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 .
DETAILED ACTION
Claims 1-20 are pending. Claims 1-20 are rejected.
Allowable Subject Matter
Claim 6 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. The claims must also be amended to overcome the 101 and 112 rejections.
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 “1-20” are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
On January 7, 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?
Claim 16 reads:
A method for controlling an autonomous vehicle, the method comprising:
receiving, from a trajectory planner, a plan comprising a planned path and a speed plan for the autonomous vehicle to traverse through a portion of a vehicle transportation network;
performing an optimization operation to revise the plan, wherein the optimization operation jointly minimizes a lateral and heading error as compared to the planned path while applying each of a lateral offset constraint and a heading angle constraint as soft constraints, wherein the soft constraints are represented by respective slack variables, and a penalty is applied to at least one of the slack variables that is greater than a penalty applied to the lateral and heading error to prioritize collision avoidance over maintaining the planned path; and
operating at least one control system of the autonomous vehicle according to the plan as revised.
Using the two-step inquiry, it is clear that claim 10 is directed toward non-statutory subject matter, as shown below:
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? Yes, the claim 16 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, calculating, determining).
The method in claim 1 is a mental process that can be practicably performed in the human mind and, therefore, an abstract idea. The abstract ideas are:
performing an optimization operation to revise the plan, wherein the optimization operation jointly minimizes a lateral and heading error as compared to the planned path while applying each of a lateral offset constraint and a heading angle constraint as soft constraints, Analyzing the abstract idea we can understand that the abstract idea with the given examples.
performing an optimization operation to revise the plan, Thinking about short cuts for the way.
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 [receiving data, data gathering, data output] further addressed in WUEC; 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.
Claim 16 does not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. While the claim does recite that the method is for:
receiving, from a trajectory planner, a plan comprising a planned path and a speed plan for the autonomous vehicle to traverse through a portion of a vehicle transportation network; data gathering, receiving data.
operating at least one control system of the autonomous vehicle according to the plan as revised. Data gathering, transmitting data. [if the control system receives data it’s operation is controlled]
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.
Claim 16 does not recite any specific limitation or combination of limitations that are not well-understood, routine, conventional (WURC) activity in the field.
Claim 16 further recites WURC extra steps of:
wherein the optimization operation jointly minimizes a lateral and heading error as compared to the planned path while applying each of a lateral offset constraint and a heading angle constraint as soft constraints, which are all insignificant extra solution; Apply it level
wherein the soft constraints are represented by respective slack variables, and a penalty is applied to at least one of the slack variables that is greater than a penalty applied to the lateral and heading error to prioritize collision avoidance over maintaining the planned path; which are all insignificant extra solution; Apply it level
Analyzing the WURC steps of the abstract idea with the given examples.
we can understand that the abstract idea falls within the WURC Activity MPEP 2106.05(d)(1) Evaluation
improvement consideration WURC consideration MPEP.05(a);
mere instructions to apply an exception consideration MPEP 2106.05(f)
insignificant extra-solution activity consideration MPEP 2106.05(g)
Generic computer performing merely generic computer functions, data gathering, populating tables, sending and receiving data or performing functions ‘known’ in the art.
CONCLUSION
Thus, since claim 16 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 16 is directed towards non-statutory subject matter.
Claim 1 is rejected using the same rejection as made to claim 16.
2-7; 17,18. Apply it level
8, 14; 19. Abstract idea of optimization i.e. thinking of a short cut and Apply it level
9-13; 20. Apply it level
15. insignificant extra solution i.e. Apply it level, linking
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Regarding claims 1-20, the phrase:
"wherein the optimization operation jointly minimizes a lateral and heading error as compared to the planned path while applying each of a lateral offset constraint and a heading angle constraint as soft constraints,
wherein the soft constraints are represented by respective slack variables, and a penalty is applied to at least one of the slack variables that is greater than a penalty applied to the lateral and heading error to prioritize collision avoidance over maintaining the planned path;"
renders the claim indefinite because it is unclear whether the limitation(s) following the phrase are part of the claimed invention. See MPEP § 2173.05(d). This can be clearly witnessed in claim 16. It is unclear weather the phrases are limitations of the claim or general mirative. Claim 16 is a method claim. Some of the limitations are in Gerund form, however; there are phrases that seem to be generally narrative and not claim limitations. Claim 16 is made as an example, however claims 18, 19, 1, 7, 8 also must be corrected.
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 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.
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1,7,15,16,18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Frazzoli US 9645577.
1. An apparatus for controlling an autonomous vehicle, the apparatus comprising:
a processor configured to:
receive, from a trajectory planner, a plan comprising a planned path and a speed plan for the autonomous vehicle to traverse through a portion of a vehicle transportation network; C7L24; Data sources 66 providing information about driving properties (e.g. typical speed and acceleration profiles) of [autonomous self-driving] vehicles that have previously traveled along a given road section [planned path as not all the paths are given only relevant to the path] at a similar time of day. Such data and transmitted to the vehicle through wireless communication from a remotely located database.
perform an optimization operation to revise the plan, wherein the optimization operation jointly minimizes a lateral and heading error as compared to the planned path C20L54; xi. A safety metric (k) computed as the ratio of the maximum lateral acceleration that would be required by the ego vehicle in order to accurately track [minimize error] the candidate trajectory [heading] (computed as the square of the vehicle velocity at a given point on the trajectory divided by radius of curvature at the same point on the given trajectory) to the maximum allowable lateral acceleration [optimization] given the current environmental conditions.
while applying each of a lateral offset constraint and a heading angle constraint as soft constraints, wherein the soft constraints are represented by respective slack variables, and C21L50; an optimal trajectory 250 is identified as one that is deemed most desirable, as determined by analysis of some combination (e.g., a weighted [offset] sum) of the quantitative metrics described in a through c. Typically, the candidate trajectory that exhibits the minimum value of the weighted sum of all performance metrics is deemed the optimal trajectory.
a penalty is applied to at least one of the slack variables that is greater than a penalty applied to the lateral and heading error to prioritize collision avoidance over maintaining the planned path; and C2L35; The costs are expressed as cost rules expressed in a formal language. The cost rules include prioritized and weighted rules. Each of the costs is expressed as an array of values each corresponding either to (a) a priority of a cost rule and an aggregate of violation [penalty] costs of cost rules having that priority, or (b) a function of the candidate trajectory.
operate at least one control system of the autonomous vehicle according to the plan as revised.C17L22; If the actual trajectory of the ego vehicle deviates by more than a threshold amount (set, for example, to indicate unacceptable risk of loss of control, rule violation, or collision) From the planned optimal trajectory (or if other vehicles behave unexpectedly), an emergency procedure is triggered, and the directed graph is reinitialized.
7. The apparatus of claim 1, wherein the slack variables vary based on a distance of the autonomous vehicle to at least one of a boundary or an obstacle. F C20L40; A safety metric (i) computed [uses variables] as the inverse of the minimum of the ratio [variables] of the headway distance [distance form vehicle to obstacle] to the leading vehicle along the candidate trajectory and the difference between the ego vehicle speed at a given point and the speed of the leading vehicle at the same point on the candidate trajectory. This metric is also known as the “time to collision” [LaValle2006].
15. An autonomous vehicle comprising the apparatus of claim 1. Frazzoli C2L57; The facilitating of an operation related to control of a vehicle includes autonomously driving the vehicle.
16. is rejected using the same rejections as made to claim 1.
18. is rejected using the same rejections as made to claim 7.
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.
Claims 2, 5, 9-13, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Frazzoli as applied to claim above, and further in view of Desai US 20250242817.
2. Frazzoli teaches all of the limitations of claim 1 but does not teach, wherein the processor is configured to determine the lateral and heading error using state variables generated using a dynamic bicycle predictive model. However, Desai teaches 21; provide input-to-state stable nonlinear observers that estimate errors in the dynamics of bicycle model and relate these errors to ground-truth tire-road forces. a robustified control barrier function based quadratic program (RCBF-QP) formulation to constrain a vehicle to within its limits-of-handling during safety-necessitated aggressive maneuvers, despite the presence of model errors.
Therefore, it was well known at the time the invention was filed and would have been obvious to one of ordinary skill in the art to combine the teachings with a reasonable expectation of success in order to control safety functions to improve automotive stability such that the claimed invention as a whole would have been obvious.
5. The apparatus of claim 2, wherein the state variables include
a side slip angle, 54; there may be additional sensors for detecting and/or computing sideslip velocities, sideslip angles, percent sideslip, frictional forces, degree of steer, heading, and trajectory.
a filtered yaw rate, 19-20; stability envelopes [filtered i.e. band pass filter] in the yaw rate-sideslip phase-plane for vehicles have been explored using the bicycle model. extended Kalman filters and observers can provide estimates of ground-truth tire-road forces robust to model errors. Also 81; These estimates can be provided to the CBF module 314 to filter nominal control commands, determined by the controller module 308, and constrain the vehicle to within its limits-of-handling.
a heading error, and 81; actual real-world implementation of the inputs provided by the controller module 308 may deviate from the reference trajectory (e.g., deviate in position, velocity, heading, etc.). These errors can reduce the accuracy of the combined vehicle dynamic model, which can be amplified in safety-critical conditions where errors could cause a vehicle to exceed its limits-of-handling.
a lateral error, and 82; estimating errors in the longitudinal component (F.sub.x) of the total tire force and observers for estimating errors in lateral component
wherein the processor is configured to determine the filtered yaw rate by estimating a yaw rate that considers a longitudinal slip ratio using wheel speed and acceleration of the autonomous vehicle as input, and Desal 23; vehicle dynamics may include a number of states, such as but not limited to, vehicle velocities, wheel angular velocity, and yaw rate, as operational states, and wheel slip determined from a model applied to sensor data and operational states.
filtering sensor noise from the yaw rate as estimated. Desai 19-20 Also 86; ΔFx can be modeled as a Markov-like process with a time-constant τ.sub.Fx. n.sub.w represents measurement noise [sensor noise]and Δ.sub.m represents the combined errors in mapping engine torque to τ.sub.d and brake-cylinder pressure to τ.sub.b. w.sub.Fx is a bounded exogenous disturbance.
9. Frazzoli teaches all of the limitations of claim 1 but does not teach, wherein the processor is configured to, once the lateral and heading error between a current state of the autonomous vehicle and a desired state of the autonomous vehicle is above a threshold, implement error state saturation logic to restrict a maximum rate of change of a steering angle to limit overcorrection at a future point in a prediction horizon. However, Desai teaches 25; The command can then be filtered by constraining the requested operational state according to a CBF based on the safety-critical threshold value, as a safety-critical constraint on the vehicle dynamic parameter, and the requested value of the vehicle dynamic parameter. A control signal can be generated and provided to an autonomous driving system for executing the filtered command to control the vehicle. Also 106; an understeering or oversteering vehicle, control, maneuvering and safety are compromised, especially in the presence of errors in modeling the vehicle dynamics.
Therefore, it was well known at the time the invention was filed and would have been obvious to one of ordinary skill in the art to combine the teachings with a reasonable expectation of success in order to control safety functions to improve automotive stability such that the claimed invention as a whole would have been obvious.
10. The apparatus of claim 9, wherein the error state saturation logic is enabled or disabled depending on at least one of a condition of the autonomous vehicle or a condition of the portion of the vehicle transportation network. Desai 25; Based on [logic trigger i.e. enabled or disabled] the current operational state, a safety-critical threshold [logic trigger] value for one or more vehicle dynamic parameters can be determined.
11. The apparatus of claim 10, wherein the error state saturation logic is enabled when
at least one of
a curvature of a lane in the portion of the vehicle transportation network is less than a minimum threshold
and
a speed of the autonomous vehicle is greater than a maximum threshold. Desai 25; Based on the current operational state, a safety-critical threshold value for one or more vehicle dynamic parameters can be determined. 80-81; safety-critical conditions that may occur where a vehicle is approaching a limits-of-handling due to exogenous effects that negatively impact vehicle control. deviate from the reference trajectory (e.g., deviate in position, velocity, heading, etc.). These errors can reduce the accuracy of the combined vehicle dynamic model, which can be amplified in safety-critical conditions.
12. Frazzoli teaches all of the limitations of claim 1 but does not teach, wherein the processor is configured to:
determine a state prediction for the autonomous vehicle for use in the optimization operation; However, Desai teaches 42; Sensors 152 may be used to detect the various operational states and calculate vehicle dynamics, such as wheel slip (e.g., critical slip, combined slip, etc.) lateral and longitudinal slop, steering angles, vehicle mass, vehicle yaw moment of inertia, and acceleration due to gravity.
and determine, using the state prediction, a speed reduction for the optimization operation based on a lookahead curvature of the planned path and steering slew rate limitations of the autonomous vehicle. Desain 44; Sensors 152 may be included to detect not only vehicle conditions but also to detect external conditions as well. Sensors that might be used to detect external conditions can include, for example, sonar, radar, lidar or other vehicle proximity sensors, and cameras or other image sensors. Image sensors can be used to detect objects in an environment surrounding vehicle 100, for example, traffic signs indicating a current speed limit, road curvature, obstacles, surrounding vehicles, and so on. 132; adjusting the driving inputs in a manner that ensures that the real-world value [based on lookahead curvature] of the vehicle dynamic parameter, resulting from executing the command to navigate the vehicle, does not exceed the safety-critical threshold value. Such modifications may include, but not are not limited to, one or more of increasing or decreasing input drive torque, increasing or decreasing input brake torque, changing of input steering angle, or any combination thereof to ensure that, for example, a real-world wheel slip does not exceed the computed safety-critical wheel slip. Also 105 26;37;
Therefore, it was well known at the time the invention was filed and would have been obvious to one of ordinary skill in the art to combine the teachings with a reasonable expectation of success in order to control safety functions to improve automotive stability such that the claimed invention as a whole would have been obvious.
13. The apparatus of claim 12, wherein the processor is configured to: access speed-based and curvature-based tuning parameters from a lookup table to determine a speed reduction for multiple time points. Desai 44; Image sensors can be used to detect objects in an environment surrounding vehicle 100, for example, traffic signs indicating a current speed limit, road curvature, obstacles, surrounding vehicles, and so on. used to implement smart roadways that may actively transmit and/or receive data [stored data i.e. lookup table] or other information. Also 48; data and other information as well as operational instructions that may be used by the processor 206 to autonomous control circuit 210.
17. is rejected using the same rejections as made to claim 2.
20. Frazzoli teaches all of the limitations of claim 16 and further teaches:
providing the speed reduction as input to the optimization operation.C8L7; A vehicle 10 having features and functions (e.g., actuators) that are instrumented to receive and act upon commands 76 corresponding to control actions (e.g., steering, acceleration, deceleration, gear selection)
Frazzoli does not teach determining a speed reduction for the optimization operation based on a lookahead curvature of the planned path and steering slew rate limitations of the autonomous vehicle; and However, Desain teaches 44; Sensors 152 may be included to detect not only vehicle conditions but also to detect external conditions as well. Sensors that might be used to detect external conditions can include, for example, sonar, radar, lidar or other vehicle proximity sensors, and cameras or other image sensors. Image sensors can be used to detect objects in an environment surrounding vehicle 100, for example, traffic signs indicating a current speed limit, road curvature, obstacles, surrounding vehicles, and so on. 132; adjusting the driving inputs in a manner that ensures that the real-world value [based on lookahead curvature] of the vehicle dynamic parameter, resulting from executing the command to navigate the vehicle, does not exceed the safety-critical threshold value. Such modifications may include, but not are not limited to, one or more of increasing or decreasing input drive torque, increasing or decreasing input brake torque, changing of input steering angle, or any combination thereof to ensure that, for example, a real-world wheel slip does not exceed the computed safety-critical wheel slip. Also 105 26;37;
Therefore, it was well known at the time the invention was filed and would have been obvious to one of ordinary skill in the art to combine the teachings with a reasonable expectation of success in order to control safety functions to improve automotive stability such that the claimed invention as a whole would have been obvious.
Claims 3 and 4 are rejected under 35 U.S.C. 103 as being unpatentable over Frazzoli and Desai as applied to claim above, and further in view of Moshchuk US 20130030651.
3. Frazzoli and Desai teach all of the limitations of claim 2 but do not teach the limitations of claim 3, however Moshchuk teaches, wherein the state variables include
a side slip angle, Moshchuk 29; The vehicle slip angle .alpha..sub.j at any prediction point j is defined by matrix P as
a yaw rate, Moshchuk 28; Where x is the state vector consisting of lateral offset, heading angle, lateral velocity and yaw rate, y is an output vector consisting of lateral offset and heading angle, and A is matrix A(V), where V.sub.x is the vehicle longitudinal speed,
a heading error, and Moshchuk 52; The cost function J is based on an error of the lateral position y of the vehicle 40 and an error of the heading angle .phi. of the vehicle 40.
a lateral error, and Moshchuk 52; The deviation between the lateral offset error y.sub.err and heading angle error .phi..sub.err is minimized by the cost function J using the braking control command u.
wherein the yaw rate is an estimated yaw rate that varies according to a longitudinal slip ratio. Moshchuk 29, a friction ellipse for a tire provides an indication of the maximum horizontal force that may be generated for the tire, where the size of the ellipse is dependent on that tire. The vehicle slip angle .alpha..sub.j at any prediction point j is defined by matrix P as:
.alpha..sub.j=PA.sup.j-1x.sub.k+(PA.sup.j-2B+ . . . +PB)u.sub.k (19)
Therefore, it was well known at the time the invention was filed and would have been obvious to one of ordinary skill in the art to combine the teachings with a reasonable expectation of success in order to avoid collision based on differential braking such that the claimed invention as a whole would have been obvious.
4. Frazzoli, Desai and Moshchuk teach all of the limitations of claim 2 and further teach, wherein the processor is configured to determine the side slip angle using the yaw rate as input to a sliding mode observer and a linear adaptive tire force model. Moshchuk 27; heading angle error, V.sub.y is the vehicle lateral velocity, r is the vehicle yaw rate,
Claims 8 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Frazzoli as applied to claim above, and further in view of Kuehnle US 20220379900.
8. Frazzoli teaches all of the limitations of claim 1 but does not teach, wherein the optimization operation jointly minimizes the lateral and heading error as compared to the planned path and steering oscillations. However, Kuehnle teaches 44; The driver's corrective force may be described as the magnitude or force with which he or she makes corrections to the following distance and relative velocity (longitudinal behavior) and/or lane position (lateral behavior). in the context of lateral behavior, a driver 164 that veers from the center of the lane, as detected by the LDW system 222 or forward-facing camera 246, may turn the steering wheel in one direction, as detected by the steering angle sensor 218 to correct the lane position, but in fact, may overcorrect and subsequently turn the steering wheel in the opposite direction. The oscillation of the steering wheel may be understood as a lack of damping and would exhibit a lower damping parameter value than a driver that exhibits little or no oscillation. The uncertainty may be understood as the uncertainty of the slope and y-intercept of a best fit line drawn to a plurality of blocks defined by the parameter values and/or time. The uncertainty of the slope of a best fit line may be, for instance, one-half of the difference between a maximum and minimum slope of the best fit line, where “best fit” means that the sum of the vertical line distances between the line and each point, also known as the residual or the error, is minimized.
Therefore, it was well known at the time the invention was filed and would have been obvious to one of ordinary skill in the art to combine the teachings with a reasonable expectation of success in order to model steering based on frequency response such that the claimed invention as a whole would have been obvious.
19. Is rejected using the same rejections as made to claim 8.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Frazzoli as applied to claim above, and further in view of Kim 2024/0336259.
14. Frazzoli teaches all of the limitations of claim 1 but does not teach, wherein the processor is configured to:
perform the optimization operation using the lateral offset constraint applied pointwise to avoid any collision with respect to a front bumper of the autonomous vehicle, wherein the lateral offset constraint is based on at least one of a boundary or an obstacle, and using the heading angle constraint to avoid any collision with respect to a rear bumper of the autonomous vehicle, wherein the heading angle constraint is calculated from a rear axle of the autonomous vehicle considering a width of the autonomous vehicle. However, Kim teaches para 68; The autonomous driving controller 100 may be configured to determine the expected collision area in the following step, including setting a body of the vehicle in a virtual rectangular shape based on the length, the width [lateral offset], and the height of the vehicle, and the distance from the front end portion [front bumper, vehicle configuration points such as axles] of the vehicle to the CG of the vehicle, identifying the distance from the CG point of the vehicle to another vehicle, and the relative heading angle of the vehicle with respect to another vehicle (the angle between the heading position of the vehicle and the heading position of another vehicle approaching [pointwise as approaching needs at least two points in time] the vehicle), projecting another vehicle in the direction of the relative heading angle determined as above when the distance from the CG of the vehicle to another vehicle is within a predetermined distance, and overlapping another vehicle projected in the direction of the relative heading angle on the body of the vehicle set in the virtual rectangular shape as above and determining the cross-sectional area of the overlapping portion.
Therefore, it was well known at the time the invention was filed and would have been obvious to one of ordinary skill in the art to combine the teachings with a reasonable expectation of success in order to control collision avoidance of vehicle such that the claimed invention as a whole would have been obvious.
Conclusion
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/SIHAR A KARWAN/Examiner, Art Unit 3664
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