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 .
Response to Arguments
Applicant’s arguments, see pages 5-8, filed 07/21/2026, with respect to the rejections under 35 USC 112(b) and 35 USC 101 have been fully considered and are persuasive in light of the amended claims. The rejections of 04/22/2026 have been withdrawn.
Applicant's remaining arguments filed 02/11/2026 have been fully considered but they are not persuasive. The applicant makes the following arguments:
Paragraphs [0004], [0013], and [0014] provide support for the amendments to the claims, which thus should not be rejected under 35 USC 112(a).
While Gustafsson teaches use of an improved map for navigation, Gustafsson fails to teach using location-specific sensor accuracy models to, for example, adjust sensor fusion weightings or detection thresholds in real-time within a vehicle’s control system.
The additionally applied art further fails to teach the use of location-specific sensor accuracy models to adjust on-board sensor fusion parameters or control actions.
Regarding argument A: Paragraphs [0013] and [0014] disclose the use of algorithms in signal processing to contribute to map accuracy and the use of sensor models as a map layer, respectively. Neither of these actions fall within the broadest reasonable interpretation of “automatically controlling operation of the vehicle”. Additionally, the specification provides no support for either an autonomous vehicle or for performing control of a vehicle based on the maps.
Regarding argument B: The applicant’s argument is based around actions such as “adjust sensor fusion weightings or detection thresholds”; these actions are neither recited in the claimed invention nor disclosed in the specification. Paragraphs [0052] and [0067] of Gustafsson teach, respectively, obtaining a radar reading based on an obstacle and autonomous control of a vehicle based on high-precision radar maps; this corresponds to controlling operation of a vehicle based on determining proximity of an object as claimed herein.
Regarding argument C: As discussed above, this feature is taught by Gustafsson, and thus this argument is moot.
Regarding argument A: The amendments to the claims are taught by Gustafsson et al., as discussed in further detail below.
Regarding argument B: As discussed below, the additionally recited elements of a vehicle and sensors are recited at so high a level of generality as to amount to no more than linking the abstract idea to the field of use of vehicles. Similarly, the back-end server is recited at so high a level of generality as to amount to no more than instructions to perform the abstract idea on a computer. These recited elements are all well-understood, routine, and conventional, and thus similarly fail to provide significantly more.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-6 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. While the specification discloses determining existence of an object in proximity to the vehicle, the specification fails to disclose internal vehicle systems which use the determination to control the vehicle. Claims 2-6 are dependent on claim 1 and thus contain new matter for the same reasons.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 2, and 4 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Gustafsson et al. (US 20210190537, previously cited).
Claim 1.
Gustafsson et al. teaches:
at a back-end server
(Gustafsson – [0048]) “The control system 20 may be arranged in a remote server in communication with the vehicles 24a, 24b, as a so-called cloud-solution.”
receiving sensor data from sensors a vehicle during a first journey of the vehicle
(Gustafsson – Abstract) “The method comprises obtaining positioning data and sensor data of each passage from the at least one road vehicle.”
setting location-dependent sensor data by associating the sensor data with a geographic position in an environment map
(Gustafsson – Abstract) “the method comprises determining a new plurality of longitudinal positions of each road vehicle for each passage by applying the estimated longitudinal error on each corresponding obtained longitudinal position, and applying the determined new plurality of longitudinal positions on associated sensor data in order to generate a first layer of a map representation of the surrounding environment along the road portion.”
(Gustafsson – [0047]) “each vehicle is preferably equipped with a localization system for monitoring a geographical position of the vehicle, i.e., a system capable of outputting a longitudinal coordinate, a lateral coordinate and a heading direction of the vehicle”
identifying detection accuracies of the sensors based on the location-dependent sensor data
(Gustafsson – Abstract) “the method comprises forming a sub-map representation of the surrounding environment at each obtained longitudinal position based on the obtained sensor data, and estimating a longitudinal error for each obtained longitudinal position within each segment.”
entering into the environment map the detection accuracies as a plurality of sensor models to create an enhanced environment map, each of the plurality of sensor models associated with a different position in the enhanced environment map
(Gustafsson – Abstract) “the method comprises determining a new plurality of longitudinal positions of each road vehicle for each passage by applying the estimated longitudinal error on each corresponding obtained longitudinal position, and applying the determined new plurality of longitudinal positions on associated sensor data in order to generate a first layer of a map representation of the surrounding environment along the road portion.”
subsequently receiving additional data associated with additional journeys of the vehicle, the data relating to multiple journeys of the vehicle and being communicated from the vehicle to the back-end server and used by the back-end server to fine-tune the plurality of sensor models to increase the accuracy of the models
(Gustafsson – Abstract) “The method comprises obtaining positioning data and sensor data of each passage from the at least one road vehicle.”
(Gustafsson – [0035]) “the digital maps may be updated/generated based on one road vehicle making multiple passages along the same road portion”
providing the enhanced environment map to at least one vehicle
(Gustafsson – [0011]) “This object is achieved by means of provide a method for generating and updating digital maps, a control system for generating and updating digital maps, and a vehicle utilizing these maps for navigation”
when the vehicle is operating at a given location, using a sensor model from the plurality of sensor models corresponding to the location in the map when determining whether an object is present in proximity to the vehicle at the location, and automatically controlling operation of the vehicle accordingly
(Gustafsson – Abstract) “the method comprises determining a new plurality of longitudinal positions of each road vehicle for each passage by applying the estimated longitudinal error on each corresponding obtained longitudinal position, and applying the determined new plurality of longitudinal positions on associated sensor data in order to generate a first layer of a map representation of the surrounding environment along the road portion.”
(Gustafsson – [0052]) “the sensor data is acquired/obtained from an active sensor system, wherein the active sensor system is arranged to transmit a signal and receive the signal reflected off objects within the surrounding environment of the road vehicle(s)”
(Gustafsson – [0067]) “the vehicle 1 is capable of autonomous or semi-autonomous navigation based on radar maps and real-time radar data is provided. This is enabled by the high-precision radar maps which may be generated by means of the methods and control systems (e.g., ref. 20 FIG.2) discussed in the foregoing.”
Claim 2.
Gustafsson et al. teaches all the limitations of claim 1, as discussed above. Gustafsson et al. further teaches:
wherein entering the detection accuracies as sensor models into the environmental map comprises entering the sensor models into the environment map as an additional map layer
(Gustafsson – Abstract) “the method comprises determining a new plurality of longitudinal positions of each road vehicle for each passage by applying the estimated longitudinal error on each corresponding obtained longitudinal position, and applying the determined new plurality of longitudinal positions on associated sensor data in order to generate a first layer of a map representation of the surrounding environment along the road portion.”
Claim 4.
Gustafsson et al. teaches all the limitations of claim 1, as discussed above. Gustafsson et al. further teaches:
wherein setting the location-dependent sensor data comprises setting the location-dependent sensor data based on localization and/or tracking and/or fusion of the sensor data
(Gustafsson – Abstract) “the method comprises forming a sub-map representation of the surrounding environment at each obtained longitudinal position based on the obtained sensor data, and estimating a longitudinal error for each obtained longitudinal position within each segment.”
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gustafsson et al. as applied to claim 1 above, and further in view of Moore et al. (US 20200379124, previously cited).
Claim 3.
Gustafsson et al. teaches all the limitations of claim 1, as discussed above. Gustafsson et al. further teaches:
wherein the sensor models contain a factor for the accuracy in radial, azimuthal,
(Gustafsson – [0045]) “the above described embodiment focuses on the longitudinal error, i.e. δx, in some embodiments, the method comprises additionally, or alternatively determining a lateral error δy and/or a heading error Θx in analogous manner.”
Gustafsson et al. does not explicitly teach a height direction or probabilities; however, Moore et al. teaches:
wherein the sensor models contain a factor for the accuracy in radial, azimuthal, and height directions, and probabilities for false-positive detections and false-negative detections
(Moore – [0070]) “a parameter such as percent of probability or percent of quality”
(Moore – [0071]) “Each can map on to visual or operational clues such as drone direction/height/Speed and % of quality of detection as mentioned above.”
It would have been obvious to one possessing ordinary skill in the art to combine these teachings, modifying the map updating system of Gustafsson et al. to take into account the additional parameters of Moore et al. One would have been motivated to do this because it allows for increased correct detection when sensor coverage is less than 100% (Moore – [0070]).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gustafsson et al. as applied to claim 4 above, and further in view of Zhang et al. (CN 104964683, previously cited).
Claim 5.
Gustafsson et al. teaches all the limitations of claim 4, as discussed above. Gustafsson et al. does not explicitly teach the use of a Kalman filter; however, Zhang et al. teaches:
wherein setting the location-dependent sensor data comprises fusion filters, static or dynamic environment occupancy maps, or Kalman filters performing the localization and/or tracking and/or fusion
(Zhang – [0008]) “the closed-loop correction method for creating an indoor environment map provided by the present invention adopts a state estimation algorithm based on a Kalman filter to correct the robot posture obtained by the Gmapping algorithm”
It would have been obvious to one possessing ordinary skill in the art to combine these teachings, modifying the map updating system of Gustafsson et al. such that it uses a Kalman filter in the fashion of Zhang et al. One would have been motivated to do this in order to compensate for errors caused by the use of low-precision sensors (Zhang – [0035]).
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gustafsson et al. as applied to claim 1 above, and further in view of Li et al. (CN 111784659, previously cited).
Claim 6.
Gustafsson et al. teaches all the limitations of claim 1, as discussed above. Gustafsson et al. does not explicitly teach the use of a neural network; however, Li et al. teaches:
wherein setting the location-dependent sensor data comprises classifying the sensor data using a neural network
(Li – [0103]) “the fusion features of the image to be tested are input into the neural network model, and the depth of the obstacle from the camera in the image to be tested output by the neural network model is obtained.”
It would have been obvious to one possessing ordinary skill in the art before the effective filing date to combine these teachings, modifying the sensors (such as cameras, as disclosed in paragraph [0035]) used in the map updating system of Gustafsson et al. with the neural network of Li et al. One would have been motivated to do this because the use of a neural network model “improv[es] the accuracy and robustness of image detection” (Li – [0103]).
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 SARAH A MUELLER whose telephone number is (703)756-4722. The examiner can normally be reached M-Th 7:30-12:00, 1:00-5:30; F 8:00-12:00.
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/S.A.M./Examiner, Art Unit 3669
/NAVID Z. MEHDIZADEH/Supervisory Patent Examiner, Art Unit 3669
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