DETAILED ACTION
Response to Amendment
This office action is in response to amended claims filed on 03/06/26. Claims 1-7 are amended. Claims 8-12 are newly added. Claims 1-12 are pending and addressed below.
Response to Arguments
Applicant’s arguments, see pages 7-9, filed 03/06/2026, with respect to the rejections of claims 1-7 are directed towards the claims as amended. Therefore, a new ground of rejection is made in view of Fairfield (US Patent Application 20180143643 A1 hereinafter “Fairfield”) further in view of Yun et all (U.S. Patent Application 20250377207 A1, which claims priority to Korean patent application KR1020220166380 filed on 12/02/2022, hereinafter “Yun”).
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 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.
Claims 1, 2, and 5-12 are rejected under 35 U.S.C. 103 as being unpatentable over Fairfield et al. (US Patent Application 20180143643 A1 hereinafter “Fairfield”) in view of Yun et all (U.S. Patent Application 20250377207 A1, which claims priority to Korean patent application KR1020220166380 filed on 12/02/2022, hereinafter “Yun”).
Regarding Claim 1, Fairfield discloses in figures 7 and 11
A method for creating a digital map representing one or more traffic routes (660), each traffic route including a plurality of individual traffic route segments (1120,1122,1124), the method comprising the following steps:
Fairfield further discloses in 0017
retrieving map data values representing a base map, the base map including respective traffic infrastructure information for each of the plurality of individual traffic route segments;
where it is stated “The map information may describe the shape and orientation of road features such as the road surface, lane markers, curbs, crosswalks, etc. As indicated above, roadways may be defined by segments within lanes identified by identifiers, starting points and ending points.” Fairfield further discloses
determining a respective tolerance specification for each individual traffic route segment of the plurality of individual traffic route segments based on the respective traffic infrastructure information for the individual traffic route segment,
Fairfield pertains to a method of generating a route for an autonomous vehicle based on a plurality of roadway segments and refers to the respective tolerance specifications in terms of a cost value. These cost values “may be assigned based on a priori knowledge about the vehicle's environment, for instance, from data in the map information.” (0021).
Fairfield does not teach the use of a redundant positioning system. However, Yun teaches
the respective tolerance specification representing a maximum permissible deviation, for the individual traffic route segment, between two independently, redundantly determined positions of an actual position of a vehicle,
Yun pertains to a method for localizing and mapping an autonomous vehicle with a plurality of localization technologies and discloses “In operation S110, the computing device 100 may perform the localization for the vehicle 10 based on the first localization technology to calculate a first localization value for the vehicle 10.” (0098) and “In operation S120, the computing device 100 may perform the localization for the vehicle 10 based on a second localization technology to calculate a second localization value for the vehicle 10.” (0102). Therefore, it would have been known to one of ordinary skill in the art to use the plurality of localization technologies of Yun to further define the a priori knowledge when assigning the cost value to the plurality of route segments of Fairfield, to determine a plan for maneuvering a vehicle for a predetermined period into the future.
Fairfield further discloses in figure 11 and 0071
wherein the respective tolerance specifications for at least two individual traffic route segments of the plurality of individual traffic route segments being different from one another;
where it is stated “The solid gray lane segments (such as lane segments 1130, 1132, 1134) represent lane segments having higher cost values than the solid black line segments. The dashed line lane segments (such as lane segments 1140, 1142, 1144) represent lane segments associated with no-go regions (as is shown in FIG. 2B) or that simply have higher cost values than the solid gray lane segments.”
Fairfield discloses assigning a cost to the plurality of individual traffic route segments based off of the respective traffic infrastructure information, but is silent on how the specific values are obtained. However, Yun teaches
creating the digital map by adding the determined respective tolerance specification for each of the plurality of individual traffic route segments to the respective traffic infrastructure information; and
Yun details how the different localization technologies are used to generate localization technology-specific weight maps, specifying “For example, when the vehicle 10 is located in a specific region, the computing device 100 may load the localization technology-specific weight corresponding to the specific region (for example, the first weight corresponding to the first localization technology and the second weight corresponding to the second localization technology) from the localization technology-specific weight map, and assign the first weight and the second weight to the first localization value and the second localization value calculated using the first localization technology and the second localization technology.” (0116). Therefore, it would have been known to one of ordinary skill in the art to use the localization technology-specific weight maps of Yun to further define the a priori knowledge when assigning the cost value to the plurality of route segments of Fairfield, to determine a plan for maneuvering a vehicle for a predetermined period into the future.
Fairfield further discloses providing the digital map for operating an automated vehicle in figure 15, step 1580.
Regarding claim 2, Fairfield in view of Yun disclose all of the limitations of claim 1, and Fairfield further discloses wherein the respective traffic infrastructure information for each of the plurality of individual traffic route segments at least partially includes configurations and/or usage specifications of corresponding infrastructure of the plurality of individual traffic route segments. Fairfield details “the routing system 168 and/or data 134 may store detailed map information, e.g., highly detailed maps identifying the shape and elevation of roadways, lane lines, intersections, crosswalks, speed limits, traffic signals, buildings, signs, real time traffic information, vegetation, or other such objects and information.”(0034).
Regarding claim 5, Fairfield discloses in figure 1 and 0025-0034
A device configured to create a digital map representing one or more traffic routes, each traffic route including a plurality of individual traffic route segments, the device comprising:
a computing unit (110), the computing unit configured to:
retrieve map data values (134) representing a base map, the base map including respective traffic infrastructure information for each of the plurality of individual traffic route segments;
The remainder of claim 5 is rejected in a similar manner as claim 1 above.
Regarding claim 6, Fairfield discloses in figure 1 and 0026-0028
A non-transitory machine-readable storage medium (130) on which is stored a computer program (132) for creating a digital map representing one or more traffic routes (134), each traffic route including a plurality of individual traffic route segments, the computer program, when executed by a computer, causing the computer to perform the following steps:
The remainder of claim 6 is rejected in a similar manner as claim 5 above.
Regarding claim 7, Fairfield discloses in figure 15 and 0076
A method for operating an automated vehicle (1500), comprising the following steps:
Fairfield does not teach a method for using a plurality of position determining systems. However, Yun teaches in figure 3 and 0098-0102
determining a first actual position of the automated vehicle within a traffic route segment using a first position-determining method; (S110)
determining a second actual position of the automated vehicle within the traffic route segment using a second position-determining method different from the first position-determining method, wherein the second actual position of the automated vehicle is determined independently and redundantly relative to the determining of the first actual position; (S120)
Therefore, it would have been known to one of ordinary skill in the art to incorporate the method of using two position determining systems of Yun into the method of using a priori knowledge when assigning the cost value to the plurality of route segments of Fairfield, when determining a plan for maneuvering a vehicle for a predetermined period into the future.
Additionally, Yun discloses in 0107-0108
determining a difference between the determined first actual position and the determined second actual position;
Yun details in operation S130, the computing device 100 may determine the position and orientation of the vehicle by fusing the first localization value calculated in operation S110 and the second localization value calculated in operation S120. Furthermore, Yun states “In various embodiments, the computing device 100 may calculate an average coordinate value for a coordinate value corresponding to the position of the vehicle 10 calculated based on the first localization technology and a coordinate value corresponding to the position of the vehicle 10 calculated based on the second localization technology, and determine that the calculated average coordinate value is position coordinates of the vehicle 10.”(0108). At the time of filing of the present application, resolving differences between positions obtained from redundant position determining devices was a known problem in the art, which included design needs and market pressure to solve the problem. The method described by Yun offers two identified, predictable potential solutions to the recognized problem; the two positions can be fused, or averaged. It would have been known to one of ordinary skill in the art that determining a difference between two positions is incorporated in procedures such as fusing and/or averaging. Therefore, it would have been known to one of ordinary skill in the art to integrate the method of resolving differences between positions obtained from redundant position determining devices of Yun into the method of using a priori knowledge when assigning the cost value to the plurality of route segments of Fairfield, when determining a plan for maneuvering a vehicle for a predetermined period into the future.
The following aspects of claim 7 are rejected in a similar manner to claim 1.
determining a maximum permissible deviation for the traffic route segment using a tolerance specification for the traffic route segment from a digital map, the digital map being created by:
retrieving map data values representing a base map, the base map including respective traffic infrastructure information for each of a plurality of individual traffic route segments,
determining a respective tolerance specification for each individual traffic route segment of the plurality of individual traffic route segments based on the respective traffic infrastructure information for the individual traffic route segment, the respective tolerance specification representing a maximum permissible deviation, for the individual traffic route segment, between two independently, redundantly, determined positions of an actual position of a first vehicle, wherein the respective tolerance specifications for at least two individual traffic route segments of the plurality of individual traffic route segments being different from one another, and
creating the digital map by adding the determined respective tolerance specification for each of the plurality of individual traffic route segments to the respective traffic infrastructure information;
Fairfield further discloses in figures 11 and 15
comparing the difference with the maximum permissible deviation; (1120)
determining a driving strategy based on the comparison; and (1570)
operating the automated vehicle based on the driving strategy. (1580)
Regarding Claim 8, Fairfield in view of Yun disclose all of the limitations of claim 1, and Yun further discloses in figure 3 wherein the two independently, redundantly determined positions are determined using different position-determining methods.
Regarding Claim 9, Fairfield in view of Yun disclose all of the limitations of claim 9, and Yun further discloses wherein a first one of the different position-determining methods is a GNSS-based method where it is stated “In various embodiments, the computing device 100 may calculate the first localization value for the vehicle 10 using the first localization technology for performing localization according to a GNSS/INS-based localization method.” (0099).
Regarding Claim 10, Fairfield in view of Yun disclose all of the limitations of claim 9, and Yun further discloses wherein a second one of the different position-determining methods is based on a comparison of sensor data of the vehicle with a localization map where it is stated “In various embodiments, the computing device 100 may calculate the second localization value for the vehicle 10 by using the second localization technology for performing localization according to a normal distribution transform (NDT) map-based localization method.” (0103).
Regarding Claim 11, Fairfield in view of Yun disclose all of the limitations of claim 7, and Yun further discloses wherein the first position-determining method is a GNSS- based method as detailed in the rejection of claim 9 above.
Regarding Claim 12, Fairfield in view of Yun disclose all of the limitations of claim 11, and Yun further discloses wherein the second position-determining method is based on a comparison of sensor data of the automated vehicle with a localization map as detailed in the rejection of claim 10 above.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Fairfield and Yun, further in view of Horita et all (U.S. Patent Application 20170329328 A1, hereinafter “Horita”).
Regarding Claim 3, Fairfield in view of Yun disclose all of the limitations of claim 1, but are silent as to the specifics of the respective tolerance specifications. However, Horita teaches wherein the determined respective tolerance specifications include a longitudinal tolerance and a transverse tolerance. Horita pertains to a control device mounted on a vehicle that estimates a position error of the vehicle. In figure 4 and 0068 Horita discloses the allowable longitudinal and transverse tolerances for the current route segment. Therefore, it would have been known to one of ordinary skill in the art to use the allowable longitudinal and transverse tolerances for the current route segment of Horita to further define the a priori knowledge of Fairfield when assigning a tolerance or cost to additional route segments when planning a route for an autonomous vehicle.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Fairfield and Yun, further in view of Seegmiller et all (U.S. Patent Application 20210107566 A1, hereinafter “Seegmiller”).
Regarding Claim 4, Fairfield in view of Yun disclose all of the limitations of claim 1, but are silent as to the specifics of the respective tolerance specifications. However, Seegmiller teaches wherein the determined respective tolerance specifications are additionally determined based on vehicle- and/or vehicle- movement-specific parameters. Seegmiller pertains to a method of generating candidate routes for an autonomous vehicle based on a plurality of route segments. In 0068 Seegmiller refers to “respective tolerance specifications” as “dynamic costs” when using real-time perception information to calculate a route. The real-time perception information is further described in 0028 as a combination of the sensor system 111, and the location subsystem 121. And in 0023 Seegmiller further details that the sensor system 111 consists of vehicle- and/or vehicle- movement-specific parameters like “speed sensors, odometer sensor, motion sensors (e.g., inertial measurement units (IMU), accelerometer, gyroscope, etc.).” Thus, Seegmiller discloses using vehicle- and/or vehicle- movement-specific parameters to determine respective tolerance specifications. Therefore, it would have been known to one of ordinary skill in the art to use the vehicle- and/or vehicle- movement-specific parameters of Seegmiller to further define the a priori knowledge of Fairfield when assigning a tolerance or cost to a route segment when planning a route for an autonomous vehicle.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Nathan Daniel Neckel whose telephone number is (571)272-9537. The examiner can normally be reached M-F, 7-3.
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/NATHAN DANIEL NECKEL/Examiner, Art Unit 3656
/WADE MILES/Supervisory Patent Examiner, Art Unit 3656