be assigned to each version of computer instructions. The insurance provider may then adjust or update insurance policies, premiums, rates, discounts, and/or other insurance-related items based upon the collision risk factor “, [084]) and ("For example, the on-board computer 114 may store suitability data for a plurality of road segments in an area of frequent operation of the vehicle 108 for repeated use over a period of time, which stored suitability data may be updated periodically by communication with a server 140. The on-board computer 114 may then access the map data as needed.”, [0149]);
Regarding claim 13
The combination of Konrardy and Leonard disclose the limitations of claim 11:
Konrardy further teaches:
wherein the risk-related driving attributes include one or more of a speeding attribute, a hard braking attribute, a hard acceleration attribute, a hard cornering attribute, or a distracted driving attribute. (“Such sensors 120 may further include one or more sensors of a sensor array 225, which may include, for example, one or more cameras, accelerometers, gyroscopes, magnetometers, barometers, thermometers, proximity sensors, light sensors, Hall Effect sensors, etc. The one or more sensors of the sensor array 225 may be positioned to determine telematics data regarding the speed, force, heading, and/or direction associated with movements of the vehicle 108.”, [070]).
Regarding claim 14
The combination of Konrardy and Leonard disclose the limitations of claim 12:
Konrardy further teaches:
determining, from the risk-related driving attributes derived for each respective traversal of the plurality of traversals, a frequency of each risk-(“The times when both the driver and the vehicle have partial or joint control may also be determined and measured. These times may present higher risk, and an appropriate auto insurance premium may be higher based upon the number of instances of partial or joint control (or partial lack of control), i.e. the frequency of control transitions. Based upon how the autonomous vehicle software handles these partial or joint control situations, premiums or discounts may be adjusted accordingly based upon risk.”, [0214]).
Allowable Subject Matter
Claims 4 – 7, 16, and 17 would be allowable if rewritten or amended to overcome the additional rejection herein pursuant to 35 U.S.C. 101. The following is a statement of reasons for the indication of allowable subject matter: Independently, while the claims' limitations most recently set forth herein may individually be disclosed by the prior art, the claims as a whole are not obvious because the examiner would have to improperly use their separate limitations as a road map to combine them.
CONCLUSION
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The following prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Please see attached form 892.
Bush (US20220410882A1) – A vehicle includes a system and method of navigating the vehicle. The system includes a sensor and a processor. The sensor captures an image of a roadway. The processor focuses the sensor at a road segment selected from a plurality of road segments of the roadway using a machine learning program based on a risk of the road segment. The machine learning program is trained to focus the sensor by calculating the risk for each of the plurality of road segments of the roadway based on a hazard probability associated with each road segment and an occupancy probability associated with each road segment, selecting the road segment from the plurality of road segments based on the risk associated with the road segment, and determining a reduction in the risk for a road risk model of the roadway due to selecting the road segment.
White (US20240142259A1) - A system, a method, and a computer program product may be provided for risky road condition warning. The system may include a memory configured to store computer executable instructions and a processor configured to execute the computer executable instructions to obtain a set of vehicle features associated with a dispensing vehicle travelling along a link. The processor is configured to determine a set of risk-related features associated with the link based at least on the set of vehicle features. The processor is configured to obtain map data associated with the link. The processor is configured to determine a risk value for the link based on the set of risk-related features and the map data, and update a map database associated with the link based on the risk value.
Kislovskiy (US20180340790A1) - A transportation management system can maintain a set of driver logs for drivers operating throughout a given region, where each driver log indicates driving characteristics of a respective driver. The system can determine a destination for the respective driver operating a vehicle from an initial location to the destination, and determine a set of routes between the initial location and the destination. Based at least in part on the driving characteristics of the respective driver, the system can determine an individualized risk value for the respective driver for each route of the set of routes, and select an optimal route from the set of routes based, at least in part, on the individualized risk value for each route.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW COBB whose telephone number is (571) 272-3850. The examiner can normally be reached 9 - 5, M - F.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to call examiner Cobb as above, or to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Peter Nolan, can be reached at (571) 270-7016. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at (866) 217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call (800) 786-9199 (IN USA OR CANADA) or (571) 272-1000.
/MATTHEW COBB/Examiner, Art Unit 3661
/PETER D NOLAN/Supervisory Patent Examiner, Art Unit 3661
Prosecution Insights