DETAILED ACTION
Claims 11-29 are currently pending and have been examined in this application. This FINAL communication is in response to the amendment submitted on 9/25/25.
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
Regarding the objection to the specification, Applicant is advised that the objection is maintained and the following two documents are required. Examiner has further clarified for the applicant here and below by reviewing 37 CFR 1.125(a & c), as well as MPEP 608.01(q).
37 CFR 1.125(c) requires a substitute specification filed under 37 CFR 1.125(a) or (b) be submitted in clean form without markings. A marked-up copy of the substitute specification showing all the changes relative to the immediate prior version of the specification of record must also be submitted. The text of any added subject matter must be shown by underlining the added text. The text of any deleted matter must be shown by strike-through except that double brackets placed before and after the deleted characters may be used to show deletion of five or fewer consecutive characters. The text of any deleted subject matter must be shown by being placed within double brackets if strike-through cannot be easily perceived. Numbering the paragraphs of the specification of record is not considered a change that must be shown under 37 CFR 1.125(c). The paragraphs of any substitute specification, other than the claims, should be individually numbered in Arabic numerals (for example [0001]) so that any amendment to the specification may be made by replacement paragraph in accordance with 37 CFR 1.121(b)(1).
Applicant's arguments filed regarding Double Patenting have been fully considered but they are not persuasive.
Issue #1
Applicant: It is believed that the amendments made herein render the non-statutory double patenting rejection of Claims 11-29 moot.
Examiner: The examiner maintains the rejection per the reasons discussed below.
Applicant's arguments filed regarding 101 have been fully considered but they are not persuasive.
Issue #1
Applicant: As explained in the background of the application, conventional action planning devices sequentially detect targets. such as other vehicles, pedestrians. etc. in order to determine a course of action (published application, [0005]). This leads to the problem that detection takes time and thus throughput of vehicles through an intersection may be decreased as a moving body such as an autonomous vehicles determine their course of action. The features recited in amended Claim11 advantageously combine to resolve the
problems of conventional action planning devices by performing mode calculations in parallel via plural mode calculation circuitries, thereby arriving at a mode for the moving body faster than conventional systems. As such, the features recited in amended Claim 11 represent a technological improvement to autonomous driving vehicle (i.e., moving body) technology. Moreover, USPTO guidance makes clear that claims which recite a practical application of an abstract idea upon which the claims touch are not deemed to be directed to an abstract idea (January 2019 USPTO Guidance on Subject Matter Eligibility, pp.5-6, et seq., hereafter the "PEG"). The October 2019 Update on Subject Matter Eligibility (hereafter the "October 2019 PEG Update") explains that determining whether an abstract idea is integrated into a practical application involves determining whether the application describes an improvement to a technology and determining whether the claims recite elements that reflect the improvement (October 2019 PEG Update, pp. 12-13). Importantly, the October 2019 PEG Update does not make any distinction with regard to the type of technology improved (Id.). It is believed, therefore, that under this clarified USPTO guidance for analyzing subject matter eligibility under 35 U.S.C. 101, that the claims of the instant application integrate any abstract idea upon which they might touch into a practical application, namely autonomous driving vehicle (i.e., moving body) technology.
Examiner: Examiner is not persuaded by applicant’s arguments. The claims previously discussed used circuitry to calculate data in parallel and now suggests that a plurality of circuitry (generic computer components) sufficiently adds technical weight to the claim as an improvement in calculation processing translating to a technical improvement in autonomous driving technology. Effectively, the claim being made by applicant is that more circuitries improves the level of parallel-processed calculations, but it’s not clear how this improves autonomous driving technology as it doesn’t go beyond the apply-it standard (still using generic computer components). Examiner suggests looking to provide additional technical elements to the claim, identifying the technical problem, addressing the root of the technical problem with a more specific technical solution (using further additional elements to delineate the technical solution to the technical problem being faced by conventional systems).
What has been the limiting step of conventional systems in parallel processing and why have they been operating sequentially (what has been the limiting step(s)). Is there any additional elements that speak to improvements to functioning of the computer itself? Further provide additional specification support to substantiate the response.
Applicant's arguments filed regarding 102/103 have been fully considered but they are not persuasive in light of the new grounds of rejection under 103 regarding Marchetti-Bowick (see rejection below for Claims 11-14 & 19, and similar logic to be applied to the remaining claims).
Issue #1
Applicant: Amended Claim 11 recites, in part, "plural mode calculation circuitries to calculate, in parallel, a plurality of modes as candidates for action that the moving body can take using the one or more pieces of scene information." The Office Action asserts that Marchetti-Bowick describes calculating modes in parallel (Office Action Marchetti-Bowick describes using a "prediction system" to determine a motion plan and generate plan data, without describing whether the prediction system includes multiple circuitries to calculate the motion plans or not (Marchetti-Bowick,[0072]). The Office Action relies on the general statement in Marchetti-Bowick that the "computer-implemented tasks and/or operations can be performed sequentially or in parallel"(Office Action, p. 8). This statement, however, lacks any indication of the structure with which parallel operations are performed. Therefore, it is believed that Marchetti-Bowick does not disclose or suggest the claimed plural mode calculation circuitries, and cannot anticipate amended Claim 11.
Examiner: It would be obvious to one skilled in the art to utilize multiple circuits/processors to determine a motion plan using the prediction system in referencing the below rejection. Examiner requests that applicant look to provide more narrowing technology from the specification to advance the prior art discussion. Applicant is further welcome to contact Examiner to discuss amendments that will potentially move the prior art discussion forward.
Specification
A substitute specification excluding the claims is required pursuant to 37 CFR 1.125(a) and 37 CFR 1.125(c) because see below, particularly that in bold. On 7/3/24, the applicant submitted a preliminary amendment which included several amendments to the specification, however did not provide a clean version of the specification including all said changes. Applicant should resubmit the entirety of the specification which includes the amended changes (with markings) submitted on 7/3/24 as well as a clean version (substitute specification) that is inclusive of all amended changes and without the markings.
A substitute specification must not contain new matter. The substitute specification must be submitted with markings showing all the changes relative to the immediate prior version of the specification of record. The text of any added subject matter must be shown by underlining the added text. The text of any deleted matter must be shown by strike-through except that double brackets placed before and after the deleted characters may be used to show deletion of five or fewer consecutive characters. The text of any deleted subject matter must be shown by being placed within double brackets if strike-through cannot be easily perceived. An accompanying clean version (without markings) and a statement that the substitute specification contains no new matter must also be supplied. Numbering the paragraphs of the specification of record is not considered a change that must be shown.
To further clarify ---- See MPEP 608.01(q)
37 CFR 1.125(c) requires a substitute specification filed under 37 CFR 1.125(a) or (b) be submitted in clean form without markings. A marked-up copy of the substitute specification showing all the changes relative to the immediate prior version of the specification of record must also be submitted. The text of any added subject matter must be shown by underlining the added text. The text of any deleted matter must be shown by strike-through except that double brackets placed before and after the deleted characters may be used to show deletion of five or fewer consecutive characters. The text of any deleted subject matter must be shown by being placed within double brackets if strike-through cannot be easily perceived. Numbering the paragraphs of the specification of record is not considered a change that must be shown under 37 CFR 1.125(c). The paragraphs of any substitute specification, other than the claims, should be individually numbered in Arabic numerals (for example [0001]) so that any amendment to the specification may be made by replacement paragraph in accordance with 37 CFR 1.121(b)(1).
Claim Objection(s)
Claim 21 is objected to because of the following informalities:
The following suggestions to the claim limitations place the claims in better form by improving consistency within the claims and/or with respect to the specification:
Claim 21:
Amend to: “the plural mode calculation”.
Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 11-29 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of copending Application No. 18562324 in view of Marchetti-Bowick (US 20210188316).
This is a provisional nonstatutory double patenting rejection.
Instant Claim 11:
‘324 teaches the following limitations:
An action planning apparatus comprising: (Claim 1 “A path planning apparatus configured to plan a path of a moving body, the path planning apparatus comprising:”) scene generation circuitry to generate, using surroundings information on surroundings of a moving body [including an autonomous driving vehicle], one or more pieces of scene information indicating a situation in which the moving body is placed; (Claim 1 “a travelable region calculation unit configured to calculate a travelable region of the moving body, based on surrounding information of the moving body;”) plural mode calculation circuitries to calculate, in parallel, a plurality of modes as candidates for action that the moving body can take using the one or more pieces of scene information; (Claim 1 “a state prediction unit configured to predict at least current state quantity of the moving body and state quantity of the moving body at one or more positions between a current position and the target position of the moving body, and thereby generate one or more path candidates;”) and output the selected one of the plurality of modes as action of the moving body. (Claim 1 “output the path to a motion controller configured to control the moving body based on the path.”)
‘324 does not explicitly teach the following limitations, however Marchetti-Bowick teaches:
[surroundings of a moving body] including an autonomous driving vehicle
([abstract] local scene data associated with an environment external to an autonomous
vehicle…determining, by the computing system, a candidate motion plan for the autonomous vehicle. [0059] The vehicle status data can include a state of a vehicle, a location of a vehicle (e.g., a latitude and longitude of a vehicle), the availability of a vehicle (e.g., whether a vehicle is available to pick-up or drop-off passengers and/or cargo, etc.), the current or forecasted navigational route of the vehicle, and/or the state of objects internal and/or external to a vehicle (e.g., the physical dimensions and/or appearance of objects internal/external to the vehicle). [0095] At 306, method 300 can include obtaining a candidate motion plan for the autonomous vehicle. The candidate
motion plan can include a target motion trajectory for the vehicle and/or certain driving maneuvers ( e.g., accelerating, decelerating, merging lanes, etc.).)
mode selection circuitry to select one of the plurality of modes calculated by the plural mode calculation circuitries and
([0073] motion planning system 128 can determine a motion plan and generate motion plan data 134 for the vehicle 102 based at least in part on the prediction data 132 (and/or other data). The motion plan data 134 can include vehicle actions with respect to the objects proximate to the vehicle 102 as well as the predicted movements…the motion planning system 128 can obtain and select one or more candidate motion plans based at least in part on the local scene data and/or the extracted actor prediction parameters. [0075] The motion planning system 128 then can provide the selected motion plan to a vehicle controller that controls one or more vehicle controls (e.g., actuators or other devices that control gas flow, steering, braking, etc.) to execute the selected motion plan. [0125, 0135, 0153, 0155])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to be motivated to modify ‘324 with Marchetti-Bowick in order to select a candidate motion plan from a plurality of motion plans or calculated modes prior to having the vehicle take autonomous control (Marchetti-Bowick – [0073]).
The remaining features of the claims in the instant application are not explicitly taught by related application ‘324. However, the remaining features are taught in view of Marchetti-Bowick as well as its combination in the 103 rejections. It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have to have modified the application ‘324 with Marchetti-Bowick and the combination of references taught below in order to select a candidate motion plan from a plurality of motion plans or calculated modes prior to having the vehicle take autonomous control (Marchetti-Bowick – [0073]) as well as the motivations for combining the features taught from the remaining prior art in combination with Taveres, as described in the aforementioned 103 rejection.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 11-29 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The claims are either directed to a system or method, which is one of the statutory categories of invention. (Step 1: YES).
The Examiner has identified system Claim 11 as the claim that represents the claimed invention for analysis and is similar to system Claim 20 and method Claim 29. Claim 11 recites the limitations of (additional elements emphasized in bold and are considered to be parsed from the remaining abstract idea):
An action planning apparatus comprising: scene generation circuitry to generate, using surroundings information on surroundings of a moving body including an autonomous driving vehicle, one or more pieces of scene information indicating a situation in which the moving body is placed; mode calculation circuitry to calculate, in parallel, a plurality of modes as candidates for action that the moving body can take using the one or more pieces of scene information; and mode selection circuitry to select one of the modes calculated by the mode calculation circuitry and output the selected one of the modes as action of the moving body.
which is a process that, under its broadest reasonable interpretation, covers performance of the limitation(s) as a Certain method of organizing human activity (fundamental economic practice), or a Mental process (concept performed in the human mind) of planning the action of a vehicle.
If a claim limitation, under its broadest reasonable interpretation (BRI), covers performance of the limitation as a certain method of a fundamental economic practice, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas.
Similarly if a claim limitation under its BRI, covers performance of the limitation in the human mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. (Claims can recite a mental process even if they are claimed as being performed on a computer Gottschalk v. Benson, 409 U.S. 63; "Courts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015).)
Accordingly, the claim recites an abstract idea. (Step 2A-Prong 1: YES. The claims are abstract)
This judicial exception is not integrated into a practical application. Limitations that are not indicative of integration into a practical application include: (1) Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05.f), (2) Adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05.g), (3) Generally linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05.h). The circuitries in Claim 11 (similarly that of Claim 20 & 29) are just using generic computer components, and the autonomous driving vehicle is generally linking the use of a judicial exception to a particular technological environment or field of use. The computer hardware is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts to no more than mere instructions to implement an abstract idea by adding the words “apply it” (or an equivalent) with the judicial exception. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore claim 11 is directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using computer hardware amounts to no more than mere instructions to implement an abstract idea by adding the words “apply it” (or an equivalent) with the judicial exception, and further the additional element of an autonomous driving vehicle is no more than generally linking the use of a judicial exception to a particular technological environment or field of use. . Mere instructions to implement an abstract idea on or with the use of generic computer components, cannot provide an inventive concept - rendering the claim patent ineligible. Thus claim 11 is not patent eligible. (Step 2B: NO. The claims do not provide significantly more)
The dependent claims further define the abstract idea that is present in their respective independent claims and hence are abstract for at least the reasons presented above. The dependent claims do not include any additional elements (including Claim 14 – FSM (finite state machine), neural network – which further apply the abstract idea on a generic computer component) that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Therefore, the dependent claims are directed to an abstract idea. Thus, the aforementioned claims are not patent-eligible.
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.
Claim(s) 11-14 & 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Marchetti-Bowick1 (US 20210188316 – Embodiment A – Example embodiments) in view of Marchetti-Bowick2 (Embodiment B – Another Embodiment).
Claim 11.
Marchetti-Bowick1 teaches the following limitations:
An action planning apparatus comprising: scene generation circuitry to generate, using surroundings information on surroundings of a moving body including an autonomous driving vehicle, one or more pieces of scene information indicating a situation in which the moving body is placed;
([abstract] determining, by the computing system, a candidate motion plan for the autonomous vehicle [0067] The one or more autonomy system sensors 114 can be configured to generate and/or store data including the autonomy sensor data 116 associated with one or more objects that are proximate to the vehicle 102… autonomy sensor data 116 can be indicative of locations associated with the one or more objects within the surrounding environment of the vehicle 102 at one or more times. [0071] The perception system 124 can identify one or more objects that are proximate to the vehicle 102 based on autonomy sensor data 116 received from the autonomy system sensors 114. In particular, in some implementations, the perception system 124 can determine, for each object, local scene data 130 that describes a current state of such object… the perception system 124 can determine local scene data 130 for each object over a number of iterations. In particular, the perception system 124 can update the local scene data 130 for each object at each iteration. Thus, the perception system 124 can detect and track objects (e.g., vehicles, bicycles, pedestrians, etc.) that are proximate to the vehicle 102 over time, and thereby produce a presentation of the world around an vehicle 102 along with its state (e.g., a presentation of the objects of interest within a scene at the current time along with the states of the objects) [Claim 1] [0095] At 306, method 300 can include obtaining a candidate motion plan for the autonomous vehicle. The candidate motion plan can include a target motion trajectory for the vehicle and/or certain driving maneuvers (e.g., accelerating, decelerating, merging lanes, etc.). [0125] one or more units may be a part of or included in one or more other units. These means can include processor(s), microprocessor(s), graphics processing unit(s), logic circuit(s), dedicated circuit(s), application-specific integrated circuit(s))
plural mode calculation [circuitries] to calculate, in parallel, a plurality of modes as candidates for action that the moving body can take using the one or more pieces of scene information; and
([0037] In some implementations, a plurality of candidate motion plans can be determined for the autonomous vehicle. [0073] motion planning system 128 can determine a motion plan and generate motion plan data 134 for the vehicle 102 based at least in part on the prediction data 132 (and/or other data). The motion plan data 134 can include vehicle actions with respect to the objects proximate to the vehicle 102 as well as the predicted movements…the motion planning system 128 can obtain and select one or more candidate motion plans based at least in part on the local scene data and/or the extracted actor prediction parameters. [0076] The motion planning system 128 can provide the motion plan data 134 with data indicative of the vehicle actions, a planned trajectory, and/or other operating parameters to the vehicle control systems 138 to implement the motion plan data 134 for the vehicle 102. [0153] Computer-implemented tasks and/or operations can be performed sequentially or in parallel. [claim 1, 0125])
Examiner Note: A plurality of candidate motion plans for action are representative of the plurality of modes.
mode selection circuitry to select one of the plurality of modes calculated by the plural mode calculation [circuitries] and output the selected one of the plurality of modes as action of the moving body.
([0073] motion planning system 128 can determine a motion plan and generate motion plan data 134 for the vehicle 102 based at least in part on the prediction data 132 (and/or other data). The motion plan data 134 can include vehicle actions with respect to the objects proximate to the vehicle 102 as well as the predicted movements…the motion planning system 128 can obtain and select one or more candidate motion plans based at least in part on the local scene data and/or the extracted actor prediction parameters. [0075] The motion planning system 128 then can provide the selected motion plan to a vehicle controller that controls one or more vehicle controls (e.g., actuators or other devices that control gas flow, steering, braking, etc.) to execute the selected motion plan. [0125])
Marchetti-Bowick1 does not explicitly teach the following limitations, however Marchetti-Bowick2 teaches the following limitations:
circuitries [to calculate, in parallel,]
([0125] motion plan determination unit(s) 906, reactive prediction generation unit(s), and/or other means for performing the operations and functions described herein. In some implementations, one or more of the units may be implemented separately. In some implementations, one or more units may be a part of or included in one or more other units. These means can include processor(s), microprocessor(s), graphics processing unit(s), logic circuit(s), dedicated circuit(s), application specific integrated circuit(s ), programmable array logic, field-programmable gate array(s), controller(s), microcontroller(s), and/or other suitable hardware. The means can also, or alternately, include software control means implemented with a processor or logic circuitry for example [0135] The memory 1014 can also store computer-readable instructions 1018 that can be executed by the one or more processors 1012. [0153] [0155] the subject disclosure does not preclude inclusion of such modifications, variations and/or additions to the present subject matter as would be readily apparent to one of ordinary skill in the art. For instance, features illustrated or described as part of one embodiment can be used with another embodiment to yield a still further embodiment. Thus, it is intended that the present disclosure cover such alterations, variations, and equivalents.)
Examiner Note: Instant Spec [0022] When each of the components of the action planning apparatus 1 is the dedicated hardware as shown in FIG. 2A, the processing circuit 12 corresponds to a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination thereof, for example. Functions of the components of the action planning apparatus 1 may be achieved by respective processing circuits 12 or may collectively be achieved by a single processing circuit 12.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to be motivated to modify Marchetti-Bowick1 with Marchetti-Bowick2 in order to calculate a plurality of modes in parallel using multiple circuitries or programmed processors [Marchetti-Bowick2 – 0125, 0135, 0155].
Claim 12.
Marchetti-Bowick1 in combination with the references taught in Claim 11 teach those respective limitations. Marchetti-Bowick1 further teaches:
wherein the plural mode calculation [circuitries] calculate the plurality of modes using the one or more pieces of scene information and
([0037] In some implementations, a plurality of candidate motion plans can be determined for the autonomous vehicle. [0073] motion planning system 128 can determine a motion plan and generate motion plan data 134 for the vehicle 102 based at least in part on the prediction data 132 (and/or other data). The motion plan data 134 can include vehicle actions with respect to the objects proximate to the vehicle 102 as well as the predicted movements…the motion planning system 128 can obtain and select one or more candidate motion plans based at least in part on the local scene data and/or the extracted actor prediction parameters. [0076] The motion planning system 128 can provide the motion plan data 134 with data indicative of the vehicle actions, a planned trajectory, and/or other operating parameters to the vehicle control systems 138 to implement the motion plan data 134 for the vehicle 102. [claim 1])
current modes of the plural mode calculation [circuitries].
([0028] the local scene data can include the autonomous vehicle's current state. The current state of the autonomous vehicle can include current velocity, autonomous vehicle system conditions, autonomous vehicle energy/fuel levels, or any other metrics associated with the autonomous vehicle. As an example, the current state of the autonomous vehicle can indicate that a LIDAR sensor on the rear of the vehicle is not functioning within normal parameters. As another example, the current state may indicate that the autonomous vehicle possesses movement capabilities that enable a certain type of motion trajectory (e.g., an engine that can produce an amount of acceleration required to perform a certain merge operation, etc.) [0062] [0103] Local scene data 502 can include contextual scene information 502A, actor data 502B, current autonomous vehicle state data 502C, and historical autonomous vehicle state data 502D.)
Marchetti-Bowick1 does not explicitly teach the following limitations, however Marchetti-Bowick2 teaches the following limitations:
circuitries
([0125] motion plan determination unit(s) 906, reactive prediction generation unit(s), and/or other means for performing the operations and functions described herein. In some implementations, one or more of the units may be implemented separately. In some implementations, one or more units may be a part of or included in one or more other units. These means can include processor(s), microprocessor(s), graphics processing unit(s), logic circuit(s), dedicated circuit(s), application specific integrated circuit(s ), programmable array logic, field-programmable gate array(s), controller(s), microcontroller(s), and/or other suitable hardware. The means can also, or alternately, include software control means implemented with a processor or logic circuitry for example [0135] The memory 1014 can also store computer-readable instructions 1018 that can be executed by the one or more processors 1012. [0155] the subject disclosure does not preclude inclusion of such modifications, variations and/or additions to the present subject matter as would be readily apparent to one of ordinary skill in the art. For instance, features illustrated or described as part of one embodiment can be used with another embodiment to yield a still further embodiment. Thus, it is intended that the present disclosure cover such alterations, variations, and equivalents.)
Examiner Note: Instant Spec [0022] When each of the components of the action planning apparatus 1 is the dedicated hardware as shown in FIG. 2A, the processing circuit 12 corresponds to a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination thereof, for example. Functions of the components of the action planning apparatus 1 may be achieved by respective processing circuits 12 or may collectively be achieved by a single processing circuit 12.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to be motivated to modify Marchetti-Bowick1 with Marchetti-Bowick2 in order to calculate a plurality of modes in parallel using multiple circuitries or programmed processors [Marchetti-Bowick2 – 0125, 0135, 0155].
Claim 13.
Marchetti-Bowick1 in combination with the references taught in Claim 11 teach those respective limitations. Marchetti-Bowick1 further teaches:
wherein the plural mode calculation [circuitries] calculate the plurality of modes using the one or more pieces of scene information and
([0037] In some implementations, a plurality of candidate motion plans can be determined for the autonomous vehicle. [0073] motion planning system 128 can determine a motion plan and generate motion plan data 134 for the vehicle 102 based at least in part on the prediction data 132 (and/or other data). The motion plan data 134 can include vehicle actions with respect to the objects proximate to the vehicle 102 as well as the predicted movements…the motion planning system 128 can obtain and select one or more candidate motion plans based at least in part on the local scene data and/or the extracted actor prediction parameters. [0076] The motion planning system 128 can provide the motion plan data 134 with data indicative of the vehicle actions, a planned trajectory, and/or other operating parameters to the vehicle control systems 138 to implement the motion plan data 134 for the vehicle 102. [claim 1])
previous modes of the plural mode calculation [circuitries].
([0028] the local scene data can include the autonomous vehicle's current state. The current state of the autonomous vehicle can include current velocity, autonomous vehicle system conditions, autonomous vehicle energy/fuel levels, or any other metrics associated with the autonomous vehicle. As an example, the current state of the autonomous vehicle can indicate that a LIDAR sensor on the rear of the vehicle is not functioning within normal parameters. As another example, the current state may indicate that the autonomous vehicle possesses movement capabilities that enable a certain type of motion trajectory (e.g., an engine that can produce an amount of acceleration required to perform a certain merge operation, etc.) [0080] [0103] Local scene data 502 can include contextual scene information 502A, actor data 502B, current autonomous vehicle state data 502C, and historical autonomous vehicle state data 502D.
Marchetti-Bowick1 does not explicitly teach the following limitations, however Marchetti-Bowick2 teaches the following limitations:
circuitries
([0125] motion plan determination unit(s) 906, reactive prediction generation unit(s), and/or other means for performing the operations and functions described herein. In some implementations, one or more of the units may be implemented separately. In some implementations, one or more units may be a part of or included in one or more other units. These means can include processor(s), microprocessor(s), graphics processing unit(s), logic circuit(s), dedicated circuit(s), application specific integrated circuit(s ), programmable array logic, field-programmable gate array(s), controller(s), microcontroller(s), and/or other suitable hardware. The means can also, or alternately, include software control means implemented with a processor or logic circuitry for example [0135] The memory 1014 can also store computer-readable instructions 1018 that can be executed by the one or more processors 1012. [0155] the subject disclosure does not preclude inclusion of such modifications, variations and/or additions to the present subject matter as would be readily apparent to one of ordinary skill in the art. For instance, features illustrated or described as part of one embodiment can be used with another embodiment to yield a still further embodiment. Thus, it is intended that the present disclosure cover such alterations, variations, and equivalents.)
Examiner Note: Instant Spec [0022] When each of the components of the action planning apparatus 1 is the dedicated hardware as shown in FIG. 2A, the processing circuit 12 corresponds to a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination thereof, for example. Functions of the components of the action planning apparatus 1 may be achieved by respective processing circuits 12 or may collectively be achieved by a single processing circuit 12.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to be motivated to modify Marchetti-Bowick1 with Marchetti-Bowick2 in order to calculate a plurality of modes in parallel using multiple circuitries or programmed processors [Marchetti-Bowick2 – 0125, 0135, 0155].
Claim 14.
Marchetti-Bowick1 in combination with the references taught in Claim 11 teach those respective limitations. Marchetti-Bowick1 further teaches:
wherein the plural mode calculation [circuitries] include at least one of a finite state machine (FSM), a neural network, and ontology.
([0022] These actor prediction parameters, alongside a candidate motion plan (e.g., a target motion trajectory for the autonomous vehicle), can be provided as inputs to a machine-learned prediction model. [0034] The machine-learned prediction model can be or can otherwise include various machine-learned models such as, for example, neural networks (e.g., deep neural networks or other types of models including linear models and/or non-linear models). Example neural networks include feed-forward neural networks, recurrent neural networks (e.g., long short-term memory recurrent neural networks), convolutional neural networks, or other forms of neural networks.)
Marchetti-Bowick1 does not explicitly teach the following limitations, however Marchetti-Bowick2 teaches the following limitations:
circuitries
([0125] motion plan determination unit(s) 906, reactive prediction generation unit(s), and/or other means for performing the operations and functions described herein. In some implementations, one or more of the units may be implemented separately. In some implementations, one or more units may be a part of or included in one or more other units. These means can include processor(s), microprocessor(s), graphics processing unit(s), logic circuit(s), dedicated circuit(s), application specific integrated circuit(s ), programmable array logic, field-programmable gate array(s), controller(s), microcontroller(s), and/or other suitable hardware. The means can also, or alternately, include software control means implemented with a processor or logic circuitry for example [0135] The memory 1014 can also store computer-readable instructions 1018 that can be executed by the one or more processors 1012. [0155] the subject disclosure does not preclude inclusion of such modifications, variations and/or additions to the present subject matter as would be readily apparent to one of ordinary skill in the art. For instance, features illustrated or described as part of one embodiment can be used with another embodiment to yield a still further embodiment. Thus, it is intended that the present disclosure cover such alterations, variations, and equivalents.)
Examiner Note: Instant Spec [0022] When each of the components of the action planning apparatus 1 is the dedicated hardware as shown in FIG. 2A, the processing circuit 12 corresponds to a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination thereof, for example. Functions of the components of the action planning apparatus 1 may be achieved by respective processing circuits 12 or may collectively be achieved by a single processing circuit 12.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to be motivated to modify Marchetti-Bowick1 with Marchetti-Bowick2 in order to calculate a plurality of modes in parallel using multiple circuitries or programmed processors [Marchetti-Bowick2 – 0125, 0135, 0155].
Claim 19.
Marchetti-Bowick1 in combination with the references taught in Claim 11 teach those respective limitations. Marchetti-Bowick1 further teaches:
wherein the scene generation circuitry generates the one or more pieces of scene information using the surroundings information and
([abstract] determining, by the computing system, a candidate motion plan for the autonomous vehicle [0067] The one or more autonomy system sensors 114 can be configured to generate and/or store data including the autonomy sensor data 116 associated with one or more objects that are proximate to the vehicle 102… autonomy sensor data 116 can be indicative of locations associated with the one or more objects within the surrounding environment of the vehicle 102 at one or more times. [0071] The perception system 124 can identify one or more objects that are proximate to the vehicle 102 based on autonomy sensor data 116 received from the autonomy system sensors 114. In particular, in some implementations, the perception system 124 can determine, for each object, local scene data 130 that describes a current state of such object… the perception system 124 can determine local scene data 130 for each object over a number of iterations. In particular, the perception system 124 can update the local scene data 130 for each object at each iteration. Thus, the perception system 124 can detect and track objects (e.g., vehicles, bicycles, pedestrians, etc.) that are proximate to the vehicle 102 over time, and thereby produce a presentation of the world around an vehicle 102 along with its state (e.g., a presentation of the objects of interest within a scene at the current time along with the states of the objects) [Claim 1] [0125] one or more units may be a part of or included in one or more other units. These means can include processor(s), microprocessor(s), graphics processing unit(s), logic circuit(s), dedicated circuit(s), application-specific integrated circuit(s))
external instruction information being information indicating an external instruction on driving of the moving body, and
[[0028] the local scene data can include the autonomous vehicle's current state. The current state of the autonomous vehicle can include current velocity, autonomous vehicle system conditions, autonomous vehicle energy/fuel levels, or any other metrics associated with the autonomous vehicle. As an example, the current state of the autonomous vehicle can indicate that a LIDAR sensor on the rear of the vehicle is not functioning within normal parameters. As another example, the current state may indicate that the autonomous vehicle possesses movement capabilities that enable a certain type of motion trajectory (e.g., an engine that can produce an amount of acceleration required to perform a certain merge operation, etc.) [0032] A candidate motion plan can be determined for the autonomous vehicle. The candidate motion plan can include a target motion trajectory for the vehicle and/or certain driving maneuvers (e.g., accelerating, decelerating, merging lanes, etc.). [0062] The one or more remote computing devices 106 can include one or more computing devices (e.g., a desktop computing device, a laptop computing device, a smart phone, and/or a tablet computing device) that can receive input or instructions from a user or exchange signals or data with an item or other computing device or computing system (e.g., the operations computing system 104). Further, the one or more remote computing devices 106 can be used to determine and/or modify one or more states of the vehicle 102 including a location (e.g., a latitude and longitude), a velocity, acceleration, a trajectory, and/or a path of the vehicle 102 based in part on signals or data exchanged with the vehicle 102. [0070] The autonomy computing system 120 can include a perception system 124, a prediction system 126, a motion planning system 128, and/or other systems that cooperate to perceive the surrounding environment of the vehicle 102 and determine a motion plan for controlling the motion of the vehicle 102 accordingly.)
Examiner Note: Instant spec 0096 “The external instruction information is information indicating an instruction on driving of the host vehicle 20 from the external apparatus 15 and is, specifically, an instruction to be stopped at a stop, an instruction to be stopped on the spot, an instruction to resume on the spot, an instruction to enter a parking space, an instruction to exit the parking space, an instruction to allow passing at an intersection, an instruction to prohibit passing, or the like.”
the plural mode calculation [circuitries] calculate the plurality of modes using the external instruction information and the one or more pieces of scene information.
([0037] In some implementations, a plurality of candidate motion plans can be determined for the autonomous vehicle. [0061] remote computing device 106 cause the one or more processors to perform operations and/or functions including operations and/or functions associated with the vehicle 102 including exchanging (e.g., sending and/or receiving) data or signals with the vehicle 102, monitoring the state of the vehicle 102, and/or controlling the vehicle 102. The one or more remote computing devices 106 can communicate (e.g., exchange data and/or signals) with one or more devices including the operations computing system 104 and the vehicle 102 via the communications network 108. [0062] The one or more remote computing devices 106 can include one or more computing devices (e.g., a desktop computing device, a laptop computing device, a smart phone, and/or a tablet computing device) that can receive input or instructions from a user or exchange signals or data with an item or other computing device or computing system (e.g., the operations computing system 104). Further, the one or more remote computing devices 106 can be used to determine and/or modify one or more states of the vehicle 102 including a location (e.g., a latitude and longitude), a velocity, acceleration, a trajectory, and/or a path of the vehicle 102 based in part on signals or data exchanged with the vehicle 102. [0073] motion planning system 128 can determine a motion plan and generate motion plan data 134 for the vehicle 102 based at least in part on the prediction data 132 (and/or other data). The motion plan data 134 can include vehicle actions with respect to the objects proximate to the vehicle 102 as well as the predicted movements…the motion planning system 128 can obtain and select one or more candidate motion plans based at least in part on the local scene data and/or the extracted actor prediction parameters. [0076] The motion planning system 128 can provide the motion plan data 134 with data indicative of the vehicle actions, a planned trajectory, and/or other operating parameters to the vehicle control systems 138 to implement the motion plan data 134 for the vehicle 102. [0061, 0068, 0070, claim 1])
Examiner Note: the candidate motion plans can be derived based at least in part on local scene data as well as other data which can be derived from remote computing devices which are used to determine and/or modify trajectories of the vehicle.
Marchetti-Bowick1 does not explicitly teach the following limitations, however Marchetti-Bowick2 teaches the following limitations:
circuitries
([0125] motion plan determination unit(s) 906, reactive prediction generation unit(s), and/or other means for performing the operations and functions described herein. In some implementations, one or more of the units may be implemented separately. In some implementations, one or more units may be a part of or included in one or more other units. These means can include processor(s), microprocessor(s), graphics processing unit(s), logic circuit(s), dedicated circuit(s), application specific integrated circuit(s ), programmable array logic, field-programmable gate array(s), controller(s), microcontroller(s), and/or other suitable hardware. The means can also, or alternately, include software control means implemented with a processor or logic circuitry for example [0135] The memory 1014 can also store computer-readable instructions 1018 that can be executed by the one or more processors 1012. [0153] [0155] the subject disclosure does not preclude inclusion of such modifications, variations and/or additions to the present subject matter as would be readily apparent to one of ordinary skill in the art. For instance, features illustrated or described as part of one embodiment can be used with another embodiment to yield a still further embodiment. Thus, it is intended that the present disclosure cover such alterations, variations, and equivalents.)
Examiner Note: Instant Spec [0022] When each of the components of the action planning apparatus 1 is the dedicated hardware as shown in FIG. 2A, the processing circuit 12 corresponds to a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination thereof, for example. Functions of the components of the action planning apparatus 1 may be achieved by respective processing circuits 12 or may collectively be achieved by a single processing circuit 12.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to be motivated to modify Marchetti-Bowick1 with Marchetti-Bowick2 in order to calculate a plurality of modes in parallel using multiple circuitries or programmed processors [Marchetti-Bowick2 – 0125, 0135, 0155].
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.
Claim(s) 15-18 & 20-29 is/are rejected under 35 U.S.C. 103 as being unpatentable over Marchetti-Bowick (US 20210188316) in view of Tavares (US 20180376357).
Claim 15.
Marchetti-Bowick in combination with the references taught in Claim 11 teach those respective limitations. Marchetti-Bowick further teaches:
wherein the mode selection circuitry selects, [using degrees of priority of the plurality of modes set in advance], one of the plurality of modes calculated by the plural mode calculation circuitries and outputs the selected one of the plurality of modes as the action of the moving body.
([0073] motion planning system 128 can determine a motion plan and generate motion plan data 134 for the vehicle 102 based at least in part on the prediction data 132 (and/or other data). The motion plan data 134 can include vehicle actions with respect to the objects proximate to the vehicle 102 as well as the predicted movements…the motion planning system 128 can obtain and select one or more candidate motion plans based at least in part on the local scene data and/or the extracted actor prediction parameters. [0075] The motion planning system 128 then can provide the selected motion plan to a vehicle controller that controls one or more vehicle controls (e.g., actuators or other devices that control gas flow, steering, braking, etc.) to execute the selected motion plan. [0098] Candidate motion plans can be determined based at least in part on a cost function that evaluates the current locations and/or predicted future locations and/or moving paths of the objects. For example, the cost function can describe a cost (e.g., over time) of adhering to a particular candidate motion plan. For example, the cost described by a cost function can increase when the autonomous vehicle approaches impact with another object and/or deviates from a preferred pathway (e.g., a predetermined travel route). [0125, 0135, 0153, 0155])
Marchetti-Bowick does not explicitly teach the following limitations, however Tavares teaches:
using degrees of priority of the modes set in advance
([0177] the rules/policies/functions/processes used to adapt the operating mode may be configured to minimize the amount of time that the AVs are looking for parking spots; [0219] The data repository 950 acts as storage for digital information representative of data and parameters including, for example, key performance indicators (KPIs), priorities, and policies and high-level goals, so that the AVs may operate in a manner consistent with such information. For example, one KPI of an AV may be the amount of time that transpires or the distance traveled when an AV that is empty (i.e., without a (e.g., passenger(s), good(s), data)). However, an AV may also have as a “priority” that the AV is to gather urban sensor data from a certain geographic area or region, but the AV may be subject to a “policy” that the AV is to travel without any detours when the AV is operating in Transport Mode. Goals of operation of one or more AVs of a fleet may be assigned levels or degrees of importance such as, for example, primary, secondary, tertiary, etc., to enable the AV system and cloud-based systems of the present disclosure to guide system behavior in a manner consistent with the operator of the fleet and/or third parties such as the managers of a government entity… Such use of KPIs and requirements for adherence to policies, priorities, and goals for AV operation may be represented in digital information stored in the data repository 950, and the AVs and/or cloud-based systems may take any or all of these constraints into account when making decisions and Mode/State transitions during the operation of the one or more AVs. [0158])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to be motivated to modify Marchetti-Bowick with Tavares in order to simultaneously or in parallel operate more than one mode for a moving autonomous vehicle [Tavares – 0189].
Claim 16.
Marchetti-Bowick in combination with the references taught in Claim 15 teach those respective limitations. Marchetti-Bowick further teaches:
address an obstacle present around the moving body.
([0098] Candidate motion plans can be determined based at least in part on a cost function that evaluates the current locations and/or predicted future locations and/or moving paths of the objects. For example, the cost function can describe a cost (e.g., over time) of adhering to a particular candidate motion plan. For example, the cost described by a cost function can increase when the autonomous vehicle approaches impact with another object and/or deviates from a preferred pathway (e.g., a predetermined travel route))
Marchetti-Bowick does not explicitly teach the following limitations, however Tavares teaches:
wherein the degrees of priority are set to give priority to a mode to
([0177] the rules/policies/functions/processes used to adapt the operating mode may be configured to minimize the amount of time that the AVs are looking for parking spots; [0219] [0158])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to be motivated to modify Marchetti-Bowick with Tavares in order to simultaneously or in parallel operate more than one mode for a moving autonomous vehicle [Tavares – 0189].
Claim 17.
Marchetti-Bowick in combination with the references taught in Claim 15 teach those respective limitations. Marchetti-Bowick does not explicitly teach the following limitations, however
Tavares teaches:
wherein the degrees of priority are set to give priority to a mode having a lower target speed.
([0177] the rules/policies/functions/processes used to adapt the operating mode may be configured to minimize the amount of time that the AVs are looking for parking spots; [0184] AVs may, for example, travel over particular routes at lower speeds for, by way of example and not limitation, sightseeing reasons, may load additional data, and/or may actively anticipate traffic congestion. While each of these types of Transport Mode operation may have a different validated business model to support it, aspects of the present disclosure enable a high level of flexibility in addressing the needs of the clients [0219] [0158])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to be motivated to modify Marchetti-Bowick with Tavares in order to simultaneously or in parallel operate more than one mode for a moving autonomous vehicle [Tavares – 0189].
Claim 18.
Marchetti-Bowick in combination with the references taught in Claim 15 teach those respective limitations. Marchetti-Bowick does not explicitly teach the following limitations, however Tavares teaches:
wherein the degrees of priority are set to give priority to a mode having
([0177] the rules/policies/functions/processes used to adapt the operating mode may be configured to minimize the amount of time that the AVs are looking for parking spots; [0219] [0158])
a smaller distance from a current position to a target position of the moving body.
([0129] AV behavior and/or actions may be taken in to account by the system, and the system may consider the expected distance and/or time to arrive at a certain location (e.g., charging station, parking place) in the calculation of trip fees. [0219] The data repository 950 acts as storage for digital information representative of data and parameters including, for example, key performance indicators (KPIs), priorities, and policies and high-level goals, so that the AVs may operate in a manner consistent with such information. For example, one KPI of an AV may be the amount of time that transpires or the distance traveled when an AV that is empty (i.e., without a (e.g., passenger(s), good(s), data)).)
Claim 20.
Marchetti-Bowick teaches the following limitations:
An action planning apparatus comprising: scene generation circuitry to generate, using surroundings information on surroundings of a moving body including an autonomous driving vehicle, one or more pieces of scene information indicating a situation in which the moving body is placed;
([abstract] determining, by the computing system, a candidate motion plan for the autonomous vehicle [0067] The one or more autonomy system sensors 114 can be configured to generate and/or store data including the autonomy sensor data 116 associated with one or more objects that are proximate to the vehicle 102… autonomy sensor data 116 can be indicative of locations associated with the one or more objects within the surrounding environment of the vehicle 102 at one or more times. [0071] The perception system 124 can identify one or more objects that are proximate to the vehicle 102 based on autonomy sensor data 116 received from the autonomy system sensors 114. In particular, in some implementations, the perception system 124 can determine, for each object, local scene data 130 that describes a current state of such object… the perception system 124 can determine local scene data 130 for each object over a number of iterations. In particular, the perception system 124 can update the local scene data 130 for each object at each iteration. Thus, the perception system 124 can detect and track objects (e.g., vehicles, bicycles, pedestrians, etc.) that are proximate to the vehicle 102 over time, and thereby produce a presentation of the world around an vehicle 102 along with its state (e.g., a presentation of the objects of interest within a scene at the current time along with the states of the objects) [Claim 1] [0095] At 306, method 300 can include obtaining a candidate motion plan for the autonomous vehicle. The candidate motion plan can include a target motion trajectory for the vehicle and/or certain driving maneuvers (e.g., accelerating, decelerating, merging lanes, etc.). [0125] one or more units may be a part of or included in one or more other units. These means can include processor(s), microprocessor(s), graphics processing unit(s), logic circuit(s), dedicated circuit(s), application-specific integrated circuit(s))
plural mode calculation circuitries to calculate, when one piece of scene information is generated by the scene generation circuitry, one or more modes as candidates for action that the moving body can take using the one piece of scene information and
([0039] In some implementations, autonomous vehicle systems can include a prediction system and a motion planning system. The prediction system can be configured to obtain and/or generate local scene data (e.g., actor speeds, predicted actor trajectories, etc.). In some implementations, the prediction system can include the machine-learned parameter extraction model. The motion planning system can determine and select one or more candidate motion plans based at least in part on the local scene data and/or the extracted actor parameters. A candidate motion plan (e.g., a suggested trajectory for an autonomous vehicle, etc.) can include a step or a series of steps (e.g., accelerate, decelerate, merge lanes, etc.) for the autonomous vehicle to implement at a corresponding series of times (e.g., a schedule of driving maneuvers, etc.) [0071] The perception system 124 can identify one or more objects that are proximate to the vehicle 102 based on autonomy sensor data 116 received from the autonomy system sensors 114. In particular, in some implementations, the perception system 124 can determine, for each object, local scene data 130 that describes a current state of such object. the local scene data 130 for each object can describe an estimate of the object's: current location (also referred to as position); current speed; current heading (which may also be referred to together as velocity); current acceleration; current orientation; size/footprint (e.g., as represented by a bounding shape such as a bounding polygon or polyhedron); class of characterization (e.g., vehicle class versus pedestrian class versus bicycle class versus other class); yaw rate; and/or other state information. [0073] motion planning system 128 can determine a motion plan and generate motion plan data 134 for the vehicle 102 based at least in part on the prediction data 132 (and/or other data). The motion plan data 134 can include vehicle actions with respect to the objects proximate to the vehicle 102 as well as the predicted movements…the motion planning system 128 can obtain and select one or more candidate motion plans based at least in part on the local scene data and/or the extracted actor prediction parameters. [0076] The motion planning system 128 can provide the motion plan data 134 with data indicative of the vehicle actions, a planned trajectory, and/or other operating parameters to the vehicle control systems 138 to implement the motion plan data 134 for the vehicle 102. [0072, claim 1] [0125, 0135, 0153, 0155])
calculate, when a plurality of pieces of scene information are generated by the scene generation circuitry, a plurality of modes as candidates for action [that the moving body can take in parallel] using the plurality of pieces of scene information; and
([0037] In some implementations, a plurality of candidate motion plans can be determined for the autonomous vehicle. [0073] motion planning system 128 can determine a motion plan and generate motion plan data 134 for the vehicle 102 based at least in part on the prediction data 132 (and/or other data). The motion plan data 134 can include vehicle actions with respect to the objects proximate to the vehicle 102 as well as the predicted movements…the motion planning system 128 can obtain and select one or more candidate motion plans based at least in part on the local scene data and/or the extracted actor prediction parameters. [0076] The motion planning system 128 can provide the motion plan data 134 with data indicative of the vehicle actions, a planned trajectory, and/or other operating parameters to the vehicle control systems 138 to implement the motion plan data 134 for the vehicle 102. [claim 1])
Examiner Note: A plurality of candidate motion plans for action are representative of the plurality of modes.
mode selection circuitry to select one of the plurality of modes calculated by the plural mode calculation circuitries and output the selected one of the plurality of modes as action of the moving body.
([0073] motion planning system 128 can determine a motion plan and generate motion plan data 134 for the vehicle 102 based at least in part on the prediction data 132 (and/or other data). The motion plan data 134 can include vehicle actions with respect to the objects proximate to the vehicle 102 as well as the predicted movements…the motion planning system 128 can obtain and select one or more candidate motion plans based at least in part on the local scene data and/or the extracted actor prediction parameters. [0075] The motion planning system 128 then can provide the selected motion plan to a vehicle controller that controls one or more vehicle controls (e.g., actuators or other devices that control gas flow, steering, braking, etc.) to execute the selected motion plan. [0125, 0135, 0153, 0155])
Marchetti-Bowick does not explicitly teach the following limitations, however Tavares teaches:
[a plurality of modes as candidates for action] that the moving body can take in parallel
(Tavares [0154] A service manager of each AV, such as the service manager block 507 of FIG. 5, may share the global context of an AV at a particular point in time. An AV global context may include what may be referred to herein as an AV context mode and an AV context state. An AV context mode may include, for example, transportation mode (e.g., when the AV is transporting people and/or goods), charging mode (e.g., when the AV is stopped and is in the process of charging the batteries of the AV), parked mode (e.g., when the AV is stationary in a parking location, waiting on a new job or activity), moving mode (e.g., the AV just finished its most recent job/activity and does not yet have a new job/activity, so the AV will seek a parking location and/or the AV is approaching the starting point for new job/activity (e.g., picking up something and/or someone)), and offline/idle mode (e.g., not in any other mode). An AV context state may include, for example, a context state in which the AV acts as an Internet service provider (i.e., “Internet”), a context state in which the AV performs sensor data acquisition (i.e., “data sensing”), a context state in which the AV acts as a “middle node” (e.g., extending connectivity to others by routing data), and a context state in which the AV is handling an emergency (i.e., “emergency”). [0188] In accordance with various aspects of the present disclosure, an AV may operate simultaneously in more than one Mode. [0189] In accordance with some AV operating scenarios described herein, simultaneous operation in Transport Mode and Charging Mode may be possible. For example, Charging Mode may be triggered during braking, to recover AV kinetic energy. In addition, an AV equipped with solar panels may, for example, simultaneously operate in Transport Mode and Charging Mode, in Parked Mode and Charging Mode, and in Offline Mode and Charging Mode. [0199])
Examiner Note: Instant Spec [0045] six modes are set: path following (hereinafter referred to as "LF (Lane15 Following)"); deceleration and stop (hereinafter referred to as "ST (STop)"); intersection approaching travel (hereinafter referred to as "AI (Approach Intersection)"); stop in front of a stop line (hereinafter referred to as "SI (Stop Intersection)"); intersection crossing (hereinafter referred to as "CI (Cross Intersection)"); and emergency stop (hereinafter referred to as "ES (Emergency Stop)").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to be motivated to modify Marchetti-Bowick with Tavares in order to simultaneously or in parallel operate more than one mode for a moving autonomous vehicle [Tavares – 0189].
Claim 21.
Rejected using the same rationale as Claim 12, except relying on the combination of Marchetti-Bowick and Tavares.
Claim 22.
Rejected using the same rationale as Claim 13, except relying on the combination of Marchetti-Bowick and Tavares.
Claim 23.
Rejected using the same rationale as Claim 14, except relying on the combination of Marchetti-Bowick and Tavares.
Claim 24.
Marchetti-Bowick in combination with the references taught in Claim 20 teach those respective limitations. Marchetti-Bowick further teaches:
wherein the mode selection circuitry selects, [using degrees of priority of the plurality of modes set in advance], one of the plurality of modes calculated by the plural mode calculation circuitries and outputs the selected one of the plurality of modes as the action of the moving body.
([0073] motion planning system 128 can determine a motion plan and generate motion plan data 134 for the vehicle 102 based at least in part on the prediction data 132 (and/or other data). The motion plan data 134 can include vehicle actions with respect to the objects proximate to the vehicle 102 as well as the predicted movements…the motion planning system 128 can obtain and select one or more candidate motion plans based at least in part on the local scene data and/or the extracted actor prediction parameters. [0075] The motion planning system 128 then can provide the selected motion plan to a vehicle controller that controls one or more vehicle controls (e.g., actuators or other devices that control gas flow, steering, braking, etc.) to execute the selected motion plan. [0098] Candidate motion plans can be determined based at least in part on a cost function that evaluates the current locations and/or predicted future locations and/or moving paths of the objects. For example, the cost function can describe a cost (e.g., over time) of adhering to a particular candidate motion plan. For example, the cost described by a cost function can increase when the autonomous vehicle approaches impact with another object and/or deviates from a preferred pathway (e.g., a predetermined travel route). [0125, 0135, 0153, 0155])
Marchetti-Bowick does not explicitly teach the following limitations, however Tavares teaches:
using degrees of priority of the plurality of modes set in advance
([0177] the rules/policies/functions/processes used to adapt the operating mode may be configured to minimize the amount of time that the AVs are looking for parking spots; [0219] The data repository 950 acts as storage for digital information representative of data and parameters including, for example, key performance indicators (KPIs), priorities, and policies and high-level goals, so that the AVs may operate in a manner consistent with such information. For example, one KPI of an AV may be the amount of time that transpires or the distance traveled when an AV that is empty (i.e., without a (e.g., passenger(s), good(s), data)). However, an AV may also have as a “priority” that the AV is to gather urban sensor data from a certain geographic area or region, but the AV may be subject to a “policy” that the AV is to travel without any detours when the AV is operating in Transport Mode. Goals of operation of one or more AVs of a fleet may be assigned levels or degrees of importance such as, for example, primary, secondary, tertiary, etc., to enable the AV system and cloud-based systems of the present disclosure to guide system behavior in a manner consistent with the operator of the fleet and/or third parties such as the managers of a government entity… Such use of KPIs and requirements for adherence to policies, priorities, and goals for AV operation may be represented in digital information stored in the data repository 950, and the AVs and/or cloud-based systems may take any or all of these constraints into account when making decisions and Mode/State transitions during the operation of the one or more AVs. [0158])
Claim 25.
Rejected using the same rationale as Claim 16.
Claim 26.
Rejected using the same rationale as Claim 17.
Claim 27.
Rejected using the same rationale as Claim 18.
Claim 28.
Rejected using the same rationale as Claim 19, except relying on the combination of Marchetti-Bowick and Tavares.
Claim 29.
Rejected using the same rationale as Claim 20.
Conclusion
The prior art made of record, and not relied upon, considered pertinent to applicant' s disclosure or directed to the state of art is listed on the enclosed PTO-892.
The following is a brief description for relevant prior art that was cited but not applied:
Levandowski (US 2020019165) discusses a system and method for determining a vehicles autonomous driving mode from a plurality of autonomous modes.
Schleede (US 12077186) discusses techniques for determining whether to yield a vehicle to an oncoming object based on a stationary object.
McGill (US 20210269051) provides systems and methods for parallel autonomy of a vehicle.
James (US 10556600) provides systems and methods for assessment of human driving performance using autonomous vehicles.
Sato (US 20170008522) provides a control system for an automated driving vehicle.
Woon (US 20200346643) provides a method for controlling an autonomous vehicle based on an operational risk determined for the autonomous vehicle.
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/ABDULMAJEED AZIZ/Supervisory Patent Examiner, Art Unit 2875
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