DETAILED ACTION
This Office Action is in response to Applicant’s Amendment and Remarks filed on 02/03/2026.
Claims 1-20 received on 02/03/2026 are considered in this Office Action.
Claims 1-20 are pending for examination.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Claims 8 and 11 were previously rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. In response to the Applicant’s amendment to claim 8, the rejection has been withdrawn.
Applicant's arguments regarding claims 1-10 and 12-20 are rejected under 35 U.S.C. 101 have been fully considered but they are not persuasive.
In the Remarks, Applicant argues that
none of the claims recite an abstract idea as the amended limitations recite a specific conditional iterative process that dynamically determines whether to continue releasing strategy spaces based on computational results, and cannot be practically performed in the human mind (Remarks pg 8),
conditional iterative release process integrates into a practical application (Remarks pg 9), and
specific trigger condition of a “null” feasible region causing a “second release” is not “well-understood, routine, conventional activity” Thus include an inventive concept.
Examiner respectfully disagrees.
Regarding (a), the basis of the argument comes from the Applicant’s allegation that performing the claimed limitations of performing one of the plurality of times of release, determining a strategy feasible region, determining whether the strategy feasible region is not null, ending the plurality of times of release and performing a second one of the plurality of times of release cannot be performed in the human mind within the time constraints of an actual driving scenario. However, claims 1, 14 and 20 as amended do not require “time constraints of an actual driving scenario” as Applicant alleges. Furthermore, the claimed limitations of performing one of the plurality of times of release, determining a strategy feasible region, determining whether the strategy feasible region is not null, ending the plurality of times of release and performing a second one of the plurality of times of release are directed to an abstract idea as they constitute a “mental process”, as the claims cover performance of the limitations in the human mind, given the broadest reasonable interpretation. The steps of “obtaining …”, “performing a plurality of times of release of the plurality of strategy spaces”, “determining a strategy feasible and traveling decision-making result”, “determining whether the strategy feasible region is not null”, “ending the plurality of times of release” and “performing a second one of the plurality of times of release” are equivalent to a mental process of judgement based on observation, such as a person identifying an obstacle, predicting its longitudinal trajectory and vehicle’s longitudinal trajectory, determining whether a change in longitudinal maneuver will result in a collision avoidance, and, in response to determining that a longitudinal maneuver is unable to avoid collision, determine an additional lateral movement to avoid collision. These steps are performed in a human mind when a braking distance is not sufficient, hence an evasive steering is necessary to avoid collision, and performed within a time constraint.
Regarding (b), the conditional iterative release process is directed to an abstract idea as stated above. In Step 2A Prong Two, evaluation of whether the claim recites additional elements that integrate the exception into a practical application of the exception is performed. Integration into practical application requires an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. Additional elements, such as processor and memory, do not integrate the judicial exception into a practical application, as mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A..
The Examiner recommends adding elements of “determining decision-making solution based on conditional iterative release process” and additional elements “performing the decision-making solution” in order integrate the exception into a practical application to as supported by para. [0077] of the specification reproduced below:
[0077]: A subject for implementing the intelligent driving decision-making solution in this embodiment of this application may be an intelligent agent that is powered and is capable of moving autonomously. The intelligent agent may perform game decision-making with another object in a traffic scenario based on the intelligent driving decision-making solution provided in an embodiment of this application, to generate a semantic-level decision-making label and an expected traveling trajectory of the intelligent agent, so that the intelligent agent may perform proper lateral and longitudinal motion planning.
Regarding (c), the basis of the argument comes from the Applicant’s allegation that the “specific trigger condition of a “null” feasible region causing a “second release” is not well-understood, routine, conventional activity, thus amounts to significantly more. However, Ersal (US20200406969A1) teaches specific trigger condition of a “null” feasible region (FIG. 13 1328; para. [0240]: “At 1328, if the process 1300 determined that the object can be avoided without a lane change maneuver (“YES” at 1328) […] If the process 1300 determined that the object cannot be avoided without a lane change maneuver (“NO” at 1328, wherein cannot be avoided indicates “null” feasible region) causing a second release (FIG. 13 1328 NO [Wingdings font/0xE0] 1336[Wingdings font/0xE0] 1348; para. [0240]: “If the process 1300 determined that the object cannot be avoided without a lane change maneuver (“NO” at 1328), the process 1300 can proceed to 1336.”; para. [0242]: “At 1336, the process 1300 can determine a sequence of control inputs to avoid a collision between the ego vehicle and the object. The sequence of control inputs can be used to maneuver the ego vehicle to an adjacent lane.”). Performing a first set of analysis and then conducting a second set of analysis in response to determining an unsuccessful first set of analysis is not an inventive concept.
Furthermore, mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Therefore, the rejection is maintained.
Applicant’s arguments with respect to claim(s) 1, 14 and 20 rejected under 35 USC § 103 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-10 and 12-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis: Step 1
Claims 1-13 are directed to a method.
Claim 14-20 are directed to an apparatus, i.e. a machine.
Therefore, claims 1-20 fall into at least one of the four statutory categories.
101 Analysis: Step 2A, Prong I (MPEP § 2106.04)
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 14 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 14 recites:
14. An apparatus for intelligent driving decision-making, comprising:
at least one processor; and
one or more memories coupled to the at least one processor and storing programming instructions for execution by the at least one processor to perform the following operations:
obtaining a game object of an ego vehicle; and
from a plurality of strategy spaces of both the ego vehicle and the game object, performing a plurality of times of release of the plurality of strategy spaces;
after performing one of the plurality of times of release, determining a strategy feasible region of both the ego vehicle and the game object based on each released strategy space;
determining, when the strategy feasible region is not null, a traveling decision-making result of the ego vehicle based on the strategy feasible region, and ending the plurality of times of release; and
performing a second one of the plurality of times of release when the strategy feasible region determined after performing the one of the plurality of times of release is null.
The examiner submits that the foregoing bolded claim limitations constitute a “mental process”, as the claims cover performance of the limitations in the human mind, given the broadest reasonable interpretation. The steps of “obtaining …”, “performing a plurality of times of release of the plurality of strategy spaces”, “determining a strategy feasible and traveling decision-making result”, “determining whether the strategy feasible region is not null”, “ending the plurality of times of release” and “performing a second one of the plurality of times of release” are equivalent to a mental process of judgement based on observation, such as a person identifying an obstacle, predicting its longitudinal trajectory and vehicle’s longitudinal trajectory, determining whether a change in longitudinal maneuver will result in a collision avoidance, and, in response to determining that a longitudinal maneuver is unable to avoid collision, determine an additional lateral movement to avoid collision. These steps are performed in a human mind when a braking distance is not sufficient, hence an evasive steering is necessary to avoid collision.
Accordingly, claims 1-20 recite at least one abstract idea.
101 Analysis: Step 2A, Prong II (MPEP § 2106.04)
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 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”):
14. An apparatus for intelligent driving decision-making, comprising:
at least one processor; and
one or more memories coupled to the at least one processor and storing programming instructions for execution by the at least one processor to perform the following operations:
obtaining a game object of an ego vehicle; and
from a plurality of strategy spaces of both the ego vehicle and the game object, performing a plurality of times of release of the plurality of strategy spaces;
after performing one of the plurality of times of release, determining a strategy feasible region of both the ego vehicle and the game object based on each released strategy space;
determining, when the strategy feasible region is not null, a traveling decision-making result of the ego vehicle based on the strategy feasible region, and ending the plurality of times of release; and
performing a second one of the plurality of times of release when the strategy feasible region determined after performing the one of the plurality of times of release is null.
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.
The additional limitations which recite the processor, memory and their connection are recited at a high level of generality. Furthermore, the processor merely automates the claimed functions of obtaining, performing and determining, thus simply being an attempt to generally link additional elements to a technological environment.
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.
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 (MPEP § 2106.05)
Step 2B of the Revised Guidance analyzes the claims to determine if the claims recite additional limitations that amount to significantly more than the judicial exception.
When considered individually or in combination, the additional limitations of claim 1 do not amount to significantly more than the judicial exception for the same reasons discussed above as to why the additional limitations do not integrate the abstract idea into a practical application. The additional element of using a generic computer to perform the claimed steps of obtaining, performing and determining amounts to nothing more than applying the exception using a generic component. Generally applying an exception using a generic computer component cannot provide an inventive concept.
Dependent claims 2-3, 6, 8, 15-16 and 19 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception that do not integrate the judicial exception into a practical application, similar to the representation claim 1 shown above.
Dependent claims 4-5, 12 and 18 constitute a “mental process”, as the claims cover performance of the limitations in the human mind, given the broadest reasonable interpretation. The steps of “determining…” and “determining total cost value” is equivalent to a mental process of judgement based on observation.
Dependent claims 7, 9-10 constitute a “mental process”, as the claims cover performance of the limitations in the human mind, given the broadest reasonable interpretation. The steps of “obtaining …” and “constraining…” is equivalent to a mental process of judgement based on observation
Regarding dependent claim 13, it recites an additional limitation “displaying” which is directed to a form of insignificant extra-solution activity, specifically insignificant post-solution displaying, that merely use a “display” to perform the process. The Examiner failed to find support from claim and specification that indicates the claimed limitation of “displaying” reflecting an improvement in technology.
In contrast to claim 1 which generally recites “determining a traveling decision-making result”, dependent claim 11 recites “a conservative traveling decision of the ego vehicle is performed”, thus applies or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, thus integrating the judicial exception into a practical application.
Therefore, claims 1-10 and 12-20 recite abstract ideas with additional elements rendered at a high level of generality resulting in claims that do not integrate the abstract idea into a practical application or amount to significantly more than the judicial exception, thus are directed toward non-statutory subject matter and are rejected under 35 U.S.C. 101.
The Examiner recommends adding elements of “determining decision-making solution based on conditional iterative release process” and additional elements “performing the decision-making solution” in order integrate the exception into a practical application to as supported by para. [0077] of the specification reproduced below:
[0077]: A subject for implementing the intelligent driving decision-making solution in this embodiment of this application may be an intelligent agent that is powered and is capable of moving autonomously. The intelligent agent may perform game decision-making with another object in a traffic scenario based on the intelligent driving decision-making solution provided in an embodiment of this application, to generate a semantic-level decision-making label and an expected traveling trajectory of the intelligent agent, so that the intelligent agent may perform proper lateral and longitudinal motion planning.
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 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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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.
Claims 1-5, 7-12, 14-18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Caldwell (US 20210046924 A1), in view of Kobilarov (US 20220402485 A1), and further in view of Ersal (US20200406969A1).
Regarding claim 1, Caldwell teaches a method for intelligent driving decision-making performed by an ego vehicle (Abstract: “techniques to determine an action for a vehicle”), comprising:
obtaining a game object of an ego vehicle (FIGs. 1-2; para. [0044]: “detect one or more dynamic objects 104 (e.g., objects 104) in the environment 100, such as via a perception system”; para. [0054]: “An object 104 may be relevant to the vehicle 102 if the object 104 and the vehicle 102 could potentially occupy the same space or come within a threshold distance of one another over a period of time (e.g., potential for a collision).”; FIG. 8 800: “Detect an object”, wherein objects relevant to the vehicle is an example corresponds to a game object);
from a plurality of strategy spaces of (para. [0046]: “vehicle computing system may determine one or more actions 110 for the vehicle 102 operating in the environment with the detected objects 104. The action(s) 110 may represent one or more potential paths the vehicle 102 could take through the environment 100 (e.g., one or more vehicle trajectories)”; FIG. 8 804: “Determine an action that a vehicle may take”) and the game object (para. [0051]: “the vehicle computing system may determine one or more predicted object trajectories 108 (trajectories 108) based on the action(s)”; FIG. 8 806: “Determine an object trajectory”), performing a plurality of times of release of the plurality of strategy spaces (para. [0053]: “For each vehicle action 110, such as actions 110(1), 110(2), 110(3), 110(4), and 110(5), the vehicle computing system may simulate future states (e.g., estimated states) by projecting the vehicle and object(s) forward in the environment for a period of time (e.g., 5 seconds, 8 seconds, 12 seconds, etc.). The vehicle computing system may project the object(s) (e.g., estimate future positions of the object(s) 104) forward based on the one or more predicted trajectories associated with a respective action 110.”; para. [0055]-[0056]: “the vehicle computing system may determine a cost associated with each estimated state, such as based on the estimated positions of the vehicle 102 and the object 104 relative to one another […] The one or more factors may include safety of the vehicle 102 and/or object 104 (e.g., avoiding a collision between the vehicle 102 and the object 104) […] The safety of the vehicle 102 and/or object 104 may include a likelihood of collision […] The likelihood of collision may be calculated based on a distance between the vehicle 102 and the object 104 (e.g., within 5 feet, 2 meters, 0.5 meters, etc.), converging trajectories (e.g., trajectory 108 of the object 104 that will substantially intersect a vehicle trajectory associated with an action 110”; FIG. 8 808; para. [0155]: “At operation 808, the process may include determining a cost associated with the action based at least in part on the object trajectory”, wherein various simulation will be performed based on the trajectories/actions of the vehicle and object); and
after performing one of the plurality of times of release (FIG. 2; FIG. 8 808; FIG. 9 908: “Determine a safety cost”), determining a strategy feasible region of both the ego vehicle and the game object based on each released strategy space (FIG. 9 908-914: “Safety cost above a threshold [Wingdings font/0xE0] Include the action in vehicle planning considerations”; FIG. 8 810: “Compare the cost”; para. [0158]: “At operation 810, the process may include comparing the cost associated with the action to costs associated with other actions the vehicle may take”, wherein vehicle planning consideration corresponds to strategy feasible region of both the ego vehicle and the game object based on each released strategy space), and
determining, when the strategy feasible region is not null (FIG. 9 908-914: “Safety cost above a threshold [Wingdings font/0xE0] Include the action in vehicle planning considerations”, wherein safety cost above a threshold indicates when the strategy feasible region is not null), a traveling decision-making result of the ego vehicle based on the strategy feasible region, and ending the plurality of times of release (FIG. 8 814; para. [0160]: “Based on a determination the cost is the lowest cost action (“Yes” at operation 812), the process, at operation 814, the process may include causing the vehicle to be controlled based at least in part on the action. In various examples, causing the vehicle to be controlled based on the action may include causing the vehicle to travel along the one or more trajectories associated with the action”, wherein causing the vehicle to be controlled based on the action indicates a traveling decision-making result and ending the plurality of times of release), but fails to specifically teach a plurality of strategy spaces of the game object, and performing a second one of the plurality of times of release when the strategy feasible region determined after performing the one of the plurality of times of release is null.
However, in the same field of endeavor, Kobilarov teaches from a plurality of strategy spaces of both the ego vehicle and the game object (FIG. 1; para. [0027]: “As shown in FIG. 1, the object 110 is associated with object trajectories 116(1) and 116(2), the object 112 is associated with object trajectories 118(1) and 118(2), the object 114 is associated with an object trajectory 120, and the vehicle 102 is associated with the vehicle trajectories 122(1) and 122(2) determined by the vehicle computing device (e.g., using the perception component 422, the prediction component 424, or another model). In some examples, the active prediction component 104 may receive path information associated with the aforementioned object trajectories (e.g., 116(1), 116(2), 118(1), 118(2), 120, 122(1), and 122(2)) from a machine learned model. Though FIG. 1 shows one or two trajectories associated with the various objects, any number of objects may be detected and any number of object trajectories may be predicted for each object”), performing a plurality of times of release of the plurality of strategy spaces (FIG. 2; para. [0034]: “FIG. 2 is an illustration of another example environment 200, in which one or more models determine potential interactions between one or more objects and a vehicle at a future time. For instance, a computing device 202 can implement the active prediction component 104 to determine the output data 108 representing potential interactions (e.g., intersections or near-intersections (e.g., within a threshold distance)) between one or more objects (e.g., the object 110, the object 112, and/or the object 114) and the vehicle 102. In some examples, the computing device 202 may be associated with the vehicle computing device(s) 404 and/or the computing device(s) 436”).
Caldwell and Kobilarov are analogous to the claimed invention because it pertains to the planning of trajectory in response to objects. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Caldwell and incorporate the multiple trajectories of the object of Kobilarov. Doing so will enhance the safety by as a route or trajectory (e.g., a candidate trajectory) determined for the vehicle can be based at least in part on consideration of the multiple predicted trajectories of each object such that enabling a planning component to select the route or trajectory for the vehicle that is most likely to avoid the object (Kobilarov para. [0020]). Caldwell in view of Kobilarov fails to specifically teach performing a second one of the plurality of times of release when the strategy feasible region determined after performing the one of the plurality of times of release is null.
However, in the same field of endeavor, Ersal teaches after performing one of the plurality of times of release (FIG. 13 1324; para. [0239]: “At 1324, the process 1300 can determine whether or not an object located longitudinally ahead of the ego vehicle can be avoided without a lane change maneuver based on the object information, the roadway information, and the ego vehicle information”), determining a strategy feasible region of both the ego vehicle and the game object based on each released strategy space (para. [0239]: “The process 1300 can determine if the ego vehicle can stop before a potential collision with the object, which may be located in the same lane as the ego vehicle. The process 1300 can determine a stopping distance for the ego vehicle based on the velocity of the ego vehicle. The process may provide the velocity of the ego vehicle to a stopping distance model and receive a stopping distance value from the stopping distance model. The stopping distance model may include a lookup table including a plurality of stopping distances at a plurality of velocities, the plurality of stopping distances being determined using manufacturer test data. The stopping distance model may be configured to accept other input values such as a temperature value and/or a rainfall value. Temperature and the presence of rain may affect the stopping distance of the ego vehicle at a given speed, and the additional information may be used to provide a more accurate stopping distance. The stopping distance model may also be configured to output a stopping time value indicating how long it will take the ego vehicle to stop from the current ego vehicle velocity. After the stopping distance value and/or stopping time value has been determined, the process 1300 can determine if the ego vehicle will be able to stop before a potential collision with the object.), and
determining, when the strategy feasible region is not null (FIG. 13 1328; para. [0240]: “At 1328, if the process 1300 determined that the object can be avoided without a lane change maneuver (“YES” at 1328)), a traveling decision-making result of the ego vehicle based on the strategy feasible region (FIG. 13 1332; para. [0241]: “At 1332, the process 1300 can cause a vehicle control system of the ego vehicle to perform a vehicle maneuver without a lane change.”), and ending the plurality of times of release (para. [0241]: “The process 1300 may cause the vehicle control system to keep the ego vehicle traveling along the same lane and brake sufficiently to avoid a collision with the object. The process 1300 can then end.”) and performing a second one of the plurality of times of release when the strategy feasible region determined after performing the one of the plurality of times of release is null (FIG. 13 1328 NO [Wingdings font/0xE0] 1336[Wingdings font/0xE0] 1348; para. [0240]: “If the process 1300 determined that the object cannot be avoided without a lane change maneuver (“NO” at 1328), the process 1300 can proceed to 1336.”; para. [0242]: “At 1336, the process 1300 can determine a sequence of control inputs to avoid a collision between the ego vehicle and the object. The sequence of control inputs can be used to maneuver the ego vehicle to an adjacent lane.”);
Ersal is analogous to the claimed invention because it pertains to the planning of trajectory in response to objects. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Caldwell in view of Kobilarov and incorporate the teachings of Ersal, and determine whether maneuver in a first set of maneuvers is sufficient to avoid a collision prior to determining whether a maneuver in a second set of maneuvers is sufficient to avoid a collision. Doing so will determine whether there is sufficient distance to avoid collision by longitudinal maneuvers, thus enhancing the safety by preventing collision imminent steering from pushing the vehicle to its dynamic limits (Ersal, para. [0004]) and further omit additional analysis of other unnecessary maneuvers.
Regarding claim 2, Caldwell in view of Kobilarov and further in view of Ersal teaches the method according to claim 1. Caldwell further teaches wherein a dimension of the plurality of strategy spaces comprises at least one of the following: a longitudinal sampling dimension, a lateral sampling dimension, or a temporal sampling dimension (FIG. 1; FIG. 2; para. [0047]: “The action(s) 110 may additionally include one or more sub-actions, such as speed variations (e.g., maintain velocity, accelerate, decelerate, etc.), positional variations (e.g., changing a position in a lane), or the like. The action(s) 110 may additionally include one or more sub-actions, such as speed variations (e.g., maintain velocity, accelerate, decelerate, etc.), positional variations (e.g., changing a position in a lane), or the like. […] In such an example, an action may comprise a sequence of actions”, wherein positional variations and/or speed variations and/or sequence of actions indicate a longitudinal sampling dimension, a lateral sampling dimension, or a temporal sampling dimension).
Regarding claim 3, Caldwell in view of Kobilarov and further in view of Ersal teaches the method according to claim 2. Caldwell further teaches wherein the performing a plurality of times of release of the plurality of strategy spaces comprises performing a release in a sequence of the following dimensions: the longitudinal sampling dimension, the lateral sampling dimension, and the temporal sampling dimension (FIG. 1 110(1)-110(5); para. [0015]: “The actions may include one or more reference actions (e.g., one of a group of maneuvers the vehicle is configured to perform in reaction to a dynamic operating environment) such as a right lane change, a left lane change, staying in a lane, going around an obstacle (e.g., double-parked vehicle, traffic cones, etc.), or the like. The action(s) may additionally include one or more sub-actions, such as speed variations (e.g., maintain velocity, accelerate, decelerate, etc.), positional variations (e.g., changing a position in a lane), or the like. […] In such an example, an action may comprise a sequence of actions”; para. [0049]: “A first action 110(1) may include remaining at the stop sign (e.g., an initial position 112) to wait for the object 104 […] A second action 110(2) may include the maintaining a position of the vehicle 102 in the lane and accelerating from the stop sign to transit through the intersection ahead of the object 104 with the right of way”; para. [0047]: “an action 110, such as second action 110(2), may include staying in a lane (reference action) and accelerating from the initial position 112 at a first acceleration (sub-action), whereas a third action 110(3) may include staying in the lane (reference action) and accelerating from the initial position 112 at a second acceleration (sub-action). For another example, an action 110, such as action 110(4) may include accelerating from an initial position 112 (sub-action) while staying in a lane (a first reference action) for two (2) seconds, followed by a lane change left (second reference action). For yet another example, an action 110, such as action 110(5) may include accelerating at a first acceleration (sub-action) while making a lane change left (reference action) and accelerating at a second acceleration when established in the left lane”, wherein as seen in the five actions generated, the sequence of action generated is longitudinal movement [accelerating or decelerating], followed by a lateral movement [change lane] and a combination [both], which corresponds to temporal sampling, thus indicating release in a sequence of the following dimensions: the longitudinal sampling dimension, the lateral sampling dimension, and the temporal sampling dimension).
Regarding claim 4, Caldwell in view of Kobilarov and further in view of Ersal teaches the method according to claim 1. Caldwell further teaches wherein when the strategy feasible region of both the ego vehicle and the game object is determined (FIG. 8 812: “Lowest Cost?”), a total cost value of a behavior-action pair (FIG. 808: “Cost associated with the action based at least in part on the object trajectory”, wherein action based on object trajectory indicates behavior-action pair) in the strategy feasible region is determined based on one or more of the following: a safety cost value, a right-of-way cost value, a lateral offset cost value, a passability cost value, a comfort cost value, an inter-frame association cost value, and a risk area cost value of the ego vehicle or the game object (FIG. 2; para. [0170]: “Based on a determination that the safety cost is not above the threshold (“No” at operation 908), the process, at operation 912, may include determining a total cost associated with the action based on one or more factors. As discussed above, the factor(s) may include the safety factor, a comfort factor, a progress factor, and/or operational rules factor associated with the vehicle and/or the object. The total cost may include a total cost of individual factors (e.g., safety cost, object progress cost, etc.) and/or a total cost of the action including each of the factor(s)”).
Regarding claim 5, Caldwell in view of Kobilarov and further in view of Ersal teaches the method according to claim 4. Caldwell further teaches wherein when the total cost value of the behavior-action pair is determined based on two or more cost values, each of the two or more cost values has a different weight (para. [0070]: “In some examples, the factor(s) may be ranked in order of importance. In such examples, at least one of the factor(s) may include a cost that is weighed higher than other factors. As discussed above, the safety cost may be weighted higher than other factors.”, wherein ranked in order of importance indicates a different weight).
Regarding claim 7, Caldwell in view of Kobilarov and further in view of Ersal teaches the method according to claim 1. Caldwell further teaches further comprising: obtaining a non-game object of the ego vehicle (FIG. 1; para. [0053]: “In various examples, the vehicle computing system may be configured to identify one or more objects 104, such as 104(4), that are irrelevant to the vehicle 102. An object 104 may be relevant to the vehicle 102 if the object 104 and the vehicle 102 could potentially occupy the same space or come within a threshold distance of one another over a period of time (e.g., potential for a collision).”);
determining a strategy feasible region of both the ego vehicle and the non-game object (para. [0054]: “an object may be determined to be irrelevant to the vehicle based on a determination that the trajectory 108 associated with the object 104, such as trajectory 108(4) associated with object 104(4), will not intersect and/or converge on a vehicle trajectory associated with an action 110. For example, the trajectory 108(4) associated with object 104(4) includes a turn away from the vehicle 102 on a road substantially perpendicular to the vehicle 102 direction of travel”, wherein all actions of 110(1)-(5) will not interfere with the non-game object, thus the actions indicate determining a strategy feasible region); and
determining the traveling decision-making result of the ego vehicle based on at least the strategy feasible region of both the ego vehicle and the non-game object (para. [0054]: “Based on a determination that an object 104 is irrelevant to the vehicle 102, the object 104 may be disregarded in estimated states associated with an action 110. For example, the vehicle computing system may determine that object 104(4) is irrelevant to the vehicle 102 and may not include the trajectory 108(4) associated with the object 104(4) in the estimated states.”, wherein “not include the trajectory 108(4) associated with the object 104(4)” indicates based on at least the strategy feasible region of both the ego vehicle and the non-game object).
Regarding claim 8, Caldwell in view of Kobilarov and further in view of Ersal teaches the method according to claim 7. Caldwell further teaches wherein: a strategy feasible region of the traveling decision-making result of the ego vehicle is determined based on an intersection of each strategy feasible region of both the ego vehicle and a respective game object or a strategy feasible region of the traveling decision-making result of the ego vehicle is determined based on an intersection of each strategy feasible region of both the ego vehicle and a respective game object and each strategy feasible region of both the ego vehicle and a respective non-game object (FIG. 9 908-914: “Safety cost above a threshold [Wingdings font/0xE0] Include the action in vehicle planning considerations”; para. [0055]-[0056]: “the vehicle computing system may determine a cost associated with each estimated state, such as based on the estimated positions of the vehicle 102 and the object 104 relative to one another […] The one or more factors may include safety of the vehicle 102 and/or object 104 (e.g., avoiding a collision between the vehicle 102 and the object 104) […] The safety of the vehicle 102 and/or object 104 may include a likelihood of collision […] The likelihood of collision may be calculated based on a distance between the vehicle 102 and the object 104 (e.g., within 5 feet, 2 meters, 0.5 meters, etc.), converging trajectories (e.g., trajectory 108 of the object 104 that will substantially intersect a vehicle trajectory associated with an action 110”; para. [0054]: “an object may be determined to be irrelevant to the vehicle based on a determination that the trajectory 108 associated with the object 104, such as trajectory 108(4) associated with object 104(4), will not intersect and/or converge on a vehicle trajectory associated with an action 110”, wherein actions which lead to avoiding of collision or trajectories which do not intersect corresponds to intersection of each strategy feasible region of both the ego vehicle and a respective game object and intersection of each strategy feasible region of both the ego vehicle and a respective game object and each strategy feasible region of both the ego vehicle and a respective non-game object).
Regarding claim 9, Caldwell in view of Kobilarov and further in view of Ersal teaches the method according to claim 2. Caldwell further teaches further comprising: obtaining a non-game object of the ego vehicle (FIG. 1; para. [0054]: “the vehicle computing system may be configured to identify one or more objects 104, such as 104(4), that are irrelevant to the vehicle 102.”); and based on a motion status of the non-game object (para. [0054]: “an object may be determined to be irrelevant to the vehicle based on a determination that the trajectory 108 associated with the object 104, such as trajectory 108(4) associated with object 104(4), will not intersect and/or converge on a vehicle trajectory associated with an action 110. For example, the trajectory 108(4) associated with object 104(4) includes a turn away from the vehicle 102 on a road substantially perpendicular to the vehicle 102 direction of travel.”),
constraining a longitudinal sampling strategy space corresponding to the ego vehicle, or constraining a lateral sampling strategy space corresponding to the ego vehicle (para. [0054]: “an object may be determined to be irrelevant to the vehicle based on a determination that the trajectory 108 associated with the object 104, such as trajectory 108(4) associated with object 104(4), will not intersect and/or converge on a vehicle trajectory associated with an action 110. For example, the trajectory 108(4) associated with object 104(4) includes a turn away from the vehicle 102 on a road substantially perpendicular to the vehicle 102 direction of travel.”, wherein “will not intersect and/or converge on a vehicle trajectory” indicates constraining a longitudinal sampling strategy space and/or lateral sampling strategy space as the ego vehicle will not intersect with the object).
Regarding claim 10, Caldwell in view of Kobilarov and further in view of Ersal teaches the method according to claim 2. Caldwell further teaches further comprising: obtaining a non-game object of the game object of the ego vehicle (FIG. 3; para. [0092: “the vehicle computing system may designate the objects 304 as the primary object 304(1) and the secondary object 304(2). The secondary object 304(2) may be designated as such based on a determination that the secondary object 304(2) is following the primary object 304(1) (e.g., has a substantially similar direction of travel and is located behind the primary object 304(1)).”, wherein primary object corresponds to a non-game object of the game object as indicated from “following the primary object”); and based on a motion status of the non-game object, constraining a longitudinal sampling strategy space corresponding to the game object of the ego vehicle, or constraining a lateral sampling strategy space corresponding to the game object of the ego vehicle (para. [0092]: “determination that the secondary object 304(2) is predicted to react in a similar way to the primary object 304(1), such as in response to the action of the vehicle 302 (e.g., similar predicted trajectories between the objects, etc.)”; para. [0095]: “the vehicle computing system may determine that the negative acceleration of the primary object 304(1) may cause the secondary object 304(2) to also slow down, such as to avoid a collision with the primary object 304(1)”, wherein secondary object slow down to avoid collision with primary object indicates constraining a longitudinal sampling strategy space).
Regarding claim 11, Caldwell in view of Kobilarov and further in view of Ersal teaches the method according to claim 8. Kobilarov further teaches wherein when the intersection is an empty set, a conservative traveling decision of the ego vehicle is performed (para. [0066]: “Using this data, the planning component 426 can determine a route to travel from a first location (e.g., a current location) to a second location (e.g., a target location) to avoid objects in an environment. In at least some examples, such a planning component 426 may determine there is no such collision free path and, in turn, provide a path which brings vehicle 402 to a safe stop avoiding all collisions and/or otherwise mitigating damage”, wherein determine there is no such collision free path indicates when the intersection is an empty set); and the conservative traveling decision comprises an action of making the ego vehicle safely stop or an action of making the ego vehicle safely decelerate for traveling (para. [0066]: “Using this data, the planning component 426 can determine a route to travel from a first location (e.g., a current location) to a second location (e.g., a target location) to avoid objects in an environment. In at least some examples, such a planning component 426 may determine there is no such collision free path and, in turn, provide a path which brings vehicle 402 to a safe stop avoiding all collisions and/or otherwise mitigating damage).
Regarding claim 12, Caldwell in view of Kobilarov and further in view of Ersal teaches the method according to claim 1. Caldwell further teaches wherein the game object or a non-game object is determined by attention (para. [0054]: “In various examples, the vehicle computing system may be configured to identify one or more objects 104, such as 104(4), that are irrelevant to the vehicle 102. An object 104 may be relevant to the vehicle 102 if the object 104 and the vehicle 102 could potentially occupy the same space or come within a threshold distance of one another over a period of time (e.g., potential for a collision). In various examples, an object may be determined to be irrelevant to the vehicle based on a determination that the trajectory 108 associated with the object 104, such as trajectory 108(4) associated with object 104(4), will not intersect and/or converge on a vehicle trajectory associated with an action 110. For example, the trajectory 108(4) associated with object 104(4) includes a turn away from the vehicle 102 on a road substantially perpendicular to the vehicle 102 direction of travel.”, wherein “turn away” is an example corresponding to attention).
Regarding claim 14, it recites an apparatus for intelligent driving decision-making, comprising: at least one processor; and one or more memories coupled to the at least one processor and storing programming instructions for execution by the at least one processor (Caldwell para. [0179]: “A vehicle comprising: a sensor; one or more processors; and memory storing processor-executable instructions that, when executed by the one or more processors, configure the vehicle to: […]”; Caldwell para. [0149]: “Generally, computer-executable instructions include routines, programs, objects, components, data structures”; See claim 1) to perform claim limitations similar to those of the method claim 1, and thus is rejected on the same basis.
Regarding claim 15, it recites an apparatus claim reciting claim limitations similar to those of the method claim 2, and thus is rejected on the same basis.
Regarding claim 16, it recites an apparatus claim reciting claim limitations similar to those of the method claim 3, and thus is rejected on the same basis.
Regarding claim 17, it recites an apparatus claim reciting claim limitations similar to those of the method claim 4, and thus is rejected on the same basis.
Regarding claim 18, it recites an apparatus claim reciting claim limitations similar to those of the method claim 5, and thus is rejected on the same basis.
Regarding claim 20, it recites a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores programming instructions for execution by at least one processor to (Caldwell para. [0195]: “A non-transitory computer-readable medium storing instructions that, when executed, cause one or more processors to perform operations comprising […]”; See claim 1) perform claim limitations similar to those of the method claim 1, and thus is rejected on the same basis.
Claims 6 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Caldwell, in view of Kobilarov and further in view of Ersal, and further in view of Wray (US 20210157315 A1).
Regarding claim 6, Caldwell in view of Kobilarov and further in view of Ersal teaches the method according to claim 1. Caldwell further teaches wherein when there are two or more game objects (FIG. 1 104(1) and 104 (2); para. [0046]: “In some examples, the action(s) 110 may be determined based on the detected objects 104. For example, the vehicle computing system may detect one or more objects 104, such as objects 104(1) and 104(2), approaching an intersection from the right”), the traveling decision-making result of the ego vehicle is determined based on (FIG. 2; para. [0048]: “For example, the vehicle computing system may identify an action 110, such as action 110(5) in which the vehicle 102 may safely transit through the intersection in front of the objects 104(1) and 104(2), without negatively effecting the objects 104(1) and 104(2), such as by requiring the objects 104(1) and 104(2), to slow down to avoid a collision with the vehicle 102.”; para. [0170]: “Based on a determination that the safety cost is not above the threshold (“No” at operation 908), the process, at operation 912, may include determining a total cost associated with the action”, wherein the safety cost being below a threshold indicates strategy feasible region of both the ego vehicle and both game objects), but fails to specifically teach the traveling decision-making result of the ego vehicle is determined based on each strategy feasible region of both the ego vehicle and a respective game object.
However, in the same field of endeavor, Wray the traveling decision-making result of the ego vehicle is determined based on each strategy feasible region of both the ego vehicle and a respective game object (FIG. 7; para. [0201]: “At 7020, and as described above, the technique 7000 identifies an intersecting set of actions as an intersection of the respective sets of candidate actions. At 7030, the technique 7000 selects an action from the intersecting set of actions based on respective priorities of the respective decision components.”; para. [0190]: “For example, as described with respect to FIG. 5A, for the SSOCEM associated with the first vehicle 5008, the candidate vehicle control actions can be the set {go}. For example, as described with respect to FIG. 5A, for the SSOCEM associated with the second vehicle 5012, the candidate vehicle control actions can be the set {stop}”; para. [0195]: “In an example, the technique 6000 can also include instantiating a second decision component instance in response to receiving second sensor information corresponding to a second external object; receiving a second set of candidate vehicle control actions from the second decision component instance; and determining a third set of actions as an intersection between the first set of candidate vehicle control actions and the second set of candidate vehicle control actions”).
Wray is analogous to the claimed invention because it pertains to the planning of trajectory in response to objects. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have a simple substitution of the multi-object trajectory determination of Caldwell in view of Kobilarov and further in view of Ersal with the intersecting plurality of single-obstacle decision making processes of Wray, because both methods are known to determine a safe/optimal trajectory and would have obtained the predictable result of resulting in a trajectory that avoids collision with multiple objects, as a trajectory that is determined to avoid collision with multiple object must be a safe trajectory to avoid collision with each object.
Regarding claim 19, to perform claim limitations similar to those of the method claim 6, and thus is rejected on the same basis.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Caldwell, in view of Kobilarov, and further in view of Ersal and further in view of Alalao (GB 2588983 A).
Regarding claim 13, Caldwell in view of Kobilarov and further in view of Ersal teaches the method according to claim 1, but fails to specifically teach further comprising: displaying at least one of the following through a human-computer interaction interface: the traveling decision-making result of the ego vehicle, the strategy feasible region of the traveling decision-making result, a traveling trajectory of the ego vehicle corresponding to the traveling decision-making result of the ego vehicle, or a traveling trajectory of the game object corresponding to the traveling decision-making result of the ego vehicle.
However, Alalao teaches further comprising: displaying at least one of the following through a human-computer interaction interface: the traveling decision-making result of the ego vehicle, the strategy feasible region of the traveling decision-making result, a traveling trajectory of the ego vehicle corresponding to the traveling decision-making result of the ego vehicle, or a traveling trajectory of the game object corresponding to the traveling decision-making result of the ego vehicle (para. [0007]: “update the graphical user interface such that the updated graphical user interface displays a trajectory of the vehicle corresponding to the vehicular maneuver”; para. [00155]: “updated graphical user interface includes a representation of the vehicular maneuver. For example, the updated graphical user interface can include a thought bubble with text explaining that the AV 100 is speeding up or slowing down to avoid a pedestrian 192 or vehicle 193. The updated graphical user interface can include arrows showing that the AV 100 is turning to avoid a construction zone. In some embodiments, the AV 100 updates the graphical user interface such that the updated graphical user interface displays a trajectory of the AV 100 corresponding to the vehicular maneuver”; para. [00198]: “The AV 100 determines 2312, using one or more processors, a vehicular maneuver to avoid a collision with the object 1008. For example, the AV 100 may stop, increase speed to get away, slow down, or change lanes. In some embodiments, determining the vehicular maneuver includes generating a trajectory 198 for the AV 100”, wherein “updated trajectory” corresponds to the traveling decision-making result of the ego vehicle).
Alalao is analogous to the claimed invention because it pertains to the planning of trajectory in response to objects. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Caldwell in view of Kobilarov and further in view of Ersal and incorporate displaying the updated maneuver of the autonomous vehicle of Alalao. Doing so will enhance user experience as display of predicted maneuvers and other objects increases the passenger comfort level and provides the passenger with a greater sense of trust in the AV (Alalao para. [0037]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. JEONG (US 20210129865 A1) teaches prioritize lateral movement towards suitable adjacent lanes and the longitudinal movement may only be performed if the lateral change is not possible in order to avoid a collision with an obstacle.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/A.S.K./Examiner, Art Unit 3668
/JAMES J LEE/Supervisory Patent Examiner, Art Unit 3668
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