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 .
Status of Claims
This action is in reply to the patent application filed on March 3, 2025.
Claims 1-14 are currently pending and have been examined.
This action is made Non-FINAL.
The examiner would like to note that this application is being handled by examiner Christine Huynh.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on March 3, 2025, August 6, 2026. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
The numbering of claims is not in accordance with 37 CFR 1.126 which requires the original numbering of the claims to be preserved throughout the prosecution. When claims are canceled, the remaining claims must not be renumbered. When new claims are presented, they must be numbered consecutively beginning with the number next following the highest numbered claims previously presented (whether entered or not). Correction is required.
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.
Claim 1-14 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
Claim 1 is directed to a trajectory planning method (i.e., a process). Claim is directed towards a trajectory planning apparatus. Therefore, claims 1 and 12 are within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. Claim 1 recites:
(Currently amended) A trajectory planning method, comprising:
acquiring a reference trajectory of a predetermined planning interval on the basis of vehicle information, environment information and end point information;
establishing a vehicle kinematic model in a road coordinate system on the basis of the vehicle information and the reference trajectory; and
using a model predictive controller to determine a sequence of control quantities in a predetermined planning interval according to the reference trajectory, the vehicle information and the vehicle kinematic model, and obtaining a final trajectory on the basis of the sequence of control quantities.
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, “determine a sequence of control quantities…” in the context of this claim encompasses a person (driver) looking at data collected such as the reference trajectory, the vehicle information, and the vehicle kinematic model, and forming a simple judgement based on the data collected. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract idea into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
(Currently amended) A trajectory planning method, comprising:
acquiring a reference trajectory of a predetermined planning interval on the basis of vehicle information, environment information and end point information;
establishing a vehicle kinematic model in a road coordinate system on the basis of the vehicle information and the reference trajectory; and
using a model predictive controller to determine a sequence of control quantities in a predetermined planning interval according to the reference trajectory, the vehicle information and the vehicle kinematic model, and obtaining a final trajectory on the basis of the sequence of control quantities.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of “acquiring a reference trajectory …”, “establishing a vehicle kinematic model…”, and “obtaining a final trajectory…”, the examiner submits that these limitations are insignificant extra-solution activities that merely use a computer (vehicle controller) to perform the process. In particular, the acquiring steps acquire information such as vehicle information, environment information, and end point information from the sensors and from the external source are recited at a high level of generality (i.e. as a general means of gathering vehicle and road condition data for use in the evaluating step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. The obtaining a final trajectory step is also recited at a high level of generality (i.e. as a general means of a model is formed using the collected vehicle information and the reference trajectory), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. Lastly, the “model predictive controller” is a model recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of ranking information based on a determined amount of use) such that it amounts no more than mere instructions to apply the exception using a generic computer component.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use 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 not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the Revised Guidance, representative 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 claim does 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 element of using a vehicle controller to perform the establishing a vehicle kinematic model and obtaining a final trajectory… amounts to nothing more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of “acquiring a reference trajectory …”, “establishing a vehicle kinematic model…”, and “obtaining a final trajectory…”, the examiner submits that these limitations are insignificant extra-solution activities. Hence, the claim is not patent eligible.
Dependent claim(s) 2-11 and 13-14 do not recite any further limitations that cause the claims to be directed towards statutory subject matter. The claims merely recite: “determine a sequence of control quantities…”. Each of the further limitations expound upon the “determine a sequence of control quantities…”and do not recite additional elements integrating the “determine a sequence of control quantities…” into a practical application or additional elements that are not well-understood, routine or conventional. Therefore, dependent claims 2-11 and 13-14 are similarly rejected as being directed towards non-statutory subject matter.
Therefore, claim(s) 1-14 is/are ineligible under 35 USC §101.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1 and 11-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dangel et al. (US 20240300541 A1) in view of Liang et al. “A Novel Combined Decision and Control Scheme for Autonomous Vehicle in Structured Road Based on Adaptive Model Predictive Control” (from the IDS), which was provided in the IDS sent on March 3, 2025.
Regarding claims 1 and 11-14:
With respect to claims and 12, Dangel teaches:
acquiring a reference trajectory of a predetermined planning interval on the basis of vehicle information, environment information and end point information; (“The resampling step may notably comprise interpolating the transformed trajectory outputs using the global vehicle model, so as to compute trajectory points between trajectory points as directly obtained from the transformed trajectory outputs.” [0026], “The coarse optimization (corresponding to blocks with reference numerals 1 to 6 in FIG. 1) provides an initial solution in the area of a local minimum. During the second part (block with reference numeral 7 in FIG. 1), an efficient, nonlinear programming (NLP) algorithm solves for the optimal trajectory of an accurate vehicle model through the convex space-time objects obtained thanks to the most suitable corridor.” [0048], “The computer system used to implement the present methods may be assumed to be provided with a global model of the vehicle to be controlled. The global model may for instance include at least two sub-models for the vehicle, including one sub-model for low velocities and a different sub-model for high velocities, as assumed in the following for illustration purposes.” [0058]), where a global vehicle model trajectory is acquired using vehicle and environmental information.
establishing a vehicle kinematic model in a road coordinate system on the basis of the vehicle information and the reference trajectory; (“The model used at block 7 may notably be a velocity-dependent blend of two or more vehicle models. The terminology “model” refers to a set of data defining a vehicle and its behavior. Several known models can be relied on, such as the so-called bicycle model and the Pacejka tire model, and, for low speeds, the “kinematic model”.” [0048-0049], “At low velocities, the vehicle model used may for example be a simpler kinematic model with four states only (x and y coordinates, velocity and heading) and no tire dynamics.” [0053], FIG. 1, reference number 7), where a vehicle kinematic model in a road coordinate system is established.
Dangel does not teach but Liang teaches:
using a model predictive controller to determine a sequence of control quantities in a predetermined planning interval according to the reference trajectory, the vehicle information and the vehicle kinematic model, and obtaining a final trajectory on the basis of the sequence of control quantities: (“By a subtle design of slack variables and scenario adaptive constraints in MPC scheme, the decision ability can be integrated in the longitudinal controller, which means the longitudinal MPC can not only calculate the desired acceleration but also adaptively make behavior decisions according to driving conditions; (2). A weight adaptive path following MPC is designed to track the global path and conduct the lateral local motion commands made by the longitudinal controller, owing to the weight adaptive mechanism, both the path tracking performance and lane change smoothness can be satisfied while the local path planning for lane change can be skipped; (3) By the proposed longitudinal and lateral adaptive MPC, a combined decision and control scheme for lane change in structured road is constituted, generally speaking, the longitudinal controller can decide “if” and “when” to conduct or cancel the lane change maneuver, and the lateral MPC can deal with “how” to conduct the lane change maneuver;” (Section I, para. 6)), where a model predictive controller can be used to determine control qualities according to driving conditions, and obtaining a trajectory.
It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to have combined Dangel’s trajectory planning with Liang’s model predictive controller because (“MPC is supposed to be the most promising method owing to its ability to systematically deal with multiple constraints and vehicle dynamics [32]. Recent years, strenuous efforts [33], [34] are made on MPC from theory and application. In vehicle dynamics, except for well-known applications like stability control for vehicle driven by human and tracking control for autonomous vehicle, the application of MPC has also been applied to Driver-automation shared control [35]–[37].” (Section I, para. 3)).
With respect to claim 11, Dangel in combination with Liang, as shown in the rejection above, discloses the limitations of claim 1. The combination of Dangel and Liang teaches trajectory planning of claim 1. Dangel further teaches, wherein acquiring a reference trajectory of a predetermined planning interval on the basis of vehicle information, environment information and end point information, comprises:
performing global trajectory planning on the basis of the vehicle information and the end point information, to obtain a global trajectory from a start point to an end point; (“ The computer system used to implement the present methods may be assumed to be provided with a global model of the vehicle to be controlled. The global model may for instance include at least two sub-models for the vehicle, including one sub-model for low velocities and a different sub-model for high velocities, as assumed in the following for illustration purposes. As noted earlier, each sub-model of the vehicle comprises data relating to the vehicle. The global model may furthermore include additional parameters, here called model parameters (captured as model parameter data), pertaining, e.g., to a class of vehicles and/or a physical property, such as steering capacity or the mass of the vehicle.” [0058], “The block with reference numeral 1 (optional) is related to the prediction of vehicle states. Here, current measurements, current states 101 of the vehicle, and driving reference information 102, are used to estimate further vehicle states 11 as output. The predicted states 101 include vehicle-related information, such as position, velocity, current acceleration, steering direction, etc… This information 102 further includes roadway information (the local geometry of the route), e.g., a sequence of waypoint defining the lane (and, therefore, the road) boundaries.” [0062]), where global trajectory planning is performed based on vehicle and environmental information.
judging whether a collision will occur on the basis of the environment information and the global trajectory; (“The block with reference numeral 2 (optional) is related to the prediction of future obstacles positions. Here, information about dynamic obstacles 103, especially positions, are used to generate a prediction of future positions of the obstacles. Obstacles predictions 21 are based on the analysis of moving or standing obstacles… More generally, obstacle predictions can involve acceleration and steering predictions. The obstacles may for instance be pedestrians, bicycles, cars, etc. Obstacles prediction is known per se.” [0063]), where future positions of the obstacles are predicted, which predicting obstacle information relative to the vehicle correlates to the possibility of a collision occurring.
Dangel does not teach, but Liang teaches:
if a collision will occur, then performing local trajectory planning to obtain the reference trajectory; (“The local path planning framework based on the proposed scenario adaptive MPC decides the longitudinal acceleration and the motion behavior, simultaneously. A combined scheme is proposed to deal with this problem. When no obstacle ahead is detected in the current lane, the longitudinal controller only needs to keep the vehicle at its desired velocity. If the obstacle is detected in the current lane (either a static obstacle or a moving vehicle), the relative velocity will be checked. When the relative velocity is negative and the smooth distance (defined as a slack variable of the feasible zone in the scenario adaptive MPC) becomes larger than a predefined threshold, the lane change necessity and feasibility will be checked. If the lane change order is made, it is directly delivered to the path tracking controller.” (Section II, para. 1), FIG. 1), where local motion planning can be obtained when an obstacle ahead could lead to a collision.
if no collision will occur, then acquiring the reference trajectory on the basis of the global trajectory; (“The local path planning framework based on the proposed scenario adaptive MPC decides the longitudinal acceleration and the motion behavior, simultaneously. A combined scheme is proposed to deal with this problem. When no obstacle ahead is detected in the current lane, the longitudinal controller only needs to keep the vehicle at its desired velocity.” (Section II, para. 1), FIG. 1), where there is no obstacle detected then the vehicle state is kept the same.
It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to have combined Dangel’s trajectory planning with Liang’s model predictive controller because (“MPC is supposed to be the most promising method owing to its ability to systematically deal with multiple constraints and vehicle dynamics [32]. Recent years, strenuous efforts [33], [34] are made on MPC from theory and application. In vehicle dynamics, except for well-known applications like stability control for vehicle driven by human and tracking control for autonomous vehicle, the application of MPC has also been applied to Driver-automation shared control [35]–[37].” (Section I, para. 3)).
With respect to claim 13, Dangel in combination with Liang, as shown in the rejection above, discloses the limitations of claim 1. The combination of Dangel and Liang teaches trajectory planning of claim 1. Dangel further teaches:
wherein the electronic device comprises a processor and a memory, and at least one instruction or at least one program is stored in the memory, the at least one instruction or the at least one program being loaded by the processor and executing the method as claimed in claim 1; (“The system includes a computerized unit 202, which has one or more processors 230, as well as a control unit 360, which is connected to the computerized unit 202. The system further comprises a memory 250 storing a vehicle model and a software program for executing a method as described above. The computerized unit 202 is notably configured to obtain information describing a roadway 301 and run the software program. To that aim, the software program is typically loaded in the main memory of the unit 202 and, once loaded, executed by the one or more processors. This way, the vehicle control unit 360 can control the vehicle thanks to signals obtained from trajectories optimized upon execution of the present methods by the processors.” [0110]), where the system consists of a processor and a memory, and instruction stored in the memory that executes the method.
With respect to claim 14, Dangel in combination with Liang, as shown in the rejection above, discloses the limitations of claim 1. The combination of Dangel and Liang teaches trajectory planning of claim 1. Dangel further teaches:
A non-transitory computer storage medium, wherein the computer storage medium stores an instruction for execution by a computing device, and when the computing device executes the instruction, the method as claimed in claim 1 is performed; (“the invention can be embodied as a computer program product for controlling a speed of a vehicle. Basically, the computer program product comprises a computer readable storage medium having program instructions embodied therewith, where the program instructions executable by a plurality of processing means to cause the latter to take steps according to the present methods.” [0114]), where the computer storage medium stores an instruction for execution by a computing device.
Allowable Subject Matter
Claims 2-10 are rejected under 35 U.S.C. 101, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims and rewritten to overcome the 35 U.S.C. 101 rejection.
The following is a statement of reasons for the indication of allowable subject matter: None of the prior art of record references taken either together or in combination with the prior art of record disclose a method, or system including the further instructions:
(Regarding claim 2) wherein using a model predictive controller to determine a sequence of control quantities in a predetermined planning interval according to the reference trajectory, the vehicle information and the vehicle kinematic model, and obtaining a final trajectory on the basis of the sequence of control quantities, comprises: linearizing the vehicle kinematic model, to obtain a time domain linearized vehicle model and a space domain linearized vehicle model; wherein the model predictive controller comprises a longitudinal control model and a transverse control model, designs a cost function of the longitudinal control model and a cost function of the transverse control model, and determines a sequence of control quantities of a predetermined planning interval on the basis of the cost function of the longitudinal control model, the cost function of the transverse control model, the time domain linearized vehicle model and the space domain linearized vehicle model; and acquiring a final trajectory on the basis of the sequence of control quantities.
in combination with the remaining elements and features of the claimed invention. It is for these reasons that the applicants’ invention defines over the prior art of record.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Cao et al. (US 12172637 B2), is pertinent because (“According to the first aspect or the first possible implementation of the first aspect, in a second possible implementation of the moving track prediction method, generating the one or more destination states based on the initial state and a motion model includes establishing one or more Frenet coordinate systems based on the one or more preset paths, and generating the one or more destination states respectively in the one or more Frenet coordinate systems based on the initial state of the target and the motion model. The Frenet coordinate system is established based on the preset path associated with the target, helping to apply the motion model to the preset path associated with the target, for calculation.” (8)), which pertains to establishing a vehicle kinematic model in a road coordinate system on the basis of the vehicle information and the reference trajectory.
WUTHISHUWONG et al. (US 20200341476 A1), is pertinent because (“The system 31 further comprises a trajectory control module 45 which outputs control parameters for the movement of the vehicle to a vehicle motion control 51 being in communication with the system 31 for estimating the trajectory of the host vehicle 11. The output of the trajectory control module 45 which is also the output of the entire system 31 comprises parameters for the steering of the host vehicle 11, e.g. steering angle or steering torque.” [0048]), which pertains to obtaining a final trajectory on the basis of the sequence of control quantities.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Christine N Huynh whose telephone number is (571)272-9980. The examiner can normally be reached Monday - Friday 8 am - 4 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Aniss Chad can be reached at (571)270-3832. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHRISTINE NGUYEN HUYNH/Examiner, Art Unit 3662
/ANISS CHAD/Supervisory Patent Examiner, Art Unit 3662
