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 .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 21 January 2025 is being considered by the examiner.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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 nonobviousness.
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 1-2, 10, 13, 15, 19-20, 28, 32, 39, 43, and 82 are rejected under 35 U.S.C. 103 as being unpatentable over Nusser et al. (US Publication 2016/0267792 A1) in view of Ko (US Publication 2020/0339138 A1).
Regarding claim 1, Nusser teaches a method comprising: determining, based at least in part from data collected by at least one user device located within an automobile traversing along a road comprising one or more curved portions, one or more kinematic properties of the automobile (Nusser: Para. 4; a smart phone or a navigation system, may have sensors that are adapted for detecting an event, such as a road sign or a curve, that is imminent for a vehicle); determining, based at least in part on the data collected, a curve geometry of an investigated curved portion selected from the one or more curved portions (Nusser: Para. 12, 62; event may be a road sign, a curve; using the control angle, for ascertaining an imminent change in a course of roadway, for instance a sharp curve); determining, based at least in part on the data collected, an advisory driving speed for the investigated curved portion (Nusser: Para. 61; sensing road sign via the optical sensor, and for outputting a first event message indicative of an imminent speed limit).
Nusser doesn’t explicitly teach determining, based at least in part on the data collected, desired curve signage for display relative to the investigated curved portion.
However Ko, in the same field of endeavor, teaches determining, based at least in part on the data collected, desired curve signage for display relative to the investigated curved portion (Ko: Para. 269; the augmented reality providing unit may generate a curve guidance object and map the generated curve guidance object to the virtual 3D space to thereby generate the augmented reality screen).
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) with a reasonable expectation of success because generating the first curve section guidance objects representing the degree of risk and output the generated first curve section guidance objects through the augmented reality (Ko: Para. 275, Fig. 17A).
Regarding claim 2, Nusser teaches the method of claim 1, wherein the data collected is selected from a group consisting of data indicative of a speed of the user device, data indicative of a global positioning system (GPS) location of the user device, data comprising inertial measurement unit (IMU) data of the user device, video data of the investigated curved portion, and a combination thereof (Nusser: Para. 12; a smart phone or a navigation system equipped with a camera or an acceleration sensor that is mounted in the vehicle).
Regarding claim 10, Nusser doesn’t explicitly teach wherein determining the curve geometry comprises: determining a point of curvature of the investigated curved portion; determining a point of tangent of the investigated curved portion; determining a curve radius for of investigated curved portion; determining a deviation angle of the investigated curved portion; and determining a superelevation of the investigated curved portion.
However Ko, in the same field of endeavor, teaches wherein determining the curve geometry comprises: determining a point of curvature of the investigated curved portion (Ko: Para. 39; determining at least three points where the electronic apparatus would be positioned at future time points according to the measured current moving speed from the curve link; calculating a radius of a circumscribed circle passing through the at least three the determined points); determining a point of tangent of the investigated curved portion (Ko: Para. 50, Fig. 14A-B); determining a curve radius for of investigated curved portion (Ko: Para. 39; calculating a radius of a circumscribed circle passing through the at least three the determined points); determining a deviation angle of the investigated curved portion (Ko: Para. 50; computing an angle formed by the determined third point and the two end points of the line segment connecting the two or more points); and determining a superelevation of the investigated curved portion (Ko: Para. 92; the slope information of the road corresponding to the link may include superelevation information (Cant) representing a gradient of a width concatenated on the horizontal line of the road).
Ko teaches determining three points. One point being connected to two different future points and the angle created by the triangle being determined (Ko: Para. 50). It is obvious to one of ordinary skill in the art that a point of tangent for the investigated curved portion could be easily identified with the information from Ko.
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) with a reasonable expectation of success because generating the first curve section guidance objects representing the degree of risk and output the generated first curve section guidance objects through the augmented reality (Ko: Para. 275, Fig. 17A).
Regarding claim 13, Nusser teaches the method of claim 10, wherein the curve radius is based, at least in part, on GPS data and/or roadway centerline data in the data collected (Nusser: Para. 39; measuring a current position and a current moving speed of an electronic apparatus using a received global positioning system (GPS) signal; calculating a radius of a circumscribed circle passing through the at least three the determined points).
Regarding claim 15, Nusser teaches the method of claim 10, wherein the deviation angle is based, at least in part, on GPS data and/or roadway centerline data in the data collected (Nusser: Para. 39, 188; measuring a current position and a current moving speed of an electronic apparatus using a received global positioning system (GPS) signal; compute an angle formed by an extension line of a line segment connecting the first position and the third position, and an extension line of a line segment connecting the second position and the third position).
Regarding claim 19, Nusser doesn’t explicitly teach wherein determining the advisory driving speed is based, at least in part, on the curve radius and the superelevation of the investigated curved portion.
However Ko, in the same field of endeavor, teaches wherein determining the advisory driving speed is based, at least in part, on the curve radius and the superelevation of the investigated curved portion (Ko: Para. 131; provide guidance of speed which is safe for driving the curve section positioned at the front of the moving body to the user).
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) with a reasonable expectation of success because generating the first curve section guidance objects representing the degree of risk and output the generated first curve section guidance objects through the augmented reality (Ko: Para. 275, Fig. 17A).
Regarding claim 20, Nusser doesn’t explicitly teach wherein the curve radius and the superelevation of the investigated curved portion are determined based, at least in part, on the data collected.
However Ko, in the same field of endeavor, teaches wherein the curve radius and the superelevation of the investigated curved portion are determined based, at least in part, on the data collected (Ko: Para. 130, 148, 177; data to which actual moving characteristics of the vehicle; F=(mv^2)/r×c; superelevation of the curve section).
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) with a reasonable expectation of success because generating the first curve section guidance objects representing the degree of risk and output the generated first curve section guidance objects through the augmented reality (Ko: Para. 275, Fig. 17A).
Regarding claim 28, Nusser teaches the method of claim 1 further comprising displaying a list of the desired curve signage (Nusser: Para. 49, 61, Fig. 2; one aggregated event message A, B, C, D or E each is assigned to the events; event messages output by other mobile terminal devices; a display screen of terminal device to be visible to a driver).
Nusser doesn’t explicitly teach wherein displaying comprises at least one of: displaying a list of coordinates and a desired sign for each of the coordinates, each of the coordinates corresponding to a geographic location; or displaying a map, the map comprising the investigated curved portion and the desired curve signage.
However Ko, in the same field of endeavor, teaches wherein displaying comprises at least one of: displaying a list of coordinates and a desired sign for each of the coordinates, each of the coordinates corresponding to a geographic location; or displaying a map, the map comprising the investigated curved portion and the desired curve signage (Ko: Para. 275, Fig. 17A; generate first curve section guidance objects representing the degree of risk of the first risk level, and may output the generated first curve section guidance objects through the augmented reality).
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) with a reasonable expectation of success because generating the first curve section guidance objects representing the degree of risk and output the generated first curve section guidance objects through the augmented reality (Ko: Para. 275, Fig. 17A).
Regarding claim 32, Nusser teaches the method of claim 1 further comprising: determining, based at least in part on the data collected, existing signage currently displayed relative to the investigated curved portions (Nusser: Para. 47; a camera system for detecting road signs or with acceleration sensors for detecting braking maneuvers or curves); comparing the existing signage to the desired curve signage (Nusser: Para. 16; comparing an aggregated event message to aggregated event messages in a known vicinity of this aggregated event message); and generating, based at least in part on the comparing, a list of signs to be added and/or to be removed from the existing signage so future signage displayed relative to the investigated curved portion matches the desired curve signage (Nusser: Para. 12; event may be a road sign, a curve; event message may be a warning that is generated on the mobile terminal device in response to an imminent event; aggregated event message may be understood to be an event message that results when at least two different event messages are combined using predetermined aggregation functions).
Regarding claim 39, Nusser teaches a method comprising: determining, based at least in part from data collected by a set of user devices, one or more of the user devices from the set of user devices located within different automobiles, each of the automobiles having driven along one or more roads comprising one or more curved portions, kinematic properties of the automobiles (Nusser: Para. 4; a smart phone or a navigation system, may have sensors that are adapted for detecting an event, such as a road sign or a curve, that is imminent for a vehicle); determining, based at least in part on the data collected, a curve geometry for the curved portions (Nusser: Para. 12, 62; event may be a road sign, a curve; using the control angle, for ascertaining an imminent change in a course of roadway, for instance a sharp curve); determining, based at least in part on the data collected, advisory driving speeds for the curved portions (Nusser: Para. 61; sensing road sign via the optical sensor, and for outputting a first event message indicative of an imminent speed limit).
Nusser doesn’t explicitly teach determining, based at least in part on the data collected, desired curve signage for display at the curved portions; displaying a list of the desired curve signage; and generating an output indicative of the advisory driving speeds.
However Ko, in the same field of endeavor, teaches determining, based at least in part on the data collected, desired curve signage for display at the curved portions (Ko: Para. 269; the augmented reality providing unit may generate a curve guidance object and map the generated curve guidance object to the virtual 3D space to thereby generate the augmented reality screen); displaying a list of the desired curve signage (Ko: Para. 269; display the generated augmented reality screen); and generating an output indicative of the advisory driving speeds (Ko: Para. 39, 131; provide guidance of speed which is safe for driving the curve section positioned at the front of the moving body to the user; outputting guidance on whether or not the vehicle which would move on a curved road positioned on a front section at the current moving speed would be dangerous to a user according to a comparison result).
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) with a reasonable expectation of success because generating the first curve section guidance objects representing the degree of risk and output the generated first curve section guidance objects through the augmented reality (Ko: Para. 275, Fig. 17A).
Regarding claim 43, Nusser teaches a system for improving curve signage comprising: one or more processors, individually and/or collectively, configured to execute code causing the system to: perform the method of claim 1 (Nusser: Para. 32; a computer program product having program code, that may be stored on a machine-readable medium).
Regarding claim 82, Nusser teaches a system comprising: one or more processors, individually and/or collectively, configured to execute code causing the system to: perform the method of claim 39 (Nusser: Para. 32; a computer program product having program code, that may be stored on a machine-readable medium).
Claims 17, 23-24, and 40-41 are rejected under 35 U.S.C. 103 as being unpatentable over Nusser et al. (US Publication 2016/0267792 A1) in view of Ko (US Publication 2020/0339138 A1) and in further view of Yu et al. (US Publication 2022/0194414 A1).
Regarding claim 17, Nusser doesn’t explicitly teach wherein the superelevation is based, at least in part, on: speed data in the data collected.
However Ko, in the same field of endeavor, teaches wherein the superelevation is based, at least in part, on: speed data in the data collected (Ko: Para. 130, 148-149, 177; data to which actual moving characteristics of the vehicle; the superelevation of the curve section is large, the weight computing unit may compute the second weight as the value smaller than ‘1’; centrifugal force computed through Equation 2 becomes smaller than centrifugal force before reflecting the second weight; F=(mv^2/r)xc).
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) with a reasonable expectation of success because generating the first curve section guidance objects representing the degree of risk and output the generated first curve section guidance objects through the augmented reality (Ko: Para. 275, Fig. 17A).
Nusser and Ko doesn’t explicitly teach a path radius and ball-bank indicator (BBI) determined, based at least in part, on the data collected.
However Yu, in the same field of endeavor, teaches a path radius and ball-bank indicator (BBI) determined, based at least in part, on the data collected (Yu: Para. 42, 94, 115; applying lateral force indicates, based on the required slip angles of the wheels and the current velocity of the autonomous vehicle, what amount of lateral force is needed for the autonomous vehicle to move along the defined trajectory curve).
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) and the autonomous vehicle calculated slip angles (Yu: Para. 115) with a reasonable expectation of success because an autonomous vehicle using IMU and velocity data can calculate the required slip angles of the wheels and the cornering stiffness based on the turning radius to successfully traverse a curved trajectory (Yu: Para. 42, 94, 115).
Regarding claim 23, Nusser doesn’t explicitly teach wherein two of the one or more kinematic properties comprise: a path radius taken by the automobile when traversing along the investigated curved portion.
However Ko, in the same field of endeavor, teaches wherein two of the one or more kinematic properties comprise: a path radius taken by the automobile when traversing along the investigated curved portion (Ko: Para. 28, 143, 145; compute centrifugal force to be applied to the vehicle using a radius of the generated circumscribed circle and the speed of the vehicle at the reference time point; compute a moving distance after the first time lapses from the current position by reflecting current speed of the vehicle and the first time to Equation 1; S=V*T).
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) with a reasonable expectation of success because generating the first curve section guidance objects representing the degree of risk and output the generated first curve section guidance objects through the augmented reality (Ko: Para. 275, Fig. 17A).
Nusser and Ko doesn’t explicitly teach a BBI of the automobile when traversing along the investigated curved portion.
However Yu, in the same field of endeavor, teaches a BBI of the automobile when traversing along the investigated curved portion (Yu: Para. 42, 94, 115; applying lateral force indicates, based on the required slip angles of the wheels and the current velocity of the autonomous vehicle, what amount of lateral force is needed for the autonomous vehicle to move along the defined trajectory curve).
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) and the autonomous vehicle calculated slip angles (Yu: Para. 115) with a reasonable expectation of success because an autonomous vehicle using IMU and velocity data can calculate the required slip angles of the wheels and the cornering stiffness based on the turning radius to successfully traverse a curved trajectory (Yu: Para. 42, 94, 115).
Regarding claim 24, Nusser and Ko doesn’t explicitly teach wherein the path radius is based, at least in part, on speed data and IMU data in the data collected.
However Yu, in the same field of endeavor, teaches wherein the path radius is based, at least in part, on speed data and IMU data in the data collected (Yu: Para. 42, 94, 115; an inertial measurement unit (IMU) and a real-time kinematic (RTK) unit; current velocity; applying lateral force indicates, based on the required slip angles of the wheels and the current velocity of the autonomous vehicle, what amount of lateral force is needed for the autonomous vehicle to move along the defined trajectory curve).
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) and the autonomous vehicle calculated slip angles (Yu: Para. 115) with a reasonable expectation of success because an autonomous vehicle using IMU and velocity data can calculate the required slip angles of the wheels and the cornering stiffness based on the turning radius to successfully traverse a curved trajectory (Yu: Para. 42, 94, 115).
Regarding claim 40, Nusser doesn’t explicitly teach determining the curve geometries comprises: determining a point of curvature of the each of the curved portions; determining a point of tangent of the each of the curved portions; determining a curve radius for of the each of the curved portions; determining a deviation angle of the each of the curved portions; and determining a superelevation of each of the curved portions wherein the superelevations are based, at least in part, on: speed data in the data collected; and a path radius and BBI determined, based at least in part, on the data collected.
However Ko, in the same field of endeavor, teaches determining the curve geometries comprises: determining a point of curvature of the each of the curved portions (Ko: Para. 39; determining at least three points where the electronic apparatus would be positioned at future time points according to the measured current moving speed from the curve link; calculating a radius of a circumscribed circle passing through the at least three the determined points); determining a point of tangent of the each of the curved portions (Ko: Para. 50, Fig. 14A-B; Ko teaches determining three points. One point being connected to two different future points and the angle created by the triangle being determined (Ko: Para. 50). It is obvious to one of ordinary skill in the art that a point of tangent for the investigated curved portion could be easily identified with the information from Ko.); determining a curve radius for of the each of the curved portions (Ko: Para. 39; calculating a radius of a circumscribed circle passing through the at least three the determined points); determining a deviation angle of the each of the curved portions (Ko: Para. 50; computing an angle formed by the determined third point and the two end points of the line segment connecting the two or more points); and determining a superelevation of each of the curved portions (Ko: Para. 92; the slope information of the road corresponding to the link may include superelevation information (Cant) representing a gradient of a width concatenated on the horizontal line of the road); wherein the superelevations are based, at least in part, on: speed data in the data collected (Ko: Para. 148-149, 177; the superelevation of the curve section is large, the weight computing unit may compute the second weight as the value smaller than ‘1’; centrifugal force computed through Equation 2 becomes smaller than centrifugal force before reflecting the second weight; F=(mv^2/r)xc).
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) with a reasonable expectation of success because generating the first curve section guidance objects representing the degree of risk and output the generated first curve section guidance objects through the augmented reality (Ko: Para. 275, Fig. 17A).
Nusser and Ko doesn’t explicitly teach a path radius and BBI determined, based at least in part, on the data collected.
However Yu, in the same field of endeavor, teaches a path radius and BBI determined, based at least in part, on the data collected (Yu: Para. 42, 94, 115; applying lateral force indicates, based on the required slip angles of the wheels and the current velocity of the autonomous vehicle, what amount of lateral force is needed for the autonomous vehicle to move along the defined trajectory curve).
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) and the autonomous vehicle calculated slip angles (Yu: Para. 115) with a reasonable expectation of success because an autonomous vehicle using IMU and velocity data can calculate the required slip angles of the wheels and the cornering stiffness based on the turning radius to successfully traverse a curved trajectory (Yu: Para. 42, 94, 115).
Regarding claim 41, Nusser doesn’t explicitly teach wherein the kinematic properties comprise: a path radius taken by the automobiles when traversing along the curved portions.
However Ko, in the same field of endeavor, teaches wherein the kinematic properties comprise: a path radius taken by the automobiles when traversing along the curved portions (Ko: Para. 28, 143, 145; compute centrifugal force to be applied to the vehicle using a radius of the generated circumscribed circle and the speed of the vehicle at the reference time point; compute a moving distance after the first time lapses from the current position by reflecting current speed of the vehicle and the first time to Equation 1; S=V*T).
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) with a reasonable expectation of success because generating the first curve section guidance objects representing the degree of risk and output the generated first curve section guidance objects through the augmented reality (Ko: Para. 275, Fig. 17A).
Nusser and Ko doesn’t explicitly teach a BBI of the automobiles when traversing along the curved portions.
However Yu, in the same field of endeavor, teaches a BBI of the automobiles when traversing along the curved portions (Yu: Para. 42, 94, 115; applying lateral force indicates, based on the required slip angles of the wheels and the current velocity of the autonomous vehicle, what amount of lateral force is needed for the autonomous vehicle to move along the defined trajectory curve).
It would have been obvious to one having ordinary skill in the art to modify the speed limit message for an upcoming curve (Nusser: Para. 12, 62) with the augmented reality display for an upcoming curve (Ko: Para. 269) and the autonomous vehicle calculated slip angles (Yu: Para. 115) with a reasonable expectation of success because an autonomous vehicle using IMU and velocity data can calculate the required slip angles of the wheels and the cornering stiffness based on the turning radius to successfully traverse a curved trajectory (Yu: Para. 42, 94, 115).
Allowable Subject Matter
Claims 21, 27, and 42 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LAURA E LINHARDT whose telephone number is (571) 272-8325. The examiner can normally be reached on M-TR, M-F: 8am-4pm.
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/L.E.L./Examiner, Art Unit 3663
/ANGELA Y ORTIZ/Supervisory Patent Examiner, Art Unit 3663
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