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 Amendment
The amendment filed November 13, 2025 has been entered. Claims 1, 4-12, 14, and 15 remain pending in the application. Applicant’s amendments to the Specification, and
Claims have overcome specification objection and 112(f) rejections previously set forth in the Non‐Final Office Action mailed August 13, 2025.
Response to Arguments
Applicant's arguments filed November 13, 2025 have been fully considered.
[1] Rejection Under 35 U.S.C. § 101
Applicant amended the independent claims to include the patent eligible feature of claim 4, and added description of non-transitory for claim 14. Rejections under 35 U.S.C. § 101 are withdrawn.
[2] Rejection Under 35 U.S.C. § 102
Applicant’s arguments with respect to claim(s) 1, 2, 4-6, 8, 9, and 12-15 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Applicant argued that Elrofai does not disclose the amended independent claims.
In this office action, the independent claims are rejected under 35 U.S.C. § 103 over Posch in view of Liu.
Claim Objection
Applicant is advised that should claim 1 be found allowable, claim 4 will be objected to under 37 CFR 1.75 as being a substantial duplicate thereof. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
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.
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.
Claim(s) 1, 4, 5, 6, 8, 12, 14, 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Posch et al. (US 20160221575 A1) in view of Liu et al. (US 20190163181 A1).
Regarding claim 1, Posch discloses:
A computer-implemented method for testing a driver assistance system of an ego vehicle on the basis of test drive data, comprising {paragraph [0024]: optimization of driver assistance systems by simulation in a virtual environment or test field, [0013]: a large number of test drives with different drivers, [0171]: analysis for an event during a test drive}:
assigning attributes to other vehicles captured in the test drive data and located in the immediate surroundings of the ego vehicle, wherein the attributes specify respective relative positions of the other vehicles in relation to the ego vehicle at a point in time within the test drive data and wherein the attributes are associated with an associated time point {Fig. 18, [0096] discloses attributes to other vehicles captured in the test drive data and located in the immediate surroundings of the ego vehicle including the relative position. [0171]: the time profile of the vehicle parameters “vehicle speed” and “steering angle of the steering wheel” as well as the time profile of the environmental parameters},
checking the test drive data for an occurrence of elementary lateral maneuvers which are in each case characterized by a change in position of the ego vehicle or one of the other vehicles perpendicular to the course of the road {[0060]: vehicle parameter… lateral acceleration, [0061]: the lateral position of one other vehicle},
elementary longitudinal maneuvers which are in each case characterized by a change in the distance to a vehicle driving in front of and/or behind the ego vehicle or one of the other vehicles, particularly in the same lane {[0061]: the longitudinal position of at least one other vehicle, particularly of the leading vehicle, in relation to one's own vehicle, the relative speed of at least one other vehicle, particularly of the leading vehicle, in relation to one's own vehicle, the relative acceleration of at least one other vehicle, particularly of the leading vehicle. Examiner notes that when there is longitudinal acceleration, change in the distance occurs},
wherein the elementary maneuvers are selected from a list of predefined elementary maneuvers and wherein the occurrence of elementary maneuvers is also associated with at least one associated point in time {[0061], [0057]: aspect with respect to a vehicle with the at least one driver assistance system, particularly a reduction in speed that is appropriate to the driving situation, a braking deceleration that is appropriate to the driving situation, and/or a steering angle that is appropriate to the driving situation},
conducting test runs on a test bed using the test drive data {[0012]: tested, for example, in HIL (Hardware in the Loop) environments (test bed) and in the automobile under all possible environmental conditions}.
Posch does not disclose:
[1] wherein models for recognizing elementary maneuvers in test drive data which have been generated by machine learning on the basis of test drive data already having been classified with respect to elementary maneuvers are used when checking for elementary maneuvers.
[2] identifying an occurrence of predefined scenarios in the test drive data based on the elementary maneuvers having occurred wherein the predefined scenarios are characterized by a constellation of elementary maneuvers and attributes.
[3] wherein the test drive data is searched exclusively for those attributes and/or elementary maneuvers which are contained in the predefined scenarios.
[4] analyzing the driving behavior of the driver assistance system in the identified scenarios based on the test runs.
[1] Liu teaches test drive data in Fig. 6, paragraph [0004]: autonomous vehicle motion planner can be tested with realistic simulated data from physical experiments; model for recognizing elementary maneuvers already classified in [0015]: can model the vehicle behaviors that would be performed by actual vehicles in the real world, including lane change, overtaking, acceleration behaviors, and the like; generated by machine learning in [0026]: the specific behavior of a simulated dynamic vehicle, as represented in the rule-based process and corresponding data structures, can be modeled using the target position and direction of the simulated dynamic vehicle along with the target speed of the simulated dynamic vehicle. Examiner notes that being represented in the rule-based process and corresponding data structures imply modeling generated by machine learning.
[2] Liu teaches identifying occurrence of predefined scenarios characterized by elementary maneuvers and attributes in [0003]: The logic in the motion planner must be able to anticipate, detect, and react to a variety of different driving scenarios, such as the actions of the dynamic vehicles in proximity to the autonomous vehicle.
[3] Liu teaches searching test drive data exclusive per the predefined scenario in Fig. 6, [0031]: enable the playback of the recorded vehicle motion data to highlight or isolate the analysis of the performance of the control module 340 and motion planner 330 in various simulated driving and traffic scenarios. Examiner notes that isolating data means searching exclusively.
[4] Liu teaches analyzing the driving behavior of the driver assistance system in [0004]: to test, evaluate, or otherwise analyze autonomous vehicle motion planning systems, which can be used in real autonomous vehicles in actual driving environments. Examiner notes that autonomous driving includes use of driver assistance system.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the machine learning model, scenario identifying, searching relevant test drive data and analyzing driver assistance system features of Liu with the described invention of Posch in order to utilize artificial intelligence in analyzing autonomous vehicle driving based on real world data.
Similar reasoning applies to claims 14, 15.
Regarding claim 4, which depends from claim 1, Liu teaches: models for recognizing elementary maneuvers in test drive data which have been generated by machine learning on the basis of test drive data already having been classified with respect to elementary maneuvers are used when checking for elementary maneuvers {Fig. 6, [0004], [0015], [0026]}.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the machine learning model feature of Liu with the described invention of Posch in order to utilize artificial intelligence in analyzing autonomous vehicle driving based on real world data.
Regarding claim 5, which depends from claim 1, Posch discloses: wherein the list includes at least one of the following elementary lateral maneuver groups: lane change to left, lane change to right, in-lane driving, out-of-lane driving, veer to right, veer to left {[0051]: remaining in lane, lane change}.
Regarding claim 6, which depends from claim 1, Posch discloses: wherein the list includes at least one of the following elementary longitudinal maneuver groups: initial start, gap opening, gap closing, vehicle following, clear-lane driving, stopping {[0051]: following to vehicle stop, following from start}.
Regarding claim 8, which depends from claim 1, Posch discloses: wherein the attributes indicate whether another vehicle is located in the same lane or in a right or left lane in relation to the ego vehicle and whether the other vehicle is located in front of, behind or even with the ego vehicle in relation to the course of a road {[0061]: the lateral position of at least one other vehicle, particularly of the leading vehicle, in relation one's own vehicle, the longitudinal position of at least one other vehicle}.
Regarding claim 12, which depends from claim 1, Posch discloses: wherein the test drive data is generated on the basis of real test drives and wherein relative positions of the other vehicles in relation to the ego vehicle are determined by an intelligent camera, lidar and/or radar, which in each case are preferably mounted on the ego vehicle {[0009]: on the basis of information from a stereo camera and the radar system, [0020]: one environmental sensor for detecting, particularly for measuring, an environmental parameter that characterizes the surroundings of the vehicle, and at least one vehicle sensor for detecting, particularly for measuring, a vehicle parameter that characterizes an operating state of a vehicle, [0061]}.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Posch in view of Liu and in further view of Michi et al. (US6853906B1).
Regarding claim 7, which depends from claim 1, modified Posch does not teach: wherein the test drive data is furthermore checked for an occurrence of elementary cornering maneuvers, wherein the elementary cornering maneuvers are selected from a list which includes at least one of the following elementary cornering maneuver groups: straight-line travel without curvature, cornering with increasing absolute curvature, exiting cornering with decreasing absolute curvature, cornering at constant curvature, left turning, right turning, traffic circle driving.
Michi teaches straight-line travel and cornering at constant curvature in col. 1, lines 60-65.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the cornering feature of Michi with the described invention of modified Posch in order to classify types of cornering.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Posch in view of Liu and in further view of Elrofai et al. (Scenario-Based Safety Validation of Connected and Automated Driving), which was cited by Applicant.
Regarding claim 9, which depends from claim 1, modified Posch does not teach: wherein the attributes are independent of the distance of the other vehicle relative to the ego vehicle but are only assigned up to a defined distance within a measuring range of a sensor for determining the attributes of the ego vehicle.
Elrofai teaches in page 14, lines 20-25 and Fig. 11 that attributes are independent of the distance of the other vehicle. Only lateral and longitudinal changes during lane change are described. page 12, lines 21-24 discloses a measuring range of a sensor.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the distance within measuring range feature of Elrofai with the described invention of modified Posch in order to utilize adequate capability of a sensor.
Claim(s) 10, 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Posch in view of Liu and in further view Yang et al. (US 20200003869 A1).
Regarding claim 10, which depends from claim 1, Posch discloses: wherein the test drive data is generated on the basis of real test drives {[0013]}.
Modified Posch does not teach: wherein a lane of the ego vehicle and the other vehicles is determined by an intelligent camera which is preferably mounted on the ego vehicle.
Yang teaches determining lane of vehicles in paragraph [0003]: center line or border line coordinates of a lane , coordinates and images of an object , such as another vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the lane determining feature of Yang with the described invention of modified Posch in order to consider driving lanes in the test.
Regarding claim 11, which depends from claim 10, Yang teaches: wherein a known position of landmarks in relation to a high-resolution map captured by the intelligent camera, is furthermore used to determine the lane of the ego vehicle and the other vehicles {[0003]: High - resolution maps obtained by images}.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the high-resolution map feature of Yang with the described invention of modified Posch in order to utilize detailed road data in the test.
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 CHANMIN PARK whose telephone number is (408)918-7555. The examiner can normally be reached Monday - Thursday and alternate Fridays, 7:30-4:30 PT.
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 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, Ramya P Burgess can be reached at (571)272-6011. 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.
/C.P./Examiner, Art Unit 3661
/RUSSELL FREJD/Primary Examiner, Art Unit 3661