DETAILED ACTION
Response to Amendment
This office action regarding application number 18/916,026, filed October 15, 2024, is in response to the applicants arguments and amendments filed 5/5/2026. Claims 1, 6, 8, 13, 15, and 20 have been amended. Claims 1-20 are currently pending and are addressed below.
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
The applicants arguments and amendments to the application have overcome some of the objections and rejections previously set forth in the Non-Final action mailed February 18, 2026. Applicants amendments to the specification have overcome SOME of the previous objections, the specification has been amended to remove reference number 308, therefore the associated drawing objection is withdrawn. Applicants amendments to claims 1, 8, and 15 have been deemed sufficient to overcome the previous 35 USC 102 rejections through the inclusion of “ determining a road friction coefficient of the wheel, the road friction coefficient associated with a characteristic curve between a lateral force of the vehicle and a slip angle of a wheel of the vehicle … determining a wheel stiffness for the wheel for the normal force from a slope of the characteristic curve associated with the road friction coefficient at the slip angle” therefore the rejections are withdrawn. However as this changes the scope of the claims, new art rejections have been made based on the changes in scope.
However applicants amendments to the drawings have not included descriptive text labels as previously objected to, therefore the below drawing objection is maintained. Additionally the applicants arguments have been fully considered but are not fully persuasive for the reasons seen below.
Applicant’s arguments with respect to claim(s) 1, 8, and 15, and in particular the arguments against the previous 102 rejections, 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.
On pages 13-14 the applicant argues “Claim 2 is dependent upon claim 1. With respect to claim 1, Applicant submits that Berntorp does not teach or suggest the feature of determining a wheel stiffness for the wheel for the normal force from a slope of the characteristic curve associated with the road friction coefficient at the slip angle, as specified in amended claim 1. Therefore, Laine and Berntorp, either alone or in any combination, do not teach or suggest at least this feature of amended claim 1. Accordingly, Applicant submits that claim 1 and its dependent claim 2 are patentable over Laine, Berntorp and the prior art of record.”, the examiner respectfully disagrees.
MPEP 2142-2144 discusses the requirements for a case of obviousness using 35 USC 103 and provides examples of such cases. MPEP 2111 discusses Broadest Reasonable Interpretation and the interpretation of claims.
As discussed in the rejections below Berntorp teaches systems for controlling a vehicle using a friction function describing a friction between a type of surface of the road and a tire of the vehicle as a function of a slip of a wheel of the vehicle including
calculating the wheel stiffness by determining a slope of a characteristic curve of a tire model at the slip angle, wherein the characteristic curve corresponds to the road friction coefficient (Paragraph [0021], “Linear parameters include a value of an initial slope of the friction function defining a stiffness of the tire for each wheel.”) (Paragraph [0034], “controlling a vehicle moving on a road, wherein the method uses a processor coupled to a memory storing parameters of multiple friction functions, each friction function describes a friction between a type of surface of the road and a tire of the vehicle as a function of a slip of a wheel of the vehicle, the parameters of each friction function include an initial slope of the friction function defining a stiffness of the tire and one or combination of a peak friction, a shape factor and a curvature factor of the friction function”).
Here Berntrop is using a friction function derived from a slip of the wheel, the parameters of the friction function include a slop, and that slop defines a stiffness of the wheel.
Therefore the combination of Laine, Shiozawa, and Berntrop teaches calculating the wheel stiffness by determining a slope of a characteristic curve of a tire model at the slip angle, wherein the characteristic curve corresponds to the road friction coefficient.
Drawings
The drawings are objected to because the unlabeled rectangular box(es) shown in the drawings should be provided with descriptive text labels. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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 factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 1-2, 5-9, 12-16, and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Laine (US-20240182041) in view of Shiozawa (US-20110106458) and further in view of Berntorp (US-20200290625).
Regarding claim 1, Laine teaches a method of operating a vehicle comprising (Abstract, "A method for controlling motion of a heavy-duty vehicle")
determining a road friction coefficient of the wheel (Paragraph [0061], "The prediction function, i.e., the mapping between slip and force is determined by the current tire parameters such as tire slip stiffness properties, tire thread area temperature, tire nominal inflation pressure, current tire normal force, wheel rotation speed, tire wear, and road friction coefficient.") (Paragraph [0106], "The one or more estimated tire parameters Sa21 optionally comprise any of: tire wear, tire longitudinal stiffness, tire lateral stiffness, tire rolling resistance, tire peak friction, tire rolling radius, tire contact patch properties, tire balance properties and wheel alignment properties.")
determining the slip angle of the wheel (Paragraph [0105], "These optional sensors 510 are arranged to measure one or more operating parameters of the tire, where the one or more operating parameters may comprise any of: vehicle speed, wheel rotation speed, tire pressure, tire temperature, tire acceleration, tire strain, tire GPS position, weather, ambient temperature, rain classification data, normal load, slip angle, steer angle, and applied positive/negative torque to the tire.")
at a selected prediction step during operation of the vehicle (Paragraph [0061], "According to a first example, the VMM 360 uses input from the tire model in order to predict a generated wheel force as a function of wheel slip. The prediction function, i.e., the mapping between slip and force is determined by the current tire parameters such as tire slip stiffness properties, tire thread area temperature, tire nominal inflation pressure, current tire normal force, wheel rotation speed, tire wear, and road friction coefficient.")
measuring an acceleration of the vehicle at the selected prediction step (Paragraph [0105], "These optional sensors 510 are arranged to measure one or more operating parameters of the tire, where the one or more operating parameters may comprise any of: vehicle speed, wheel rotation speed, tire pressure, tire temperature, tire acceleration, tire strain, tire GPS position, weather, ambient temperature, rain classification data, normal load, slip angle, steer angle, and applied positive/negative torque to the tire.")
calculating a normal force for the vehicle at the selected prediction step from the acceleration (Paragraph [0070], "the VMM function 360 continuously determines a vehicle state s (often a vector variable) comprising positions, speeds, accelerations, yaw motions, normal forces and articulation angles of the different units in the vehicle combination by monitoring vehicle state and behavior using various sensors 510 arranged on the vehicle 100, often but not always in connection to the MSDs")
determining a wheel stiffness for the wheel for the normal force at the slip angle (Paragraph [0011], "According to aspects, the one or more estimated tire parameters comprise any of: tire wear, tire longitudinal stiffness, tire lateral stiffness") (Paragraph [0054], "The normal force F.sub.z is key to determining some important vehicle properties. For instance, the normal force to a large extent determines the achievable longitudinal tire force F.sub.x by the wheel since, normally, F.sub.x≤μ F.sub.z, where μ is a friction coefficient associated with a road friction condition.") (Paragraph [0056], "The tire stiffnesses C.sub.x and C.sub.y normally increase with wear w and normal force F.sub.z. ... Given a tire model such as the function C.sub.x(.Math.)λ.sub.x and/or the function C.sub.y(.Math.)α and input data related to the tire parameters w, F.sub.z, it is possible for a VCU to obtain an accurate relationship between generated wheel force and wheel slip. This relationship will change in dependence of the tire parameters, i.e., the relationship will be a dynamic relationship which is updated over time as the tire wears and as the normal force F.sub.z of the tire changes," here the system can determine tire parameter such as longitudinal and lateral stiffness, the system calculates these properties using a normal force in the tire model functions)
generating a control input for the vehicle using a model predictive control with the wheel stiffness as input (Paragraph [0038], "For example, the tire models disclosed herein may be used to model a relationship between generated wheel force and wheel slip, which relationship then allows the VCU to better control the vehicle by requesting a wheel slip from a torque generating device instead of a direct request for torque. The torque generating device is then able to maintain a much more stable generated wheel force due to a higher bandwidth control loop run locally, i.e., closer to the wheel end.")
and controlling, at a processor, the vehicle using the control input generated by the model predictive control (Paragraph [0007], "The method also comprises configuring a tire model, where the tire model defines a relationship between wheel slip and generated wheel force and where the tire model is parameterized by the one or more tire parameters, and controlling the motion of the heavy-duty vehicle based on the relationship between wheel slip and generated wheel force. This way the vehicle control can be based on an accurate and up to date tire model which better reflects the current properties of the tire.").
However Laine does not explicitly teach the road friction coefficient associated with a characteristic curve between a lateral force of the vehicle and a slip angle of a wheel of the vehicle.
Shiozawa teaches road surface friction coefficient estimating device includes a lateral force detecting section for detecting the lateral force of a wheel during traveling including
the road friction coefficient associated with a characteristic curve between a lateral force of the vehicle and a slip angle of a wheel of the vehicle (Paragraph [0006], “a road surface friction coefficient estimating section that: stores information about a characteristic curve in a coordinate plane, wherein the coordinate plane has a coordinate axis representing the lateral force and a coordinate axis representing the slip angle, and wherein the characteristic curve represents a relationship between the lateral force and the slip angle under condition of a reference road surface friction coefficient”) (Paragraph [0058], “Road surface .mu. calculating section 3 calculates an estimated value of the road surface .mu. of the actual traveled road surface on the basis of the thus-obtained characteristic map of the tire characteristic curve under condition of the reference road surface.”).
Laine and Shiozawa are analogous art as they are both generally related to controlling vehicles based on tire and road characteristics.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include the road friction coefficient associated with a characteristic curve between a lateral force of the vehicle and a slip angle of a wheel of the vehicle of Shiozawa in the system for controlling a vehicle of Laine with a reasonable expectation of success in order to prevent the occurrence of a loss of braking or driving force due to slippage (Paragraph [0116], “This makes it possible to calculate on the basis of the ratio between the lateral force and slip angle the actual road surface .mu. of the traveled road surface, if the lateral force and slip angle can be detected. Accordingly, it is possible to estimate the road surface .mu. of the traveled road surface before the occurrence of slippage. This makes it possible to suitably control the steering assist torque of the vehicle according to the road surface .mu. of the traveled road surface. As a result, it is possible to prevent the occurrence of a loss in braking/driving force due to slippage, and prevent spinning and drifting-out, while the vehicle is turning.”).
However the combination does not explicitly teach determining a wheel stiffness for the wheel for the normal force from a slope of the characteristic curve associated with the road friction coefficient at the slip angle.
Berntorp teaches systems for controlling a vehicle using a friction function describing a friction between a type of surface of the road and a tire of the vehicle as a function of a slip of a wheel of the vehicle including
determining a wheel stiffness for the wheel for the normal force from a slope of the characteristic curve associated with the road friction coefficient at the slip angle (Paragraph [0021], “Linear parameters include a value of an initial slope of the friction function defining a stiffness of the tire for each wheel.”) (Paragraph [0034], “controlling a vehicle moving on a road, wherein the method uses a processor coupled to a memory storing parameters of multiple friction functions, each friction function describes a friction between a type of surface of the road and a tire of the vehicle as a function of a slip of a wheel of the vehicle, the parameters of each friction function include an initial slope of the friction function defining a stiffness of the tire and one or combination of a peak friction, a shape factor and a curvature factor of the friction function”).
Laine, Shiozawa and Berntorp are analogous art as they are both generally related to controlling vehicles based on tire and road characteristics.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include determining a wheel stiffness for the wheel for the normal force from a slope of the characteristic curve associated with the road friction coefficient at the slip angle of Berntorp in the system for controlling a vehicle of Laine and Shiozawa with a reasonable expectation of success in order to improve the accuracy and safety of the vehicle control by to rapidly estimate vehicle and road characteristics while driving (Paragraph [0016], “In contrast, the aggressive driving changes the friction function rapidly and non-linearly. Hence, controlling the vehicle using values of the linear part of the friction function can jeopardize accuracy and safety of vehicle control. In addition, non-linear variations of the friction function during the aggressive driving and relatively short time when a vehicle is driven under a specific style of the aggressive driving make the learning of the non-linear part of the friction function impractical. Hence, there is still a need for a method that can rapidly estimate non-linear part of the friction function during a real-time control of the vehicle.”).
Regarding claim 2, the combination of Laine, Shiozawa, and Berntrop teaches the method as discussed above in claim 1, however Laine does not explicitly teach further comprising calculating the wheel stiffness by determining a slope of a characteristic curve of a tire model at the slip angle, wherein the characteristic curve corresponds to the road friction coefficient.
Berntorp teaches systems for controlling a vehicle using a friction function describing a friction between a type of surface of the road and a tire of the vehicle as a function of a slip of a wheel of the vehicle including
calculating the wheel stiffness by determining a slope of a characteristic curve of a tire model at the slip angle, wherein the characteristic curve corresponds to the road friction coefficient (Paragraph [0021], “Linear parameters include a value of an initial slope of the friction function defining a stiffness of the tire for each wheel.”) (Paragraph [0034], “controlling a vehicle moving on a road, wherein the method uses a processor coupled to a memory storing parameters of multiple friction functions, each friction function describes a friction between a type of surface of the road and a tire of the vehicle as a function of a slip of a wheel of the vehicle, the parameters of each friction function include an initial slope of the friction function defining a stiffness of the tire and one or combination of a peak friction, a shape factor and a curvature factor of the friction function”).
Laine and Berntorp are analogous art as they are both generally related to controlling vehicles based on tire and road characteristics.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include calculating the wheel stiffness by determining a slope of a characteristic curve of a tire model at the slip angle, wherein the characteristic curve corresponds to the road friction coefficient of Berntorp in the system for controlling a vehicle of Laine with a reasonable expectation of success in order to improve the accuracy and safety of the vehicle control by to rapidly estimate vehicle and road characteristics while driving (Paragraph [0016], “In contrast, the aggressive driving changes the friction function rapidly and non-linearly. Hence, controlling the vehicle using values of the linear part of the friction function can jeopardize accuracy and safety of vehicle control. In addition, non-linear variations of the friction function during the aggressive driving and relatively short time when a vehicle is driven under a specific style of the aggressive driving make the learning of the non-linear part of the friction function impractical. Hence, there is still a need for a method that can rapidly estimate non-linear part of the friction function during a real-time control of the vehicle.”).
Regarding claim 5, the combination of Laine, Shiozawa, and Berntrop teaches the method as discussed above in claim 1, Laine further teaches wherein one of (i) the wheel is a front wheel and the wheel stiffness is a front wheel stiffness; and (ii) the wheel is a rear wheel and the wheel stiffness is a rear wheel stiffness (Paragraph [0105], "With reference also to FIG. 5, FIG. 6A shows a method for controlling motion of a heavy-duty vehicle 100. The method comprises obtaining Sa1 input data 561, 562 related to one or more parameters of a tire 150, 160, 170 on the heavy-duty vehicle 100,” here as can as be seen in figure one tires 150, 160, 170 include both front and rear wheels and the method Sa1 can be performed for any of those tires).
Regarding claim 6, the combination of Laine, Shiozawa, and Berntrop teaches the method as discussed above in claim 1, Laine further teaches wherein the slip angle is in a non-linear region of the characteristic curve (Paragraph [0055], "FIG. 2 shows a graph 200 illustrating an example of achievable tire forces F.sub.x, F.sub.y as function of wheel slip. The longitudinal tire force Fx shows an almost linearly increasing part 210 for small wheel slips, followed by a part 220 with more non-linear behavior for larger wheel slips.", as can be seen in figure 2, which includes non-linear areas).
Regarding claim 7, the combination of Laine, Shiozawa, and Berntrop teaches the method as discussed above in claim 1, Laine further teaches determining the wheel stiffness and the slip angle from measurements obtained while the vehicle is being operated (Paragraph [0008], "The sensors can be configured to provide real-time data from the tire, thus enabling a real-time dynamic adaptation of the tire model which quickly reacts to changes in tire properties. Thus, if tire properties change, so will the tire model, which is an advantage,” here the system is operating is real time while the vehicle is being operated).
Regarding claim 8, Laine teaches a system for operating an autonomous vehicle comprising (Abstract, "A method for controlling motion of a heavy-duty vehicle")
a sensor for measuring a state parameter of the autonomous vehicle, the state parameter including a slip angle of a wheel of the autonomous vehicle (Paragraph [0105], "These optional sensors 510 are arranged to measure one or more operating parameters of the tire, where the one or more operating parameters may comprise any of: vehicle speed, wheel rotation speed, tire pressure, tire temperature, tire acceleration, tire strain, tire GPS position, weather, ambient temperature, rain classification data, normal load, slip angle, steer angle, and applied positive/negative torque to the tire.")
and an acceleration of the autonomous vehicle (Paragraph [0105], "These optional sensors 510 are arranged to measure one or more operating parameters of the tire, where the one or more operating parameters may comprise any of: vehicle speed, wheel rotation speed, tire pressure, tire temperature, tire acceleration, tire strain, tire GPS position, weather, ambient temperature, rain classification data, normal load, slip angle, steer angle, and applied positive/negative torque to the tire.")
a processor configured to (Paragraph [0139], “Processing circuitry 710 is provided using any combination of one or more of a suitable central processing unit CPU, multiprocessor, microcontroller, digital signal processor DSP, etc., capable of executing software instructions stored in a computer program product, e.g. in the form of a storage medium 730.”)
determine a road friction coefficient of the wheel at a selected prediction step from the state parameter (Paragraph [0061], "The prediction function, i.e., the mapping between slip and force is determined by the current tire parameters such as tire slip stiffness properties, tire thread area temperature, tire nominal inflation pressure, current tire normal force, wheel rotation speed, tire wear, and road friction coefficient.") (Paragraph [0106], "The one or more estimated tire parameters Sa21 optionally comprise any of: tire wear, tire longitudinal stiffness, tire lateral stiffness, tire rolling resistance, tire peak friction, tire rolling radius, tire contact patch properties, tire balance properties and wheel alignment properties.")
calculate a normal force for the autonomous vehicle at the selected prediction step from the acceleration (Paragraph [0070], "the VMM function 360 continuously determines a vehicle state s (often a vector variable) comprising positions, speeds, accelerations, yaw motions, normal forces and articulation angles of the different units in the vehicle combination by monitoring vehicle state and behavior using various sensors 510 arranged on the vehicle 100, often but not always in connection to the MSDs")
determine a wheel stiffness for the wheel for the normal force (Paragraph [0011], "According to aspects, the one or more estimated tire parameters comprise any of: tire wear, tire longitudinal stiffness, tire lateral stiffness") (Paragraph [0054], "The normal force F.sub.z is key to determining some important vehicle properties. For instance, the normal force to a large extent determines the achievable longitudinal tire force F.sub.x by the wheel since, normally, F.sub.x≤μ F.sub.z, where μ is a friction coefficient associated with a road friction condition.") (Paragraph [0056], "The tire stiffnesses C.sub.x and C.sub.y normally increase with wear w and normal force F.sub.z. ... Given a tire model such as the function C.sub.x(.Math.)λ.sub.x and/or the function C.sub.y(.Math.)α and input data related to the tire parameters w, F.sub.z, it is possible for a VCU to obtain an accurate relationship between generated wheel force and wheel slip. This relationship will change in dependence of the tire parameters, i.e., the relationship will be a dynamic relationship which is updated over time as the tire wears and as the normal force F.sub.z of the tire changes," here the system can determine tire parameter such as longitudinal and lateral stiffness, the system calculates these properties using a normal force in the tire model functions)
generate a control input for the autonomous vehicle using a model predictive control having wheel stiffness as input (Paragraph [0038], "For example, the tire models disclosed herein may be used to model a relationship between generated wheel force and wheel slip, which relationship then allows the VCU to better control the vehicle by requesting a wheel slip from a torque generating device instead of a direct request for torque. The torque generating device is then able to maintain a much more stable generated wheel force due to a higher bandwidth control loop run locally, i.e., closer to the wheel end.")
and control the autonomous vehicle using the control input generated by the model predictive control (Paragraph [0007], "The method also comprises configuring a tire model, where the tire model defines a relationship between wheel slip and generated wheel force and where the tire model is parameterized by the one or more tire parameters, and controlling the motion of the heavy-duty vehicle based on the relationship between wheel slip and generated wheel force. This way the vehicle control can be based on an accurate and up to date tire model which better reflects the current properties of the tire.").
However Laine does not explicitly teach select a characteristic curve associated with the road friction coefficient, the characteristic curve between a lateral force of the vehicle and a slip angle of a wheel of the vehicle.
Shiozawa teaches road surface friction coefficient estimating device includes a lateral force detecting section for detecting the lateral force of a wheel during traveling including
select a characteristic curve associated with the road friction coefficient, the characteristic curve between a lateral force of the vehicle and a slip angle of a wheel of the vehicle (Paragraph [0006], “a road surface friction coefficient estimating section that: stores information about a characteristic curve in a coordinate plane, wherein the coordinate plane has a coordinate axis representing the lateral force and a coordinate axis representing the slip angle, and wherein the characteristic curve represents a relationship between the lateral force and the slip angle under condition of a reference road surface friction coefficient”) (Paragraph [0057], “The tire characteristic curve under condition of the reference road surface which forms the characteristic map is obtained beforehand, for example, by a running test of the vehicle.”) (Paragraph [0058], “Road surface .mu. calculating section 3 calculates an estimated value of the road surface .mu. of the actual traveled road surface on the basis of the thus-obtained characteristic map of the tire characteristic curve under condition of the reference road surface.”).
Laine and Shiozawa are analogous art as they are both generally related to controlling vehicles based on tire and road characteristics.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include select a characteristic curve associated with the road friction coefficient, the characteristic curve between a lateral force of the vehicle and a slip angle of a wheel of the vehicle of Shiozawa in the system for controlling a vehicle of Laine with a reasonable expectation of success in order to prevent the occurrence of a loss of braking or driving force due to slippage (Paragraph [0116], “This makes it possible to calculate on the basis of the ratio between the lateral force and slip angle the actual road surface .mu. of the traveled road surface, if the lateral force and slip angle can be detected. Accordingly, it is possible to estimate the road surface .mu. of the traveled road surface before the occurrence of slippage. This makes it possible to suitably control the steering assist torque of the vehicle according to the road surface .mu. of the traveled road surface. As a result, it is possible to prevent the occurrence of a loss in braking/driving force due to slippage, and prevent spinning and drifting-out, while the vehicle is turning.”).
However the combination does not explicitly teach determine a wheel stiffness for the wheel for the normal force from a slope of the characteristic curve associated with the road friction coefficient at the slip angle.
Berntorp teaches systems for controlling a vehicle using a friction function describing a friction between a type of surface of the road and a tire of the vehicle as a function of a slip of a wheel of the vehicle including
determine a wheel stiffness for the wheel for the normal force from a slope of the characteristic curve associated with the road friction coefficient at the slip angle (Paragraph [0021], “Linear parameters include a value of an initial slope of the friction function defining a stiffness of the tire for each wheel.”) (Paragraph [0034], “controlling a vehicle moving on a road, wherein the method uses a processor coupled to a memory storing parameters of multiple friction functions, each friction function describes a friction between a type of surface of the road and a tire of the vehicle as a function of a slip of a wheel of the vehicle, the parameters of each friction function include an initial slope of the friction function defining a stiffness of the tire and one or combination of a peak friction, a shape factor and a curvature factor of the friction function”).
Laine, Shiozawa and Berntorp are analogous art as they are both generally related to controlling vehicles based on tire and road characteristics.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include determine a wheel stiffness for the wheel for the normal force from a slope of the characteristic curve associated with the road friction coefficient at the slip angle of Berntorp in the system for controlling a vehicle of Laine and Shiozawa with a reasonable expectation of success in order to improve the accuracy and safety of the vehicle control by to rapidly estimate vehicle and road characteristics while driving (Paragraph [0016], “In contrast, the aggressive driving changes the friction function rapidly and non-linearly. Hence, controlling the vehicle using values of the linear part of the friction function can jeopardize accuracy and safety of vehicle control. In addition, non-linear variations of the friction function during the aggressive driving and relatively short time when a vehicle is driven under a specific style of the aggressive driving make the learning of the non-linear part of the friction function impractical. Hence, there is still a need for a method that can rapidly estimate non-linear part of the friction function during a real-time control of the vehicle.”).
Regarding claim 9, claim 9 is similar in scope to claim 2, and therefore is rejected under similar rationale.
Regarding claim 12, claim 12 is similar in scope to claim 5, and therefore is rejected under similar rationale.
Regarding claim 13, claim 13 is similar in scope to claim 6, and therefore is rejected under similar rationale.
Regarding claim 14, claim 14 is similar in scope to claim 7, and therefore is rejected under similar rationale.
Regarding claim 15, Laine teaches an autonomous vehicle comprising (Abstract, "A method for controlling motion of a heavy-duty vehicle") (Paragraph [0067], “the techniques disclosed herein are just as applicable with autonomous or semi-autonomous vehicles”)
a slip angle sensor for measuring a slip angle of a wheel of the autonomous vehicle (Paragraph [0105], "These optional sensors 510 are arranged to measure one or more operating parameters of the tire, where the one or more operating parameters may comprise any of: vehicle speed, wheel rotation speed, tire pressure, tire temperature, tire acceleration, tire strain, tire GPS position, weather, ambient temperature, rain classification data, normal load, slip angle, steer angle, and applied positive/negative torque to the tire.")
an accelerometer for measuring an acceleration of the autonomous vehicle (Paragraph [0105], "These optional sensors 510 are arranged to measure one or more operating parameters of the tire, where the one or more operating parameters may comprise any of: vehicle speed, wheel rotation speed, tire pressure, tire temperature, tire acceleration, tire strain, tire GPS position, weather, ambient temperature, rain classification data, normal load, slip angle, steer angle, and applied positive/negative torque to the tire.")
a steering actuator for controlling a steering angle of the autonomous vehicle (Paragraph [0059], “Other example torque generating motion support devices which may be controlled according to the principles discussed herein comprise engine retarders and power steering devices. An MSD control unit 340 may be arranged to control one or more actuators.”)
a processor configured to (Paragraph [0139], “Processing circuitry 710 is provided using any combination of one or more of a suitable central processing unit CPU, multiprocessor, microcontroller, digital signal processor DSP, etc., capable of executing software instructions stored in a computer program product, e.g. in the form of a storage medium 730.”)
determine a road friction coefficient of the wheel at a selected prediction step (Paragraph [0061], "The prediction function, i.e., the mapping between slip and force is determined by the current tire parameters such as tire slip stiffness properties, tire thread area temperature, tire nominal inflation pressure, current tire normal force, wheel rotation speed, tire wear, and road friction coefficient.") (Paragraph [0106], "The one or more estimated tire parameters Sa21 optionally comprise any of: tire wear, tire longitudinal stiffness, tire lateral stiffness, tire rolling resistance, tire peak friction, tire rolling radius, tire contact patch properties, tire balance properties and wheel alignment properties.")
calculate a normal force for the autonomous vehicle at the selected prediction step from the acceleration (Paragraph [0070], "the VMM function 360 continuously determines a vehicle state s (often a vector variable) comprising positions, speeds, accelerations, yaw motions, normal forces and articulation angles of the different units in the vehicle combination by monitoring vehicle state and behavior using various sensors 510 arranged on the vehicle 100, often but not always in connection to the MSDs")
determine a wheel stiffness for the wheel for the normal force at the slip angle (Paragraph [0011], "According to aspects, the one or more estimated tire parameters comprise any of: tire wear, tire longitudinal stiffness, tire lateral stiffness") (Paragraph [0054], "The normal force F.sub.z is key to determining some important vehicle properties. For instance, the normal force to a large extent determines the achievable longitudinal tire force F.sub.x by the wheel since, normally, F.sub.x≤μ F.sub.z, where μ is a friction coefficient associated with a road friction condition.") (Paragraph [0056], "The tire stiffnesses C.sub.x and C.sub.y normally increase with wear w and normal force F.sub.z. ... Given a tire model such as the function C.sub.x(.Math.)λ.sub.x and/or the function C.sub.y(.Math.)α and input data related to the tire parameters w, F.sub.z, it is possible for a VCU to obtain an accurate relationship between generated wheel force and wheel slip. This relationship will change in dependence of the tire parameters, i.e., the relationship will be a dynamic relationship which is updated over time as the tire wears and as the normal force F.sub.z of the tire changes," here the system can determine tire parameter such as longitudinal and lateral stiffness, the system calculates these properties using a normal force in the tire model functions)
calculate a steering command for the autonomous vehicle using a model predictive control having the wheel stiffness as input (Paragraph [0038], "For example, the tire models disclosed herein may be used to model a relationship between generated wheel force and wheel slip, which relationship then allows the VCU to better control the vehicle by requesting a wheel slip from a torque generating device instead of a direct request for torque. The torque generating device is then able to maintain a much more stable generated wheel force due to a higher bandwidth control loop run locally, i.e., closer to the wheel end.") (Paragraph [0071], “The result of the motion estimation 520, i.e., the estimated vehicle state s, is input to a global force generation module 530 which determines the required global forces on the vehicle units which need to be generated in order to meet the motion requests from the TSM 370. An MSD coordination function 540 allocates, e.g., wheel forces and coordinates other MSDs such as steering and suspension.”)
and control the steering actuator using the steering command to steer the autonomous vehicle (Paragraph [0007], "The method also comprises configuring a tire model, where the tire model defines a relationship between wheel slip and generated wheel force and where the tire model is parameterized by the one or more tire parameters, and controlling the motion of the heavy-duty vehicle based on the relationship between wheel slip and generated wheel force. This way the vehicle control can be based on an accurate and up to date tire model which better reflects the current properties of the tire.").
However Laine does not explicitly teach select a characteristic curve associated with the road friction coefficient, the characteristic curve between a lateral force of the vehicle and a slip angle of a wheel of the vehicle.
Shiozawa teaches road surface friction coefficient estimating device includes a lateral force detecting section for detecting the lateral force of a wheel during traveling including
select a characteristic curve associated with the road friction coefficient, the characteristic curve between a lateral force of the vehicle and a slip angle of a wheel of the vehicle (Paragraph [0006], “a road surface friction coefficient estimating section that: stores information about a characteristic curve in a coordinate plane, wherein the coordinate plane has a coordinate axis representing the lateral force and a coordinate axis representing the slip angle, and wherein the characteristic curve represents a relationship between the lateral force and the slip angle under condition of a reference road surface friction coefficient”) (Paragraph [0057], “The tire characteristic curve under condition of the reference road surface which forms the characteristic map is obtained beforehand, for example, by a running test of the vehicle.”) (Paragraph [0058], “Road surface .mu. calculating section 3 calculates an estimated value of the road surface .mu. of the actual traveled road surface on the basis of the thus-obtained characteristic map of the tire characteristic curve under condition of the reference road surface.”).
Laine and Shiozawa are analogous art as they are both generally related to controlling vehicles based on tire and road characteristics.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include select a characteristic curve associated with the road friction coefficient, the characteristic curve between a lateral force of the vehicle and a slip angle of a wheel of the vehicle of Shiozawa in the system for controlling a vehicle of Laine with a reasonable expectation of success in order to prevent the occurrence of a loss of braking or driving force due to slippage (Paragraph [0116], “This makes it possible to calculate on the basis of the ratio between the lateral force and slip angle the actual road surface .mu. of the traveled road surface, if the lateral force and slip angle can be detected. Accordingly, it is possible to estimate the road surface .mu. of the traveled road surface before the occurrence of slippage. This makes it possible to suitably control the steering assist torque of the vehicle according to the road surface .mu. of the traveled road surface. As a result, it is possible to prevent the occurrence of a loss in braking/driving force due to slippage, and prevent spinning and drifting-out, while the vehicle is turning.”).
However the combination does not explicitly teach determine a wheel stiffness for the wheel for the normal force from a slope of the characteristic curve associated with the road friction coefficient at the slip angle.
Berntorp teaches systems for controlling a vehicle using a friction function describing a friction between a type of surface of the road and a tire of the vehicle as a function of a slip of a wheel of the vehicle including
determine a wheel stiffness for the wheel for the normal force from a slope of the characteristic curve associated with the road friction coefficient at the slip angle (Paragraph [0021], “Linear parameters include a value of an initial slope of the friction function defining a stiffness of the tire for each wheel.”) (Paragraph [0034], “controlling a vehicle moving on a road, wherein the method uses a processor coupled to a memory storing parameters of multiple friction functions, each friction function describes a friction between a type of surface of the road and a tire of the vehicle as a function of a slip of a wheel of the vehicle, the parameters of each friction function include an initial slope of the friction function defining a stiffness of the tire and one or combination of a peak friction, a shape factor and a curvature factor of the friction function”).
Laine, Shiozawa and Berntorp are analogous art as they are both generally related to controlling vehicles based on tire and road characteristics.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include determine a wheel stiffness for the wheel for the normal force from a slope of the characteristic curve associated with the road friction coefficient at the slip angle of Berntorp in the system for controlling a vehicle of Laine and Shiozawa with a reasonable expectation of success in order to improve the accuracy and safety of the vehicle control by to rapidly estimate vehicle and road characteristics while driving (Paragraph [0016], “In contrast, the aggressive driving changes the friction function rapidly and non-linearly. Hence, controlling the vehicle using values of the linear part of the friction function can jeopardize accuracy and safety of vehicle control. In addition, non-linear variations of the friction function during the aggressive driving and relatively short time when a vehicle is driven under a specific style of the aggressive driving make the learning of the non-linear part of the friction function impractical. Hence, there is still a need for a method that can rapidly estimate non-linear part of the friction function during a real-time control of the vehicle.”).
Regarding claim 16, claim 16 is similar in scope to claim 2, and therefore is rejected under similar rationale.
Regarding claim 19, claim 19 is similar in scope to claim 5, and therefore is rejected under similar rationale.
Regarding claim 20, claim 20 is similar in scope to claim 6, and therefore is rejected under similar rationale.
Claim 3-4, 10-11, and 17-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Laine (US-20240182041) in view of Shiozawa (US-20110106458) further in view of Berntorp (US-20200290625) and further in view of Li (CN-108099902).
Regarding claim 3, the combination of Laine, Shiozawa, and Berntrop teaches the method as discussed above in claim 1, Laine further teaches using a look up table to perform calculations such as wheel stiffness (Paragraph [0065], "The tire model may, as mention above, be implemented as a look-up table or other type of function. The tire model is parameterized, i.e., defined, by one or more tire parameters. This means that the function itself varies in dependence of the tire properties. The tire model can be used to model various relationships, as exemplified above, such as a relationship or mapping between wheel slip and generated wheel force, and/or a mapping between tire wear rate and vehicle state such as tire normal load, vehicle speed, and wheel slip.").
However Laine does not explicitly teach further comprising calculating the wheel stiffness by calculating a derivative from values in a lateral force table for the wheel.
Li teaches a yaw stability control method using a vehicle model for outputting the actual motion state information of vehicle, comprising a vehicle longitudinal speed, yaw rate, sideslip angle and tire-road friction coefficient including
further comprising calculating the wheel stiffness by calculating a derivative from values in a lateral force table for the wheel (Paragraph [0024], “obtain the relationship curves between the front tire lateral force and the front tire slip angle under different road adhesion coefficients, resulting in a three-dimensional diagram of the front tire slip characteristics; obtain the relationship curves between the derivative of the front tire lateral force and the front tire slip angle under different road adhesion coefficients, resulting in a three-dimensional diagram of the front tire lateral stiffness characteristics,” here the system is calculating a derivative using force values this derivative results in a stiffness diagram, while Li is not explicitly teaching storing these values in a table, Laine teaches the use of the table and the method of calculating a derivative could reasonably be applied to the table of values of Laine).
Laine and Li are analogous art as they are both generally related to controlling vehicles based on tire and road characteristics.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include calculating the wheel stiffness by calculating a derivative from values in a lateral force table for the wheel of Li in the system for controlling a vehicle of Laine with a reasonable expectation of success in order to reduce the computational burden of the system and improve the yaw stability of the vehicle (Paragraph [0077], “The beneficial effects of this invention are: This method uses a linear time-varying approach to transform the nonlinear predictive control problem into a linear predictive control problem, making full use of the nonlinear tire yaw characteristics, reducing the computational burden of the system, improving the yaw stability of the vehicle, and expanding the yaw stability control domain of the vehicle; The two predictive models used in this method share a single predictive control algorithm, simplifying the design of the controller.”).
Regarding claim 4, the combination of Laine, Shiozawa, and Berntrop teaches the method as discussed above in claim 1, however Laine does not explicitly teach calculating a system dynamics matrix for the vehicle using the wheel stiffness and optimizing the system dynamics matrix to generate the control input.
Li further teaches calculating a system dynamics matrix for the vehicle using the wheel stiffness and optimizing the system dynamics matrix to generate the control input (Paragraph [XXXX], “the formula (10), state space equation for designing prediction equations, specifically as follows: wherein, the state variable x is a yaw rate of the vehicle; the control input u is the additional steering angle of front wheel, system interference input d is a sideslip angle of the vehicle, in the formula state matrix A2, the input matrix Bu2, interference input matrix Bd2 is as follows: step 3.1.3, designing prediction switching door condition of the model A and B prediction model, current tire side deviation rigidity value is greater than zero, the MPC controller uses the prediction model A, current tire side deviation rigidity value is less than zero. MPC controller uses a prediction model B in each control period, the tire lateral force and the side deflecting rigidity processor are updated once the front wheel tire lateral force and the side deflecting rigidity data and output to the MPC controller, an MPC controller selecting a prediction model according to the side deflecting rigidity. optimizing and solving the front wheel of the next moment, additional steering angle,” here the system is calculating dynamics matrixes for the vehicle including using wheel stiffness in order to optimize and solve for control inputs for each wheel, see also formulas and matrices on page 4 of the reference).
Laine and Li are analogous art as they are both generally related to controlling vehicles based on tire and road characteristics.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include calculating a system dynamics matrix for the vehicle using the wheel stiffness and optimizing the system dynamics matrix to generate the control input of Li in the system for controlling a vehicle of Laine with a reasonable expectation of success in order to reduce the computational burden of the system and improve the yaw stability of the vehicle (Paragraph [0077], “The beneficial effects of this invention are: This method uses a linear time-varying approach to transform the nonlinear predictive control problem into a linear predictive control problem, making full use of the nonlinear tire yaw characteristics, reducing the computational burden of the system, improving the yaw stability of the vehicle, and expanding the yaw stability control domain of the vehicle; The two predictive models used in this method share a single predictive control algorithm, simplifying the design of the controller.”).
Regarding claim 10, claim 10 is similar in scope to claim 3, and therefore is rejected under similar rationale.
Regarding claim 11, claim 11 is similar in scope to claim 4, and therefore is rejected under similar rationale.
Regarding claim 17, claim 17 is similar in scope to claim 3, and therefore is rejected under similar rationale.
Regarding claim 18, claim 18 is similar in scope to claim 4, and therefore is rejected under similar rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Desai (US-20250242817) teaches systems and methods are provided for operation of a vehicle to prevent the vehicle from entering unsafe driving states using a tire slip angle, a lateral force and the friction between the tires and the roadway. Rydstrom (US-20250026325) teaches a control unit for controlling a heavy-duty vehicle is arranged to obtain an initial inverse tire model configured to represent a preliminary relationship between wheel slip and generated longitudinal wheel force for at least one wheel of the heavy-duty vehicle. Hassel (US-11318947) teaches systems and methods for estimating surface friction coefficients using lateral force excitations of one or more rear wheels of a rear wheel steering vehicle.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER FEES whose telephone number is (303)297-4343. The examiner can normally be reached Monday-Thursday 7:30 - 5:30 MT.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Aniss Chad can be reached at (571) 270-3832. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/CHRISTOPHER GEORGE FEES/Primary Examiner, Art Unit 3662
Prosecution Insights