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 and Arguments
The amendment filed 6/29/2026 has been entered. Claims 1-4, 6-8, and 10-12 remain pending in the application. Claims no longer invoke interpretation under 35 USC 112(f).
Response to Arguments
Applicant's arguments filed 6/29/2026 have been fully considered but they are not persuasive.
Applicant argues that Hong at least fails to teach the feature of "wherein the Al performs analysis based on the plurality of pieces of information to calculate an index value for controlling the autonomous driving vehicle during the traveling test" and that “the simulation test in Hong is information that was a selected closest instance transformed by a transformer and is then applied to simulate a less safe driving scenario…the traveling test in Hong is not conducted using the same information from the acquired information”. Examiner respectfully disagrees.
Hong teaches AI performing analysis based on sensor data to calculate a value for controlling the autonomous vehicle during the travel test (simulation run simultaneously by multiple neural networks) in [0064], [0080], [0126], [0112], [0120-0122]: “technology described herein allows for multiple neural networks to be performed simultaneously and/or sequentially, and for the results to be combined together to enable Level 3-5 autonomous driving functionality…a warning sign consisting of “Caution: flashing lights indicate icy conditions,” along with an electric light, may be independently or collectively interpreted by several neural networks. The sign itself may be identified as a traffic sign by a first deployed neural network (e.g., a neural network that has been trained), the text “Flashing lights indicate icy conditions” may be interpreted by a second deployed neural network, which informs the vehicle's path planning software ”, [0164], [0166].
While Hong does update or transform sensor data to be used by the simulation in certain embodiments, the sensor data is still being used (altered or not) to run simulations, thus reading on the claimed limitation. Furthermore, the requirement to use the same, unaltered sensor data information to run a simulation is not concurrently claimed.
Claim Rejections - 35 USC § 102
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1-4, 6-8, 10-12 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US20250377265A1 (“Hong”).
Claim 1:
An autonomous driving test method comprising: setting a plurality of obstacles on a test course; and acquiring, by a sensor mounted on an autonomous driving vehicle, a plurality of pieces of information regarding the plurality of obstacles; and performing a traveling test related to autonomous driving of the autonomous driving vehicle by using the plurality of pieces of information regarding the plurality of obstacles acquired by the sensor, and an artificial intelligence (Al), wherein the Al performs analysis based on the plurality of pieces of information to calculate an index value for controlling the autonomous driving vehicle during the traveling test. (Hong at least the abstract, [0007], [0024-0035], [0093], [0064], [0080], [0126], [0064], [0079], [0080], [0112], [0120-0122], [0164-0166])
Claim 2:
acquiring information indicating a behavior of the autonomous driving vehicle in a case in which the autonomous driving vehicle is caused to travel on the test course through autonomous driving. (Hong at least [0007], [0021]: “sensor data may be generated in a real-world environment and/or on a test tracks using real objects. For example, the vehicle may drive toward and/or away from a real-world object at a slow and safe speed”)
Claim 3:
the plurality of pieces of information includes position information of the obstacles, and the position information of the obstacles and the information indicating the behavior of the autonomous driving vehicle are stored in association with each other. (Hong at least [0025])
Claim 4:
A non-transitory recording medium storing a program that is executable by a computer to perform processing, the processing comprising: acquiring information regarding a plurality of obstacles set on a test course; and performing a traveling test related to autonomous driving of a vehicle by using a plurality of pieces of the acquired information and an artificial intelligence (Al), wherein the Al performs analysis based on the plurality of pieces of information to calculate an index value for controlling the autonomous driving vehicle during the traveling test. (Hong at least the abstract, [0126], [0007], [0024-0035], [0093], [0064], [0080], [0126])
Claim 6:
An autonomous driving test method comprising: acquiring information indicating a behavior of an autonomous driving vehicle; and performing a traveling test of causing the autonomous driving vehicle to travel on a test course on a virtual space on the basis of data in the virtual space corresponding to a test course in which a plurality of obstacles are installed and the information. (Hong at least the abstract, [0007], [0024-0035], [0093], [0064], [0080], [0126], [0064], [0079], [0080], [0112], [0120-0122], [0164-0166])
Claim 7:
information indicating the behavior of the autonomous driving vehicle at the time of the traveling test is stored. (Hong at least [0007], [0021])
Claim 8:
the obstacles and the information indicating the behavior of the autonomous driving vehicle are stored in association with each other. (Hong at least [0025])
Claim 10:
wherein the Al performs multivariate analysis based on the plurality of pieces of acquired information at nanosecond intervals. (Hong at least [0138])
Claim 11:
generating the test course on the virtual space based on course shape information, obstacle information, and weather information, wherein the course shape information includes information regarding a shape of the test course or a road surface information, wherein the obstacle information includes at least one of a type, a size, a position, or a behavior of the plurality of obstacles, and wherein the weather information includes information regarding weather of the test course. (Hong at least [0036])
Claim 12:
the information indicating the behavior of the autonomous driving vehicle is acquired by a sensor mounted on the autonomous driving vehicle (Hong at least [0022], [0024])
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.
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/O.T./Examiner, Art Unit 3669
/TODD MELTON/Primary Examiner, Art Unit 3669
