DETAILED ACTION
This Office Action is a first Office Action on the merits of the application. Claims 1 - 20 are presented for examination. Claims 1, 3, 4, 7, 8, 16, and 18 - 20 are rejected.
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 .
Drawings Objections
The drawings are objected to because elements of FIGS 1 and 3, including the words in FIG. 1 and the elements pertaining to “Range” and “Update Frequency” are blurry and difficult to read. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 16 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 16 lacks antecedent basis for “at least one of the following” (Claim 16, line 2).
Suggested language: Amend the claim to recite “at least one of”.
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.
Claims 1, 19 and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kamenev et al (U.S. PG Pub 2021/0295171 A1), hereinafter “Kamenev”.
As per claim 1, Kamenev discloses:
a simulation method, comprising generating, using a processor, a main entity comprising a representation of an autonomous vehicle in a simulation platform (Kamenev, par [0019] discloses simulation of an autonomous vehicle and objects in an environment.)
acquiring simulation parameters of environmental entities, the simulation parameters comprising update periods of the environmental entities and a number constraint of the environmental entities in a preset area where the main entity is located within each update period (Kamenev, par [0004] discloses the number of actors and the path they travel from time period to time period, par [0028] - [0030] discloses the ego vehicle, and past and current locations relative to the ego vehicle, locations of actors at a time slice at a specified time, and mapping information regarding a time slice to capture a driving area, with updates occurring during intervals.)
Par [0019] refers to the autonomous vehicle that’s in focus as the ego vehicle, and par [0022] adds the actors are other vehicles, pedestrians or objects in the environment.
determining, according to the number constraint, an expected number of the environmental entities in the preset area where the main entity is located within each update period (Kamenev, par [0004] discloses the number of actors and the path they travel from time period to time period, and par [0023] adds the movements of the objects around the vehicle in the environment, and par [0028] adds locations and actors in the environment at locations relative to the vehicle over a period of time or over time slices.)
generating, according to the simulation parameters and the expected number, a corresponding number of the environmental entities in the preset area of the main entity within each update period, each of the generated environmental entities comprising a representation of an object located within the present area of each update period (Kamenev, par [0030] discloses location of road lanes, static objects, in the form of map information relative to the ego vehicle, and par [0034] adds the future trajectories predicted over a plurality of time slices for actors, road structures, and additional conditions using a neural network.)
As per claim 19, Kamenev discloses:
a computing device, comprising: a processor, a memory, and a computer program stored on the memory and executable on the processor; wherein the processor, when executing the computer program, performs a method comprising:
generating a main entity comprising a representation of an autonomous vehicle in a simulation platform (Kamenev, par [0019] discloses simulation of an autonomous vehicle and objects in an environment.)
acquiring simulation parameters of environmental entities, the simulation parameters comprising update periods of the environmental entities and a number constraint of the environmental entities in a preset area where the main entity is located within each update period (Kamenev, par [0004] discloses the number of actors and the path they travel from time period to time period, par [0028] - [0030] discloses the ego vehicle, and past and current locations relative to the ego vehicle, locations of actors at a time slice at a specified time, and mapping information regarding a time slice to capture a driving area, with updates occurring during intervals.)
Par [0019] refers to the autonomous vehicle that’s in focus as the ego vehicle, and par [0022] adds the actors are other vehicles, pedestrians or objects in the environment.
determining, according to the number constraint, an expected number of the environmental entities in the preset area within each update period (Kamenev, par [0004] discloses the number of actors and the path they travel from time period to time period, and par [0023] adds the movements of the objects around the vehicle in the environment, and par [0028] adds locations and actors in the environment at locations relative to the vehicle over a period of time or over time slices.)
generating, according to the simulation parameters and the expected number, a corresponding number of the environmental entities in the preset area of the main entity within each update period, each of the generated environmental entities comprising a representation of an object located within the present area of each update period (Kamenev, par [0030] discloses location of road lanes, static objects, in the form of map information relative to the ego vehicle, and par [0034] adds the future trajectories predicted over a plurality of time slices for actors, road structures, and additional conditions using a neural network.)
As per claim 20, Kamenev discloses:
a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a computing device, causes the computing device to implement a method comprising (Kamenev, par [0193] discloses a computer storage media including memory, storing instructions.)
generating a main entity in a simulation platform, the main entity comprising a representation of an autonomous vehicle (Kamenev, par [0019] discloses simulation of an autonomous vehicle and objects in an environment.)
acquiring simulation parameters of environmental entities, the simulation parameters comprising update periods of the environmental entities and a number constraint of the environmental entities in a preset area where the main entity is located within each update period (Kamenev, par [0004] discloses the number of actors and the path they travel from time period to time period, par [0028] - [0030] discloses the ego vehicle, and past and current locations relative to the ego vehicle, locations of actors at a time slice at a specified time, and mapping information regarding a time slice to capture a driving area, with updates occurring during intervals.)
Par [0019] refers to the autonomous vehicle that’s in focus as the ego vehicle, and par [0022] adds the actors are other vehicles, pedestrians or objects in the environment.
determining, according to the number constraint, an expected number of the environmental entities in the preset area within each update period (Kamenev, par [0004] discloses the number of actors and the path they travel from time period to time period, and par [0023] adds the movements of the objects around the vehicle in the environment, and par [0028] adds locations and actors in the environment at locations relative to the vehicle over a period of time or over time slices.)
generating, according to the simulation parameters and the expected number, a corresponding number of the environmental entities in the preset area of the main entity within each update period, each of the generated environmental entities comprising a representation of an object located within the present area of each update period (Kamenev, par [0030] discloses location of road lanes, static objects, in the form of map information relative to the ego vehicle, and par [0034] adds the future trajectories predicted over a plurality of time slices for actors, road structures, and additional conditions using a neural network.)
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.
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 3 is rejected under 35 U.S.C. 103 as being unpatentable over Kamenev et al (U.S. PG Pub 2021/0295171 A1), and further in view of Bagschik et al (U.S. PG Pub 2021/0370972 A1), hereinafter “Bagschik”.
As per claim 3, the prior art of Kamenev discloses the method of claim 1.
The prior art of Kamenev does not expressly disclose:
wherein determining, according to the number constraint, the expected number of the environmental entities in the preset area where the main entity is located within each update period comprises:
in response to an arrival of an update moment of each update period, determining, according to the number constraint, the expected number of the environmental entities in the preset area where the main entity is located within the update period
Bagschik however discloses:
wherein determining, according to the number constraint, the expected number of the environmental entities in the preset area where the main entity is located within each update period comprises:
in response to an arrival of an update moment of each update period, determining, according to the number constraint, the expected number of the environmental entities in the preset area where the main entity is located within the update period (Bagschik, par [0011] discloses classification of objects in an environment, with object classification, including pedestrians, signage, cyclist, additional vehicles, static objects, along with the location of the objects, with [0030] and [0032] discloses a location of objects, including a vehicle and pedestrian, in the same area and the position from a previous time step to a current time step.)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the locations of objects and vehicles in an environment over a period of time teaching of Kamenev with objects in the environment at a location at a previous time to a current time regarding movement of a vehicle teaching of Bagschik. The motivation to do so would have been because Bagschik discloses the benefit of simulating an aberrant behavior using the agent behavior model may improve tests of an autonomous vehicle's response to objects in the environment surrounding the autonomous vehicle (Bagschik, par [0010]).
Claims 4, 7, and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Kamenev et al (U.S. PG Pub 2021/0295171 A1), and further in view of Djuric et al (“Uncertainty-Aware Short -Term Motion Prediction of Traffic Actors for Autonomous Driving”), hereinafter “Djuric”.
As per claim 4, the prior art of Kamenev discloses the method of claim 1.
The prior art of Kamenev does not expressly disclose:
wherein determining, according to the number constraint, the expected number of the environmental entities in the preset area where the main entity is located within each update period comprises: determining in advance, according to the number constraint, the expected number of the environmental entities in the preset area where the main entity is located within each update period so as to obtain a plurality of expected numbers corresponding to a plurality of update periods.
Djuric however discloses:
wherein determining, according to the number constraint, the expected number of the environmental entities in the preset area where the main entity is located within each update period comprises: determining in advance, according to the number constraint, the expected number of the environmental entities in the preset area where the main entity is located within each update period so as to obtain a plurality of expected numbers corresponding to a plurality of update periods (Djuric, page 3, right col, ln 1 - 4, and 14 - 33 discloses tracking of actors in real time, and discrete times for tracking using map data, sensor range used to count actors in range and determining past and future positions for a number of different actors at specified times.)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the locations of objects and vehicles in an environment over a period of time teaching of Kamenev with the past and future positions for different actors at specific times and tracked using map data teaching of Djuric. The motivation to do so would have been because Djuric discloses the benefit of using a deep learning-based approach using a current world state to obtain raster images of the vicinity of each actor, provided to deep convolution models that can infer future movement of actors and accounting and capturing inherent uncertainty (Djuric, page 1, left column, Abstract, lines 4 - 11).
For claim 7: The combination of Kamenev and Djuric discloses claim 7: The method according to claim 1, wherein the simulation parameters further comprise at least one of:
a location constraint, a type constraint, a dimension constraint, an initial speed constraint, a target speed constraint, an acceleration constraint, a deceleration constraint, or driving habit parameters of the environmental entities in the preset area within each update period (Djuric, page 3, right col, ln 18 - 23 discloses tracking unique actors during times in the area of a sensor, in which the range of the sensor (sensor range) is interpreted as the constraint of the location for tracking environmental entities.)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the locations of objects and vehicles in an environment over a period of time teaching of Kamenev with the past and future positions for different actors at specific times and tracked using map data teaching of Djuric, and the additional teaching of tracking unique actors in an area at times based on the location of a sensor, also found in Djuric. The motivation to do so would have been because Djuric discloses the benefit of using a deep learning-based approach using a current world state to obtain raster images of the vicinity of each actor, provided to deep convolution models that can infer future movement of actors and accounting and capturing inherent uncertainty (Djuric, page 1, left column, Abstract, lines 4 - 11).
For claim 8: The combination of Kamenev and Djuric discloses claim 8: The method according to claim 1, wherein the simulation parameters further comprise a location constraint, the location constraint comprises at least one of:
a relative location of each environmental entity relative to the main entity when each environmental entity being generated, or an offset value of each environmental entity relative to a lane center when each environmental entity being generated (Djuric, page 3, right col, ln 18 - 23 discloses a sensor range for tracking actors, including the number of actors in the range area at different time steps.)
wherein the relative location comprises at least one of:
left front, straight ahead, right front, left side, right side, left back, directly behind, or right back (Djuric, page 2, left column, lines 1 - 2 discloses a scene using a 3D viewer in FIG. 1a, including the actor (vehicle) of interested and the location of additional actors (vehicle).)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the locations of objects and vehicles in an environment over a period of time teaching of Kamenev with the past and future positions for different actors at specific times and tracked using map data teaching of Djuric, and the additional teaching of tracking unique actors in specific directions relative to a target actor in an area, also found in Djuric. The motivation to do so would have been because Djuric discloses the benefit of using a deep learning-based approach using a current world state to obtain raster images of the vicinity of each actor, provided to deep convolution models that can infer future movement of actors and accounting and capturing inherent uncertainty (Djuric, page 1, left column, Abstract, lines 4 - 11).
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Kamenev et al (U.S. PG Pub 2021/0295171 A1), and further in view of Ventakesh (U.S. PG Pub 2023/0106268 A1), hereinafter “Ventakesh”.
As per claim 18, the prior art of Kamenev discloses the method according to claim 1.
The prior art of Kamenev does not expressly disclose:
wherein different weather conditions and road conditions respectively have different simulation parameters.
Ventakesh however discloses:
wherein different weather conditions and road conditions respectively have different simulation parameters (Ventakesh, Par [0107] discloses environment navigation for an automated vehicle using map data including geometric boundaries, including traffic control measures, road surface markings, road with barriers, with [0171] discloses candidate trajectories for a planned route, with operating restrictions including condition-specific speed restrictions related to weather conditions, and par [0172] adds the instructions for a trip sent to a vehicle for simulating a trip performed by a vehicle.)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the locations of objects and vehicles in an environment over a period of time teaching of Kamenev with the road and weather conditions for an autonomous vehicle to travel teaching of Ventakesh. The motivation to do so would have been because Ventakesh discloses the benefit of an application to facility a map display with identifiers to show where robotic systems can move to and from, as well as stop at pick up and drop off locations (PUDOLs) regarding a road map, to assist with improving parameters used to calculate or determine serviceable area, connected zones, and routes between connected zones (Ventakesh, par [0065]).
Allowable Subject Matter
Claims 2, 5, 6, and9 - 17 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.
The prior art of Kamenev et al (U.S. PG Pub 2021/0295171 A1) discloses locations of objects and vehicles in an environment over a period of time, Bagschik et al (U.S. PG Pub 2021/0370972 A1) discloses objects in the environment at a location at a previous time to a current time regarding movement of a vehicle, Djuric et al (“Uncertainty-Aware Short -Term Motion Prediction of Traffic Actors for Autonomous Driving”) discloses the past and future positions for different actors at specific times and tracked using map data, and Ventakesh (U.S. PG Pub 2023/0106268 A1) discloses road and weather conditions for an autonomous vehicle to travel.
However, none of the references cited, including the prior art of Kamenev, Bagschik, Djuric, and Ventakesh, taken either alone or in combination with the prior art of record discloses:
Claim 2, with a number values for more than one update period and an expected number in the form of a range of values associated with the number constraints comply with a distribution rule, in combination with the remaining elements and features of the claimed invention. It is for these reasons that the applicants’ invention defines over the prior art of record.
Claim 5, in which the amount of entities in the environment for a preset area is computer regarding the location of the main entity, and a computation between the amount of entities and the expected number of entities in the preset area, with additional entities in the environment is generated when there are more actual number of entities in the preset area of the environment than the expected number of entities, in combination with the remaining elements and features of the claimed invention. It is for these reasons that the applicants’ invention defines over the prior art of record.
Dependent claim 6 is allowable under 35 U.S.C. 103 for depending from claim 5, an allowable base claim under 35 U.S.C. 103.
Claim 9, in which a preset distance is used to determine an override distance between an entity in the environment and a vehicle in front or a distance in which an environmental entity is moving from one lane to another lane in relation to a vehicle in front used to determine a driving habit parameter, in combination with the remaining elements and features of the claimed invention. It is for these reasons that the applicants’ invention defines over the prior art of record.
Dependent claims 10 - 12 are allowable under 35 U.S.C. 103 for depending from claim 9, an allowable base claim under 35 U.S.C. 103.
Claim 13, in which a simulation includes controlling a vehicle on a test map moving from a starting location to a destination, and making a return trip from the destination back to the starting point, in combination with the remaining elements and features of the claimed invention. It is for these reasons that the applicants’ invention defines over the prior art of record.
Claim 14, in which, after an abnormality occurs in the simulation performed, and after a specified amount of time, the removal of the abnormality, or after an abnormality occurs and results in environmental entities relocating out of the boundaries of the preset area, the removal of the abnormality, in combination with the remaining elements and features of the claimed invention. It is for these reasons that the applicants’ invention defines over the prior art of record.
Claim 15, in which a present evaluation index is used to determine an abnormality occurs, and log a certain amount of time in which the abnormality occurs during simulation periods in the simulation, in combination with the remaining elements and features of the claimed invention. It is for these reasons that the applicants’ invention defines over the prior art of record.
Dependent claims 16 and 17 are allowable under 35 U.S.C. 103 for depending from claim 15, an allowable base claim under 35 U.S.C. 103.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CEDRIC D JOHNSON whose telephone number is (571)270-7089. The examiner can normally be reached M-Th 4:30am - 2:00pm, F 4:30am - 11:30am.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Renee Chavez can be reached at 571-270-1104. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Cedric Johnson/ Primary Examiner, Art Unit 2186
July 11, 2026
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