DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) filed 10/31/2024 has been received and considered by the examiner. The submission is in compliance with the provisions of 37 CFR 1.97.
The information disclosure statement (IDS) filed 10/22/2024 has been received and considered by the examiner. The submission is in compliance with the provisions of 37 CFR 1.97.
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 1-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
In January, 2019 (updated October 2019), the USPTO released new examination guidelines setting forth a two-step inquiry for determining whether a claim is directed to non-statutory subject matter. According to the guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claim 1 is directed toward non-statutory subject matter, as shown below:
STEP 1: Does claim 1 fall within one of the statutory categories? Yes. The claim is directed toward an apparatus.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? Yes, the claim is directed to an abstract idea.
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
Claim 1. A passage point generation apparatus generating a passage point which a moving body should reach, comprising:
target state candidate generation circuitry selecting a plurality of target position candidates from a plurality of travelable positions and calculating a plurality of target state candidates including the plurality of target position candidates which has been selected based on surrounding environment information of the moving body and a state amount of the moving body;
and local target state generation circuitry calculating a local target state as a local target state reachable in any of the plurality of target state candidates in an intermediate point of a trajectory toward a surrounding area of the plurality of target state candidates and outputting the local target state as the passage point.
The method in claim 1, specifically the limitations emphasized above, is a mental process that can be practicably performed in the human mind and, therefore, an abstract idea. It merely consists of selecting a plurality of target position candidates and calculating a local target state. This is equivalent to a person mentally viewing the environment, choosing target position candidates, and determining the local target state.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? No, the claim does not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
In the present case, the additional limitations beyond the above-noted abstract ideas are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the abstract “idea”).
Claim 1. A passage point generation apparatus generating a passage point which a moving body should reach, comprising:
target state candidate generation circuitry selecting a plurality of target position candidates from a plurality of travelable positions and calculating a plurality of target state candidates including the plurality of target position candidates which has been selected based on surrounding environment information of the moving body and a state amount of the moving body;
and local target state generation circuitry calculating a local target state as a local target state reachable in any of the plurality of target state candidates in an intermediate point of a trajectory toward a surrounding area of the plurality of target state candidates and outputting the local target state as the passage point.
Claim 1 does not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. The step of “outputting the local target state as the passage point” is recited at a high level of generality and amounts to mere post solution actions, which is a form of extra solution activity. The limitations “A passage point generation apparatus generating a passage point which a moving body should reach, comprising: target state candidate generation circuitry” and “local target state generation circuitry” are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The passage point generation apparatus generating a passage point which a moving body should reach, comprising: target state candidate generation circuitry and local target state generation circuitry merely describe how to generally “apply” the otherwise mental judgments in a generic or general purpose computing environment. The passage point generation apparatus generating a passage point which a moving body should reach, comprising: target state candidate generation circuitry and local target state generation circuitry are recited at a high level of generality and merely automate the selecting, calculating and outputting steps. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(I). Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No, the claim does not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Regarding Step 2B of the 2019 PEG, independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claims do not integrate the abstract idea into a practical application.
As discussed above with respect to integration of the abstract idea into a practical application, the additional limitation(s) of “A passage point generation apparatus generating a passage point which a moving body should reach, comprising: target state candidate generation circuitry” and “local target state generation circuitry” is/are merely means to apply the exception and do not amount to “significantly more”, as adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984, are not sufficient to amount to significantly more than the judicial exception.
Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The additional limitation of “outputting the local target state as the passage point” are well-understood, routine, and conventional activities because the specification does not provide any indication that the selecting, calculating, and outputting steps are performed using anything other than a conventional computer. See also MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures |, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TL! Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and O/P Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere performance of an action is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). Hence, the claim is not patent eligible.
Thus, since claim 1 is: (a) directed toward an abstract idea, (b) does not recite additional elements that integrate the judicial exception into a practical application, and (c) does not recite additional elements that amount to significantly more than the judicial exception, it is clear that claim 1 is directed towards non-statutory subject matter.
Dependent claims 2-13 further limit the abstract idea without integrating the abstract idea into practical application or adding significantly more, such as the limitations in claim 6 that amount to insignificant extra solution activity using a similar analysis applied to claim 1 above.
As such, claims 1-13 are rejected under 35 USC 101 as being drawn to an abstract idea without significantly more, and thus are ineligible.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 2, and 5 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Mochida (US 20190300054 A1).
Regarding Claim 1, Mochida teaches A passage point generation apparatus generating a passage point which a moving body should reach, comprising: target state candidate generation circuitry selecting a plurality of target position candidates from a plurality of travelable positions and calculating a plurality of target state candidates including the plurality of target position candidates which has been selected based on surrounding environment information of the moving body and a state amount of the moving body (See at least paragraph [0035], “As illustrated in FIG. 3, the vehicle controller includes a vehicle ECU (electronic control unit) 10 that is mounted on the subject vehicle. The vehicle controller further includes a camera 1, a sonar 2, and a vehicle condition detection sensor 3 that are connected to input side of the vehicle ECU 10. The vehicle controller further includes a steering device 21 connected to output side of the vehicle ECU 10” and paragraph [0044], “The parking route generation unit 13 is a functional block to generate the parking route to park the subject vehicle at the target position without interfering with the obstacles, based on the surroundings information transmitted from the camera 1 and the sonar 2 and the vehicle condition transmitted from the vehicle condition detection sensor 3. The parking route generation unit 13 specifically includes a first route generation unit 131 and a second route generation unit 132. The first route generation unit 131 generates the first route that is a parking route to park the subject vehicle from the current position to the temporary target position, by use of the recognition result transmitted from the temporary target position recognition unit 12. FIG. 7 is a diagram to explain operation to generate the first route. FIG. 7 illustrates the parking route on which the vehicle moves left forward once and then moves right rearward. The first route preferably includes a parking route that causes the subject vehicle to turn at a minimum turning radius.”); and local target state generation circuitry calculating a local target state as a local target state reachable in any of the plurality of target state candidates in an intermediate point of a trajectory toward a surrounding area of the plurality of target state candidates and outputting the local target state as the passage point (See at least paragraph [0044], “The parking route generation unit 13 is a functional block to generate the parking route to park the subject vehicle at the target position without interfering with the obstacles, based on the surroundings information transmitted from the camera 1 and the sonar 2 and the vehicle condition transmitted from the vehicle condition detection sensor 3. The parking route generation unit 13 specifically includes a first route generation unit 131 and a second route generation unit 132. The first route generation unit 131 generates the first route that is a parking route to park the subject vehicle from the current position to the temporary target position, by use of the recognition result transmitted from the temporary target position recognition unit 12. FIG. 7 is a diagram to explain operation to generate the first route. FIG. 7 illustrates the parking route on which the vehicle moves left forward once and then moves right rearward. The first route preferably includes a parking route that causes the subject vehicle to turn at a minimum turning radius”, paragraph [0045], “Further, the second route generation unit 132 generates the second route that is a corrected parking route to park the subject vehicle from the middle of the first route to the target position, by use of the recognition result transmitted from the target position recognition unit 11. FIG. 8 is a diagram to explain operation to generate the second route. FIG. 8 illustrates the parking route on which the vehicle moves rearward from a predetermined designated position in the first route to the target position. The predetermined designated position is a position that allows for generation of the achievable second route. In the example illustrated in FIG. 8, a position where a distance in the +Y direction from the coordinate origin to the center position of the rear wheel axle of the subject vehicle becomes a predetermined distance (e.g., 5000 mm to 6000 mm) or more is set as the designated position” and paragraph [0046], “Note that the designated position is preferably a position allowing for recognition of the target position with high precision. In other words, the target position can be updated to a more precise position by use of the latest surroundings information obtained while the subject vehicle follows the first route. Therefore, the designated position is set to, for example, a position where the target position can be recognized with high precision in the update operation of the target position. This enables the second route generation unit 132 to generate the second route toward the precise target position.”).
Regarding Claim 2, Mochida teaches The passage point generation apparatus according to claim 1, as set for in the anticipation rejection above. Mochida teaches wherein the target state candidate generation circuitry generates a set of state amounts in which each of the target states adjacent to each other is within a predetermined range so that the moving body can reach any of the target state candidates when the moving body reaches the local target state (See at least paragraph [0045], “Further, the second route generation unit 132 generates the second route that is a corrected parking route to park the subject vehicle from the middle of the first route to the target position, by use of the recognition result transmitted from the target position recognition unit 11. FIG. 8 is a diagram to explain operation to generate the second route. FIG. 8 illustrates the parking route on which the vehicle moves rearward from a predetermined designated position in the first route to the target position. The predetermined designated position is a position that allows for generation of the achievable second route. In the example illustrated in FIG. 8, a position where a distance in the +Y direction from the coordinate origin to the center position of the rear wheel axle of the subject vehicle becomes a predetermined distance (e.g., 5000 mm to 6000 mm) or more is set as the designated position”, and paragraph [0046], “Note that the designated position is preferably a position allowing for recognition of the target position with high precision. In other words, the target position can be updated to a more precise position by use of the latest surroundings information obtained while the subject vehicle follows the first route. Therefore, the designated position is set to, for example, a position where the target position can be recognized with high precision in the update operation of the target position. This enables the second route generation unit 132 to generate the second route toward the precise target position.” The system limits target state quantities based on vehicle dynamics and predetermined distance thresholds such that adjacent target states are within a predetermined range and the vehicle can reach any of the target state candidates upon reaching the local target state.).
Regarding Claim 5, Mochida teaches The passage point generation apparatus according to claim 1, as set for in the anticipation rejection above. Mochida teaches further comprising global target state generation circuitry generating a more global target state than each target state of the plurality of target state candidates and outputting the target state as a global target state, wherein the target state candidate generation circuitry performs calculation so that any of the target state candidates can reach the global target state (See at least paragraph [0044], “The parking route generation unit 13 is a functional block to generate the parking route to park the subject vehicle at the target position without interfering with the obstacles, based on the surroundings information transmitted from the camera 1 and the sonar 2 and the vehicle condition transmitted from the vehicle condition detection sensor 3. The parking route generation unit 13 specifically includes a first route generation unit 131 and a second route generation unit 132. The first route generation unit 131 generates the first route that is a parking route to park the subject vehicle from the current position to the temporary target position, by use of the recognition result transmitted from the temporary target position recognition unit 12. FIG. 7 is a diagram to explain operation to generate the first route. FIG. 7 illustrates the parking route on which the vehicle moves left forward once and then moves right rearward. The first route preferably includes a parking route that causes the subject vehicle to turn at a minimum turning radius”, paragraph [0045], “Further, the second route generation unit 132 generates the second route that is a corrected parking route to park the subject vehicle from the middle of the first route to the target position, by use of the recognition result transmitted from the target position recognition unit 11. FIG. 8 is a diagram to explain operation to generate the second route. FIG. 8 illustrates the parking route on which the vehicle moves rearward from a predetermined designated position in the first route to the target position. The predetermined designated position is a position that allows for generation of the achievable second route. In the example illustrated in FIG. 8, a position where a distance in the +Y direction from the coordinate origin to the center position of the rear wheel axle of the subject vehicle becomes a predetermined distance (e.g., 5000 mm to 6000 mm) or more is set as the designated position” and paragraph [0046], “Note that the designated position is preferably a position allowing for recognition of the target position with high precision. In other words, the target position can be updated to a more precise position by use of the latest surroundings information obtained while the subject vehicle follows the first route. Therefore, the designated position is set to, for example, a position where the target position can be recognized with high precision in the update operation of the target position. This enables the second route generation unit 132 to generate the second route toward the precise target position.” The system generates a final target position as a global target state and selects immediate target states such that the vehicle can reach the final target position from any of the intermediate target states.).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 3, 4, and 7-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mochida (US 20190300054 A1) in view of Wang (US 9969386 B1).
Regarding Claim 3, Mochida teaches The passage point generation apparatus according to claim 1, as set for in the anticipation rejection above. Mochida does not explicitly disclose, however, Wang, in the same field of endeavor, teaches wherein the target state candidate generation circuitry performs calculation so that any of the target state candidates is within a reachable region which the moving body can dynamically reach (See at least Col. 13 lines 1-30, “The method samples 550 a point in the state space of the parking lot to produce a sampled state. The sampled state is rejected 555 if all states corresponding to the nodes of the geometrical graph are within 560 a non-reachable area of the sampled state. Otherwise, the method determines 570 a nearest node of the geometric graph having a state nearest to the sampled state and adds 580 a node for the sampled state to the geometric graph and connecting the added node with the nearest node via an edge if the edge is collision free.” The system performs calculations such that the target state candidates are within a region dynamically reachable by the moving body, because sampled states located in non-reachable areas are rejected.).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the invention of Mochida with the teachings of Wang such that the vehicle system of Mochida is further configured to perform calculation so that any of the target state candidates is within a reachable region which the moving body can dynamically reach, as taught by Wang (See Col. 13 lines 1-30.), with a reasonable expectation of success. The motivation for doing so would be predicting safe paths to avoid obstacles as well as optimizing vehicle operation criteria, as taught by Wang (See Col. 1 lines 1-20.).
Regarding Claim 4, Mochida teaches The passage point generation apparatus according to claim 1, as set for in the anticipation rejection above. Mochida does not explicitly disclose, however, Wang, in the same field of endeavor, teaches wherein the target state candidate generation circuitry performs calculation so that the moving body can reach any of the target state candidates by traveling in consideration of ride quality of the moving body (See at least Col. 4 lines 1-20, “One embodiment uses a biased sampling to guide state sampling for constructing kinematic graphs. Additionally, or alternatively, one embodiment uses an approximate reachable set into the sampling step to improve the quality of sampled states. By taking the approximate reachable set into account, sampled states which are difficult or costly to connect are rejected. This treatment can reduce computation time wasted in collision detection due to inefficient samples, and also provide a set of waypoints which enable fast construction of the kinematic graph.” The system calculates target states while improving the quality of travel by rejecting states that are difficult or costly to connect, which corresponds to consideration of ride quality.).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the invention of Mochida with the teachings of Wang such that the vehicle system of Mochida is further configured to perform calculation so that the moving body can reach any of the target state candidates by traveling in consideration of ride quality of the moving body, as taught by Wang (See Col. 4 lines 1-20.), with a reasonable expectation of success. The motivation for doing so would be predicting safe paths to avoid obstacles as well as optimizing vehicle operation criteria, as taught by Wang (See Col. 1 lines 1-20.).
Regarding Claim 7, Mochida teaches The passage point generation apparatus according to claim 1, as set for in the anticipation rejection above. Mochida does not explicitly disclose, however, Wang, in the same field of endeavor, teaches wherein the target state candidate generation circuitry includes: virtual trajectory generation circuitry generating a plurality of virtual trajectories passing through a plurality of target states (See at least Col. 13 lines 30-45, “The geometric graph includes nodes and edges representing geometric connections between the nodes such that the initial node is connected with the target node. Given the geometric graph, there can be many geometric paths from the initial state to the target state. It is advantageous to select a geometric path from the geometric graph that reduces a certain cost function. For example, one embodiment selects the geometric path by performing two steps: a) determining a cost for each node, where the node cost represents the minimal cost from the state specified by the node to the target state; b) starting with the initial node, selecting a set of nodes according to the node cost, where the cost of the initial node reaches minimum only if the vehicle passes through the set of nodes.”); virtual trajectory evaluation circuitry evaluating the plurality of virtual trajectories based on a dynamics limitation of the moving body (See at least Col. 13 lines 1-30, “The method samples 550 a point in the state space of the parking lot to produce a sampled state. The sampled state is rejected 555 if all states corresponding to the nodes of the geometrical graph are within 560 a non-reachable area of the sampled state. Otherwise, the method determines 570 a nearest node of the geometric graph having a state nearest to the sampled state and adds 580 a node for the sampled state to the geometric graph and connecting the added node with the nearest node via an edge if the edge is collision free.”); and target state candidate calculation circuitry calculating the plurality of target states reachable along a virtual trajectory within the limitation as the plurality of target state candidates (See at least Col. 12 lines 50-65, “Additionally, or alternatively, some embodiments perform the sampling using a reachability criterion. According to the reachability criterion, the sample in the state space is preserved only if that sample is reachable from the already constructed graph. In one embodiment, to avoid usage of the dynamic of the vehicle to test reachability, the reachability is defined as an absence of non-reachability, and nonreachability is a predetermined area near the sides of the vehicle.”).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the invention of Mochida with the teachings of Wang such that the vehicle system of Mochida is further configured to utilize virtual trajectory generation circuitry generating a plurality of virtual trajectories passing through a plurality of target states, evaluating the plurality of virtual trajectories based on a dynamics limitation of the moving body, and target state candidate calculation circuitry calculating the plurality of target states reachable along a virtual trajectory within the limitation as the plurality of target state candidates, as taught by Wang (See Col. 12 lines 50-65, Col. 13 lines 1-45.), with a reasonable expectation of success. The motivation for doing so would be predicting safe paths to avoid obstacles as well as optimizing vehicle operation criteria, as taught by Wang (See Col. 1 lines 1-20.).
Regarding Claim 8, Mochida teaches The passage point generation apparatus according to claim 1, as set for in the anticipation rejection above. Mochida does not explicitly disclose, however, Wang, in the same field of endeavor, teaches wherein the local target state generation circuitry sets an optional position on a virtual trajectory reaching a target state candidate located closest to a center in the plurality of target state candidates calculated in the target state candidate calculation circuitry in the plurality of virtual trajectories to the local target state (See at least Col. 13 lines 30-45, “The geometric graph includes nodes and edges representing geometric connections between the nodes such that the initial node is connected with the target node. Given the geometric graph, there can be many geometric paths from the initial state to the target state. It is advantageous to select a geometric path from the geometric graph that reduces a certain cost function. For example, one embodiment selects the geometric path by performing two steps: a) determining a cost for each node, where the node cost represents the minimal cost from the state specified by the node to the target state; b) starting with the initial node, selecting a set of nodes according to the node cost, where the cost of the initial node reaches minimum only if the vehicle passes through the set of nodes.” The system evaluates multiple virtual trajectories and associated target state candidates to identify a representative target state candidate closest to a center of candidates based on cost evaluation, and sets a position along the virtual trajectory reaching that candidate as the local target state.).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the invention of Mochida with the teachings of Wang such that the vehicle system of Mochida is further configured to set an optional position on a virtual trajectory reaching a target state candidate located closest to a center in the plurality of target state candidates calculated in the target state candidate calculation circuitry in the plurality of virtual trajectories to the local target state, as taught by Wang (See Col. 13 lines 30-45.), with a reasonable expectation of success. The motivation for doing so would be predicting safe paths to avoid obstacles as well as optimizing vehicle operation criteria, as taught by Wang (See Col. 1 lines 1-20.).
Regarding Claim 9, Mochida teaches The passage point generation apparatus according to claim 1, as set for in the anticipation rejection above. Mochida does not explicitly disclose, however, Wang, in the same field of endeavor, teaches wherein the local target state generation circuitry limits a change of the local target state immediately before the moving body reaches the local target state (See at least Col. 13 lines 1-45, “The method repeats the sampling, the rejecting, the determining, and the adding until the initial node is connected to the target node. For example, in one embodiment, construction of the geometric graph stops as long as the initial and target geometric trees are connected. In another embodiment, construction of the geometric graph stops until certain number of sampled states are added to both the initial and target geometric trees.” The system limits changes to the located target state by stopping updates to the planned path when the target becomes reachable, corresponding to limiting changes to the local target state immediately before the moving body reaches the local target state.).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the invention of Mochida with the teachings of Wang such that the vehicle system of Mochida is further configured to limit a change of the local target state immediately before the moving body reaches the local target state, as taught by Wang (See Col. 13 lines 1-45.), with a reasonable expectation of success. The motivation for doing so would be predicting safe paths to avoid obstacles as well as optimizing vehicle operation criteria, as taught by Wang (See Col. 1 lines 1-20.).
Regarding Claim 10, Mochida teaches The passage point generation apparatus according to claim 1, as set for in the anticipation rejection above. Mochida does not explicitly disclose, however, Wang, in the same field of endeavor, teaches wherein the local target state generation circuitry performs weighting on the plurality of target state candidates based on a predetermined evaluation index, and calculates the local target state based on a value of a weight (See at least Col. 13 lines 30-45, “The geometric graph includes nodes and edges representing geometric connections between the nodes such that the initial node is connected with the target node. Given the geometric graph, there can be many geometric paths from the initial state to the target state. It is advantageous to select a geometric path from the geometric graph that reduces a certain cost function. For example, one embodiment selects the geometric path by performing two steps: a) determining a cost for each node, where the node cost represents the minimal cost from the state specified by the node to the target state; b) starting with the initial node, selecting a set of nodes according to the node cost, where the cost of the initial node reaches minimum only if the vehicle passes through the set of nodes.” The system evaluates target state candidates using cost as an evaluation index and selects candidates based on the minimum cost, corresponding to performing weighting based on a predetermined evaluation index.).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the invention of Mochida with the teachings of Wang such that the vehicle system of Mochida is further configured to performs weighting on the plurality of target state candidates based on a predetermined evaluation index, and calculates the local target state based on a value of a weight, as taught by Wang (See Col. 13 lines 30-45.), with a reasonable expectation of success. The motivation for doing so would be predicting safe paths to avoid obstacles as well as optimizing vehicle operation criteria, as taught by Wang (See Col. 1 lines 1-20.).
Regarding Claim 11, Mochida and Wang teach The passage point generation apparatus according to claim 7, as set forth in the obviousness rejection above. Mochida does not explicitly disclose, however, Wang, in the same field of endeavor, teaches wherein the target state candidate generation circuitry provides scores to the plurality of virtual trajectories based on a predetermined evaluation index, compares a score provided to each virtual trajectory and a threshold value, and sets a point where the moving body travels along the virtual trajectory having a score equal to or larger than the threshold value or smaller than the threshold value to the plurality of target state candidates (See at least Col. 4 lines 1-20, “One embodiment uses a biased sampling to guide state sampling for constructing kinematic graphs. Additionally, or alternatively, one embodiment uses an approximate reachable set into the sampling step to improve the quality of sampled states. By taking the approximate reachable set into account, sampled states which are difficult or costly to connect are rejected. This treatment can reduce computation time wasted in collision detection due to inefficient samples, and also provide a set of waypoints which enable fast construction of the kinematic graph” and Col. 13 lines 30-45, “The geometric graph includes nodes and edges representing geometric connections between the nodes such that the initial node is connected with the target node. Given the geometric graph, there can be many geometric paths from the initial state to the target state. It is advantageous to select a geometric path from the geometric graph that reduces a certain cost function. For example, one embodiment selects the geometric path by performing two steps: a) determining a cost for each node, where the node cost represents the minimal cost from the state specified by the node to the target state; b) starting with the initial node, selecting a set of nodes according to the node cost, where the cost of the initial node reaches minimum only if the vehicle passes through the set of nodes.” The system assigns cost values as scores to virtual trajectories, rejects trajectories and states that are costly or difficult to connect, and selects nodes among remaining trajectories as target state candidates.).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the invention of Mochida with the teachings of Wang such that the vehicle system of Mochida is further configured to utilize virtual trajectory generation circuitry generating a plurality of virtual trajectories passing through a plurality of target states, evaluating the plurality of virtual trajectories based on a dynamics limitation of the moving body, target state candidate calculation circuitry calculating the plurality of target states reachable along a virtual trajectory within the limitation as the plurality of target state candidates and providing scores to the plurality of virtual trajectories based on a predetermined evaluation index, compares a score provided to each virtual trajectory and a threshold value, and sets a point where the moving body travels along the virtual trajectory having a score equal to or larger than the threshold value or smaller than the threshold value to the plurality of target state candidates, as taught by Wang (See Col. 4 lines 1-20, Col. 12 lines 50-65, Col. 13 lines 1-45.), with a reasonable expectation of success. The motivation for doing so would be predicting safe paths to avoid obstacles as well as optimizing vehicle operation criteria, as taught by Wang (See Col. 1 lines 1-20.).
Regarding Claim 12, Mochida and Wang teach The passage point generation apparatus according to claim 7, as set forth in the obviousness rejection above. Mochida does not explicitly disclose, however, Wang, in the same field of endeavor, teaches wherein the local target state generation circuitry performs weighting on a virtual trajectory reaching the plurality of target state candidates calculated in the target state candidate calculation circuitry in in the plurality of virtual trajectories, and sets a state where a weighted average of an optional position on the virtual trajectory and a weight is obtained to the local target state (See at least Col. 13 lines 30-45, “The geometric graph includes nodes and edges representing geometric connections between the nodes such that the initial node is connected with the target node. Given the geometric graph, there can be many geometric paths from the initial state to the target state. It is advantageous to select a geometric path from the geometric graph that reduces a certain cost function. For example, one embodiment selects the geometric path by performing two steps: a) determining a cost for each node, where the node cost represents the minimal cost from the state specified by the node to the target state; b) starting with the initial node, selecting a set of nodes according to the node cost, where the cost of the initial node reaches minimum only if the vehicle passes through the set of nodes” and Col. 14 lines 25-45, “In another embodiment, the best geometric path is determined by three steps: a) trimming the geometric graph by removing all leaf nodes except the initial and target nodes, where a leaf node has only one neighbor node; b) determining the minimal cost of each node by performing the value iteration over the geometric graph after trimming; c) starting with the initial node, selecting a set of nodes according to the geometric graph after trimming. This embodiment is based on realization that the best geometric path does not contain any leaf node, and thus performing value iteration over the geometric graph after trimming gives the same minimal cost of all non-leaf nodes. This embodiment can significantly reduce computation load of determining the minimal cost of the node, and the best geometric path. A set of waypoints can be extracted from the set of nodes defining the best geometric graph.” The system determines a representative position along a virtual trajectory based on cost-based weighting through iterative evaluation, corresponding to setting a local target based on weighting of nodes along the virtual trajectory.).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the invention of Mochida with the teachings of Wang such that the vehicle system of Mochida is further configured to utilize virtual trajectory generation circuitry generating a plurality of virtual trajectories passing through a plurality of target states, evaluating the plurality of virtual trajectories based on a dynamics limitation of the moving body, target state candidate calculation circuitry calculating the plurality of target states reachable along a virtual trajectory within the limitation as the plurality of target state candidates, and performing weighting on a virtual trajectory reaching the plurality of target state candidates calculated in the target state candidate calculation circuitry in in the plurality of virtual trajectories, and sets a state where a weighted average of an optional position on the virtual trajectory and a weight is obtained to the local target state, as taught by Wang (See Col. 12 lines 50-65, Col. 13 lines 1-45, Col. 14 lines 25-45.), with a reasonable expectation of success. The motivation for doing so would be predicting safe paths to avoid obstacles as well as optimizing vehicle operation criteria, as taught by Wang (See Col. 1 lines 1-20.).
Claim(s) 6 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mochida (US 20190300054 A1) in view of Jin (US 20190311616 A1).
Regarding Claim 6, Mochida teaches The passage point generation apparatus according to claim 5, as set for in the anticipation rejection above. Mochida does not explicitly disclose, however, Jin, in the same field of endeavor, teaches wherein each of the plurality of target state candidates is a target state for the moving body to pass through a gate of a tollgate, and the global target state includes at least a state amount of a position to which the moving body proceeds after the moving body passes through the gate of the tollgate (See at least paragraph [0181], “710—Pre-Routing Services for Different Toll Method in Toll Plaza: CAVH vehicles with different toll-devices or toll-plan are pre-routed to a different lane/path before they reach a toll-gate to avoid congestion in a toll plaza” and paragraph [0182], “711—Pre-Routing Services for Different Exit Direction in Departure Stage: CAVH vehicles are pre-routed to a different lane/path to get a smooth access to a specific exit ramp/link according to their destination and preference.”).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the invention of Mochida with the teachings of Jin such that the vehicle system of Mochida is further configured to utilize each of the plurality of target state candidates is a target state for the moving body to pass through a gate of a tollgate, and the global target state includes at least a state amount of a position to which the moving body proceeds after the moving body passes through the gate of the tollgate, as taught by Jin (See Paragraph [0181], [0182].), with a reasonable expectation of success. The motivation for doing so would be providing control and guidance signals to vehicles to execute autonomous driving through different road segments and nodes, as taught by Jin (See Paragraph [0003].).
Regarding Claim 13, Mochida teaches The passage point generation apparatus according to claim 1, as set for in the anticipation rejection above. Mochida does not explicitly disclose, however, Jin, in the same field of endeavor, teaches wherein the passage point generation apparatus is mounted on a control apparatus admissive- controlling the moving body by communication with the moving body, and the local target state generation circuitry calculates the local target state so that the moving body can reach any of the target state candidates in consideration of communication delay of admissive control (See at least paragraph [0165]-[0168], “610—Communication from RSU to OBU or other device: data flow including CAVH control/guidance signals from RSU to OBU; 611—Communication between RSUs: data flow including control/guidance signals from one RSU to other RSUs; 612—Communication from OBU to RSU: data flow including control/guidance signals from OBU to RSU; 613—Communication between TCU/TCC/CAVH Cloud and RSU: data flow including control/guidance signals from TCU/TCC/CAVH Cloud to RSU and necessary data from RSU to TCU” and paragraph [0185], “714—CAVH V2I Link in Lower Deck/Tunnel: CAVH V2I link in this area is not guaranteed. Detection may be unavailable in some segments and V2I communication may have high packet-loss/delay.” The system generates guidance or control information for the moving body via communication and accounts for communication delay when determining the local target state.).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the invention of Mochida with the teachings of Jin such that the vehicle system of Mochida is further configured to utilize a mounted control apparatus admissive- controlling the moving body by communication with the moving body, and the local target state generation circuitry calculates the local target state so that the moving body can reach any of the target state candidates in consideration of communication delay of admissive control., as taught by Jin (See Paragraph [0165]-[0168], [0185].), with a reasonable expectation of success. The motivation for doing so would be providing control and guidance signals to vehicles to execute autonomous driving through different road segments and nodes, as taught by Jin (See Paragraph [0003].).
Conclusion
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/JEWEL A KUNTZ/Examiner, Art Unit 3666
/ANNE MARIE ANTONUCCI/Supervisory Patent Examiner, Art Unit 3666