DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This action is reply to the Application Number 17/787,679 filed on 05/29/2026.
Claims 1, 7, 9, 10 and 24 – 49 are currently pending and have been examined. Claims 1, 24 and 26 have been amended. Claims 43 – 49 are new.
This action is made FINAL.
Information Disclosure Statement
The information disclosure statements filed 05/29/2026 have been received and considered.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 9, 10, 24 – 30 are rejected under 35 U.S.C. 103 as being unpatentable over Aikin et al. (US 20180079272 A1) further in view of Nauderer et al. (DE102015202405A1).
Regarding claim 1, Aikin teaches a method comprising:
obtaining information associated with a road-profile of an upcoming travel surface ahead of a vehicle; (Aikin: Abstract: “A method includes receiving, at a control system of a vehicle, a road profile for a road at a particular location, the road profile indicating a road condition of the road at the particular location. The method also includes determining that the vehicle is approaching the road at the particular location.”)
based on the information, before traversing the upcoming travel surface, (Aikin: Paragraph 0006: “a method to minimize motion of a vehicle is disclosed. The method includes receiving, at a control system of a vehicle, a road profile for a road at a particular location, the road profile indicating a road condition of the road at the particular location. The method also includes determining that the vehicle is approaching the road at the particular location. The method further includes adjusting an active suspension system of the vehicle in response to a determination that the vehicle is approaching the road at the particular location.”; Paragraph 0041: “ In some embodiments, the control system 312 may prepare for the road hazard 342 by reading data from the road profile 314 that may indicate previous adjustments to the active suspension system of the vehicle 310. For example, the road profile 314 may indicate that in a previous drive over the road hazard 342 that the vehicle 310 was raised a particular height to minimize vertical motion of the vehicle 310. The road profile 314 may indicate a particular location corresponding to the road hazard 342 such that the control system 312 may anticipate the road hazard 342 prior to the road hazard 342 entering the field of view 320 of the one or more sensors 316.”; Paragraphs 0051 – 0052: “The profile library 450 may be configured to receive and refine suspension adjustment profiles or force profiles in addition to or instead of the road profile. The vehicle 402 may be configured to send a suspension adjustment profile to the profile library 450 via the network 440 using the one or more communication interfaces 406. The suspension adjustment profile may include information identifying a type of vehicle, a particular location and one or more particular adjustments, as described herein. The profile library 450 may store the suspension adjustment profile to the profile database 454. The profile library 450 may aggregate multiple suspension adjustment profiles from multiple vehicles, including the vehicle 402, in the profile database 454. The vehicle 402 may request a suspension adjustment profile corresponding to a particular road segment from the profile library 450, such as when the vehicle 402 has not traveled over the particular road segment. The profile library 450 may send the suspension adjustment profile from the profile database 454 to the vehicle 402 via the network 440 using the one or more communication interfaces 452. In some embodiments, the profile library 450 may restrict the vehicle 402 from receiving the suspension adjustment profile from a particular vehicle make or model when the vehicle 402 has a different vehicle make or model. In other embodiments, the profile library 450 may send the suspension adjustment profile, and the vehicle 402 may be configured to modify the suspension adjustment profile based on known differences between the make or model of the vehicle 402 and a different make or model associated with the received suspension adjustment profile.”,
Supplemental Note: a road profile is saved in a profile library and can be received by the control system of the vehicle, therefore interpreted as gathering the profile before traversing the roadway)
… implementing the selected trajectory when the vehicle traverses the upcoming travel surface (Aikin: Paragraph 0006: “a method to minimize motion of a vehicle is disclosed. The method includes receiving, at a control system of a vehicle, a road profile for a road at a particular location, the road profile indicating a road condition of the road at the particular location. The method also includes determining that the vehicle is approaching the road at the particular location. The method further includes adjusting an active suspension system of the vehicle in response to a determination that the vehicle is approaching the road at the particular location.”; Paragraph 0041: “ In some embodiments, the control system 312 may prepare for the road hazard 342 by reading data from the road profile 314 that may indicate previous adjustments to the active suspension system of the vehicle 310. For example, the road profile 314 may indicate that in a previous drive over the road hazard 342 that the vehicle 310 was raised a particular height to minimize vertical motion of the vehicle 310. The road profile 314 may indicate a particular location corresponding to the road hazard 342 such that the control system 312 may anticipate the road hazard 342 prior to the road hazard 342 entering the field of view 320 of the one or more sensors 316.”; Paragraphs 0051 – 0052: “The profile library 450 may be configured to receive and refine suspension adjustment profiles or force profiles in addition to or instead of the road profile. The vehicle 402 may be configured to send a suspension adjustment profile to the profile library 450 via the network 440 using the one or more communication interfaces 406. The suspension adjustment profile may include information identifying a type of vehicle, a particular location and one or more particular adjustments, as described herein. The profile library 450 may store the suspension adjustment profile to the profile database 454. The profile library 450 may aggregate multiple suspension adjustment profiles from multiple vehicles, including the vehicle 402, in the profile database 454. The vehicle 402 may request a suspension adjustment profile corresponding to a particular road segment from the profile library 450, such as when the vehicle 402 has not traveled over the particular road segment. The profile library 450 may send the suspension adjustment profile from the profile database 454 to the vehicle 402 via the network 440 using the one or more communication interfaces 452. In some embodiments, the profile library 450 may restrict the vehicle 402 from receiving the suspension adjustment profile from a particular vehicle make or model when the vehicle 402 has a different vehicle make or model. In other embodiments, the profile library 450 may send the suspension adjustment profile, and the vehicle 402 may be configured to modify the suspension adjustment profile based on known differences between the make or model of the vehicle 402 and a different make or model associated with the received suspension adjustment profile.”; Paragraph 0034: “In some embodiments, the road profile may be used to generate or determine a suspension adjustment profile that may be used by the control system 112 to adjust the suspension actuators 130A-B. The suspension adjustment profile may also be referred to as a force profile.”,
Supplemental Note: a road profile is saved in a profile library and can be received by the control system of the vehicle, therefore interpreted as gathering the profile before traversing the roadway).
In sum, Aikin teaches a method comprising: obtaining information associated with a road-profile of an upcoming travel surface ahead of a vehicle; based on the information, before traversing the upcoming travel surface, implementing the selected trajectory when the vehicle traverses the upcoming travel surface. Aikin however does not fully teach selecting a trajectory to minimize a negative effect of the road- profile on the vehicle, wherein the selecting comprises identifying a filter-frequency parameter of a filter to be applied during a traversal of the upcoming travel surface by a proactive controller to the information.
Nauderer teaches selecting a trajectory to minimize a negative effect of the road- profile on the vehicle, wherein the selecting comprises identifying a filter-frequency parameter of a filter to be applied during a traversal of the upcoming travel surface by a proactive controller to the information; and (Nauderer: Paragraph 0003: “The obtained road profile is typically filtered with a bandpass filter to isolate unevenness in the road surface that stimulates the body of the vehicle. Such irregularities lie in the frequency range from 0.5 Hz to approx. 2 Hz.”; Paragraph 0004: “In particular, high-frequency components in a frequency range of approx. 5 Hz to approx. 15 Hz largely eliminated from the road profile. Irregularities in this frequency range typically cause wheel vibrations. The high-frequency components of the road profile can cause a damper in the chassis to tremble or vibrate, particularly in active chassis”; Paragraph 0018: “The plurality of locations of the driving profile then corresponds, depending on the driving speed, to a plurality of points in time at which the vehicle reaches the corresponding plurality of locations.”; Paragraph 0033: “The suspension and/or damping of the wheel block 103 relative to the vehicle block 101 by the suspension and/or by the shock absorber is represented in Fig. 1a by the chassis unit 102. The chassis unit 102 includes suspension and/or damping properties that can be changed by selecting different driving modes (comfort mode, sport mode). A setting of the chassis unit 102 can be changed according to the method described in this document and adapted in a predictive manner to a profile of the roadway 120”).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention disclosed by Aikin with the teachings of Nauderer with a reasonable expectation of success. Aikin and Nauderer both teach a vehicle system able to acquire roadway surface data to be used to adjust the suspension of a vehicle for a smooth ride. One of ordinary skill in the art would find it obvious to try to implement the filter frequencies of the road profile with a bandpass filter as taught by Nauderer with the vehicle of Aikin as applying a bandpass filter aids in isolating the unevenness of the roadway applied to the body of the vehicle. This combination is proper as Aikin teaches the ability to generate a force profile based on the acquired road profile which is used to minimize the frequency response on the roadway surface, thus the ability to filter the frequencies of the road profile as taught by Nauderer would be obvious to try in generating a more effective force profile of Aikin. Both the filtering of the frequencies and the force profile taught by Aikin and Nauderer are used to adjust the suspension system of their respective vehicles to minimize the vibrations of the vehicle over the road surface. This information can be applied to calculate how much suspension force to apply when an a roadway surface is isolated per the filter.
Regarding claim 9, Aikin, as modified, teaches further comprising at least one component of a system of the vehicle based on at least one setpoint, wherein the at least one setpoint is based on at least one of frequency, gain, or calibration factor (Aikin: Paragraph 0028: “The suspension position 190 may be adjusted for each of the suspension actuators 130A-B. As referred to herein, low-frequency refers to a frequency which is less than the primary ride frequency, and high-frequency refers to a frequency which is at least equal to (i.e., greater than or equal to) the primary ride frequency, where the primary ride frequency refers to a natural frequency of the sprung mass.”).
Regarding claim 10, Aikin, as modified, teaches at least one computer readable storage medium having encoded thereon executable instructions that, when executed by at least one controller, cause the at least one controller to carry out the method of claim 1 (Aikin: Paragraph 0008: “a computer-readable storage medium is disclosed. The computer-readable storage medium stores instructions that, when executed by one or more processors, cause the one or more processors to perform operations. The operations include receiving a road profile indicating a road condition at a particular location. The operations also include receiving, from one or more sensors of a vehicle, a road input based on a current road condition at the particular location. The operations further include updating the road profile based at least in part on the road input.”; Paragraph 0006: “The method includes receiving, at a control system of a vehicle, a road profile for a road at a particular location, the road profile indicating a road condition of the road at the particular location. The method also includes determining that the vehicle is approaching the road at the particular location. The method further includes adjusting an active suspension system of the vehicle in response to a determination that the vehicle is approaching the road at the particular location.”,
Supplementary Note: a control system of a vehicle stores the instructions to perform the tasks stated for claim 1).
Regarding claim 24, Aikin, as modified, teaches wherein the selected trajectory increases a comfort of a vehicle occupant (Aikin: Paragraph 0003: “Comfort of a passenger in a vehicle is generally managed with passive hardware elements, such as seats, dampers, bushing, springs, jounce bumpers, etc. The passive hardware elements are configured to attenuate lateral, longitudinal or vertical accelerations resulting from the vehicle driving over a road.”; Paragraph 0025: “The control system 112 may be communicatively coupled to the internal sensors 116 and the external sensors 114 via communication links 111. In some embodiments, the control elements may include suspension actuators 130A-B of an active suspension system that is configured to reduce movement of the sprung mass 110 (e.g., a body of the vehicle or a vehicle interior) during operation of the vehicle 100. Accordingly, the control system 112 may control the suspension actuators 130A-B based at least in part on the data received from the external sensors 114, the internal sensors 116, or both.”,
Supplemental Note: the prior art teaches the ability of the suspension to adjust per the roadway profile).
Regarding claim 25, Aikin, as modified, teaches wherein minimizing negative effects increases the comfort of the vehicle occupant (Aikin: Paragraph 0003: “Comfort of a passenger in a vehicle is generally managed with passive hardware elements, such as seats, dampers, bushing, springs, jounce bumpers, etc. The passive hardware elements are configured to attenuate lateral, longitudinal or vertical accelerations resulting from the vehicle driving over a road.”; Paragraph 0025: “The control system 112 may be communicatively coupled to the internal sensors 116 and the external sensors 114 via communication links 111. In some embodiments, the control elements may include suspension actuators 130A-B of an active suspension system that is configured to reduce movement of the sprung mass 110 (e.g., a body of the vehicle or a vehicle interior) during operation of the vehicle 100. Accordingly, the control system 112 may control the suspension actuators 130A-B based at least in part on the data received from the external sensors 114, the internal sensors 116, or both.”,
Supplemental Note: the suspension of a vehicle provides comfort to the passengers. The prior art teaches the adjustments of the suspension to increase the comfort of the passengers in the vehicle).
Regarding claim 26, Aikin, as modified, teaches wherein the selected trajectory causes a suspension of the vehicle to start moving a body of the vehicle before traversing an event associated with the road-profile (Aikin: Paragraph 0041: “the control system 312 may anticipate the road hazard 342 prior to the road hazard 342 entering the field of view 320 of the one or more sensors 316. In another example, the road profile 314 may indicate that the road hazard 342 is limited to a particular portion of the road 340. The control system 312 may be configured to adjust only portions of the active suspension system based on the particular portion of the road 340 relative to the vehicle 310. For example, the road hazard 342 may be a small pothole on a passenger side of the vehicle 310. Based on the road profile 314 indicating the size and location of the road hazard 342, the control system 312 may adjust only portions of the active suspension system corresponding to the passenger side of the vehicle 310.”,
Supplemental Note: the road profile states data of a pothole, which a vehicle with this suspension system as it anticipates the pothole and only adjusts the active suspension for that particular portion).
Regarding claim 27, Aikin, as modified, teaches wherein the event is a disturbance associated with the road-profile that causes the vehicle to violate one or more constraints (Aikin: Paragraph 0041: “the control system 312 may anticipate the road hazard 342 prior to the road hazard 342 entering the field of view 320 of the one or more sensors 316. In another example, the road profile 314 may indicate that the road hazard 342 is limited to a particular portion of the road 340. The control system 312 may be configured to adjust only portions of the active suspension system based on the particular portion of the road 340 relative to the vehicle 310. For example, the road hazard 342 may be a small pothole on a passenger side of the vehicle 310. Based on the road profile 314 indicating the size and location of the road hazard 342, the control system 312 may adjust only portions of the active suspension system corresponding to the passenger side of the vehicle 310.”,
Supplemental Note: in this example, a pothole is a constraint event).
Regarding claim 28, Aikin, as modified, does not teach wherein the selecting comprises applying a zero-phase filter to the information.
Nauderer teaches wherein the selecting comprises applying a zero-phase filter to the information (Nauderer: Paragraph 0032: “Fig. 1a shows an exemplary vertical dynamics model of a vehicle 100. The vehicle travels in a horizontal direction 111 (i.e. along an x-axis 151) over the roadway 120. The road surface 120 has unevennesses 121, which cause movements of the vehicle 100 in the vertical direction 112 (i.e. perpendicular to the road surface 120 or along a z-axis 152). The vehicle 100 typically includes devices 102, 104 (e.g. suspension/damping units) to cushion and/or dampen the impulses in the vertical direction 112 caused by the bumps 121.”; Paragraph 0047: “The road profile 301 has different amplitudes of vertical deflections on the z-axis 152 at different locations on the x-axis 151. The amplitudes of the vertical deflections of the road profile 301 can be evaluated via threshold values S1 311 and S2 312 (in positive direction) and S3 321 and S4 322 (in negative direction). The threshold values 311, 312, 321, 322 can be parameterized. In particular, the amplitudes of the vertical deflections can be divided into ranges, e.g. B. in the following areas: • Range I: S3 < amplitude < S1; • Range II: S1 < amplitude < S2 or S4 < amplitude < S3; • Range III: Amplitude > S2 or amplitude < S4.”,
Supplemental Note: based on the deflections of the roadway as captured on the roadway profile, the suspension system analyzes the correct force to alleviate the bumps. This is interpreted as zero-phase filtering as the suspension systems are acting as an opposite force to the acquired roadway profile. Please see Figures A and B).
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Figure A: Nauderer: Fig. 1A
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Figure B: Nauderer: Fig. 3a
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention disclosed by Aikin with the teachings of Nauderer with a reasonable expectation of success. As discussed in claim 1, Aikin and Nauderer both teach a vehicle system able to acquire roadway surface data to be used to adjust the suspension of a vehicle for a smooth ride. One of ordinary skill in the art would find it obvious to try to implement the filter frequencies of the road profile with a bandpass filter as taught by Nauderer with the vehicle of Aikin as applying a bandpass filter aids in isolating the unevenness of the roadway applied to the body of the vehicle. This information can be applied to calculate how much suspension force, a opposite force to apply to cancel an uneven road surface (i.e. potholes, rutting, etc.), when an a roadway surface is isolated per the filter.
Regarding claim 29, Aikin, as modified, teaches wherein the information is obtained from one or more data stores of travel surface information (Aikin: Paragraph 0049: “the vehicle 402 may acquire or download the road profile from the profile library 450 that includes aggregated road profiles from a plurality of other vehicles.”).
Regarding claim 30, Aikin, as modified, teaches wherein the one or more data stores are based on data from a crowd-sourced road mapping system (Aikin: Paragraph 0049: “the vehicle 402 may acquire or download the road profile from the profile library 450 that includes aggregated road profiles from a plurality of other vehicles.”).
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Aikin et al. (US 20180079272 A1) in view of Nauderer et al. (DE102015202405A1) as applied to claim 1 above, and further in view of Munzinger et al. (US 20170138752 A1).
Regarding claim 7, Aikin, as modified, does not teach wherein the information comprises a topography of a road surface.
Munzinger teaches wherein the information comprises a topography of a road surface (Munzinger: Abstract: “A system for updating location-based data available to a network of user includes a network of users connected to a server; a database comprising location-based information on the server accessible to the network of users, the location-based information including global positioning system (GPS) coordinates of environmental conditions including traffic conditions, topographical information, weather information, road surface condition information, roadside object information, on-road object information, and combinations thereof;”).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention disclosed by Aikin with the teachings of Munzinger with a reasonable expectation of success. Aikin teaches the ability to gather a roadway profile of the roadway surface, one with knowledge in the art would find the ability to acquire a topography of the road surface as taught by Munzinger to be obvious to try to combine with the vehicle of Aikin. Aikin teaches: (Paragraph 0030: “The road profile may be used by the control system 112 to adjust the control elements. In a particular embodiment, the road profile may indicate to the control system 112 that the vehicle is approaching a particular road condition in the surface 140 (e.g., a pothole) that was previously determined and stored to the road profile. Based on information from the road profile, the control system 112 may adjust the control elements proactively in anticipation of the pothole. For example, the control system 112 may cause the control elements to adjust only a driver-side set of suspension actuators 130A-B in response to the pothole being on the driver-side of the surface 140. In some embodiments, the road profile may serve as a map of commonly traveled routes and corresponding road conditions. In other embodiments, the road profile may indicate a road type at the particular location. The control system 112 may adjust the control elements based on the road type. For example, the road profile may indicate that the road type of the surface 140 at the particular location as being a part of a highway.“) , thus already teaching the ability of the road profile to serve as a map of routes and roadway conditions. The addition of topography information allows the vehicle to have elevations of all parts of the roadway, therefore more effectively able to control its suspension system for a smoother ride than it currently stands.
Claims 31 – 39, 41 and 42 are rejected under 35 U.S.C. 103 as being unpatentable over Aikin et al. (US 20180079272 A1) in view of Nauderer et al. (DE102015202405A1) and further in view of Kobilarov et al. (US 10671075 B1).
Regarding claim 31, Aikin teaches a method for minimizing a negative effect of travel with a vehicle along an upcoming path of travel on a road, the method comprising: (Aikin: Paragraph 0006: “In one embodiment, a method to minimize motion of a vehicle is disclosed. The method includes receiving, at a control system of a vehicle, a road profile for a road at a particular location, the road profile indicating a road condition of the road at the particular location. The method also includes determining that the vehicle is approaching the road at the particular location. The method further includes adjusting an active suspension system of the vehicle in response to a determination that the vehicle is approaching the road at the particular location.”)
obtaining road-profile data for the path of travel (Aikin: Abstract: “A method includes receiving, at a control system of a vehicle, a road profile for a road at a particular location, the road profile indicating a road condition of the road at the particular location. The method also includes determining that the vehicle is approaching the road at the particular location.”)
before traveling along the path, planning at least two candidate trajectories of vehicle-body motion along the path, wherein, for each of the at least two candidate trajectories, the planning comprises generating that trajectory (Aikin: Paragraphs 0051 – 0052: “The profile library 450 may be configured to receive and refine suspension adjustment profiles or force profiles in addition to or instead of the road profile. The vehicle 402 may be configured to send a suspension adjustment profile to the profile library 450 via the network 440 using the one or more communication interfaces 406. The suspension adjustment profile may include information identifying a type of vehicle, a particular location and one or more particular adjustments, as described herein. The profile library 450 may store the suspension adjustment profile to the profile database 454. The profile library 450 may aggregate multiple suspension adjustment profiles from multiple vehicles, including the vehicle 402, in the profile database 454. The vehicle 402 may request a suspension adjustment profile corresponding to a particular road segment from the profile library 450, such as when the vehicle 402 has not traveled over the particular road segment. The profile library 450 may send the suspension adjustment profile from the profile database 454 to the vehicle 402 via the network 440 using the one or more communication interfaces 452. In some embodiments, the profile library 450 may restrict the vehicle 402 from receiving the suspension adjustment profile from a particular vehicle make or model when the vehicle 402 has a different vehicle make or model. In other embodiments, the profile library 450 may send the suspension adjustment profile, and the vehicle 402 may be configured to modify the suspension adjustment profile based on known differences between the make or model of the vehicle 402 and a different make or model associated with the received suspension adjustment profile.”,
Supplemental Note: multiple profiles can be made for the same roadway section)
… while traveling along the path, operating a suspension system of the vehicle to implement the selected trajectory of vehicle-body motion (Aikin: Paragraph 0034: “In some embodiments, the road profile may be used to generate or determine a suspension adjustment profile that may be used by the control system 112 to adjust the suspension actuators 130A-B. The suspension adjustment profile may also be referred to as a force profile. For example, the suspension adjustment profile may cause the control system 112 to increase actuation of the suspension actuator 130A and decrease actuation of the suspension actuator 130B based on a road hazard (e.g., a pothole) or road configuration (e.g., a turn in the road). In some embodiments, the suspension adjustment profile may correlate or associate a particular force adjustment with particular high-bandwidth accelerations of the unsprung mass 120 and a particular location indicated by the road profile. The force adjustment may indicate that a force is to be applied to a particular control element, such as a suspension actuator or a wheel assembly, to minimize the high-bandwidth accelerations applied to the vehicle 100. For example, the vehicle 100 may have a wheel assembly that is controlled based on the force profile such that movement of the wheel assembly is not controlled by the driver. In some embodiments, the vehicle 100 may be location-aware by the external sensors 114, such as a global positioning system (GPS) providing location data to the vehicle 100. Based on location and the force profile, the control system 112 may cause one or more forces to be applied to the suspension actuators 130A-B or the wheel assemblies 122A-B.”,
Supplemental Note: the received road profile can be used to improve the suspension of the vehicle. Location aware data from external sensors are also used to improve the force profile of the suspension from the received road profile. The trajectory is interpreted as the suspension as it adjusts the vehicle vertical trajectory as they traverse the road profile).
In sum, Aikin teaches A method for minimizing a negative effect of travel with a vehicle along an upcoming path of travel on a road, the method comprising: obtaining road-profile data for the path of travel before traveling along the path, planning at least two candidate trajectories of vehicle-body motion along the path, wherein, for each of the at least two candidate trajectories, the planning comprises generating that trajectory while traveling along the path, operating a suspension system of the vehicle to implement the selected trajectory of vehicle-body motion. Aikin however does not teach filtering the road-profile data with a filter having a distinct filter-frequency parameter.
Nauderer teaches by filtering the road-profile data with a filter having a distinct filter-frequency parameter; (Nauderer: Paragraph 0003: “The obtained road profile is typically filtered with a bandpass filter to isolate unevenness in the road surface that stimulates the body of the vehicle. Such irregularities lie in the frequency range from 0.5 Hz to approx. 2 Hz.”; Paragraph 0004: “In particular, high-frequency components in a frequency range of approx. 5 Hz to approx. 15 Hz largely eliminated from the road profile. Irregularities in this frequency range typically cause wheel vibrations. The high-frequency components of the road profile can cause a damper in the chassis to tremble or vibrate, particularly in active chassis”).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention disclosed by Aikin with the teachings of Nauderer with a reasonable expectation of success. Please refer to claim 1 as both state the same function and therefore rejected under the same pretenses. Aikin in view of Nauderer however still do not teach from among the at least two candidate trajectories, selecting a trajectory that minimizes the negative effect of traveling along the path.
Kobilarov teaches from among the at least two candidate trajectories, selecting a trajectory that minimizes the negative effect of traveling along the path; and (Kobilarov: Col. 18, lines 9 – 27: “At operation 702, the process can include receiving a candidate trajectory. In some instances, the candidate trajectory received in the operation 702 can include an optimized trajectory that is to be implemented by components of an autonomous vehicle. For example, the candidate trajectory of the operation 702 may have been selected as an action to be performed and optimized to minimize one or more costs while respecting motion dynamics, safety, performance, mission requirements, and the like. In some instances, the candidate trajectory can be received by the decision planner component 512, the trajectory tracker component 514, and/or the execution component 516. In some instances, the operation 702 can include simulating the vehicle dynamics with respect to the candidate trajectory and/or simulating various fallback or stopping operations with respect to the candidate trajectory or obstacles that may be present in an environment with respect to the candidate trajectory.”; Col. 17, lines 57 – 67 :“At operation 610, the process can include outputting the candidate trajectory. In some instances, the candidate trajectory can be output to another selection step whereby a candidate trajectory can be selected from a plurality of optimized candidate trajectories corresponding to various actions (e.g., optimal trajectories for merging left, merging right, stopping, continuing straight, etc.). In some instances, the candidate trajectory can be output to the trajectory tracker component 514 and/or the execution component 516 to control an autonomous vehicle to follow the candidate trajectory.”).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention disclosed by Aikin with the teachings of Kobilarov with a reasonable expectation of success. Aikin and Kobilarov both teach gathering roadway information and adjusting its vehicle components to increase the comfort of the user while traversing that section. Kobilarov further teaches the ability to select a candidate trajectory for a vehicle to from multiple optimized trajectories. One with knowledge in the art would find this obvious to try to implement with the vehicle of Aikin to increase the comfort for the passenger. Aikin teaches storing roadway profiles in an online database which can be acquired by any vehicle also planning to traverse that section (Aikin: Paragraphs 0051 – 0052). The profiles however may not fully match the vehicle therefore the selected profile may not be the most effective. The ability to compare the different profiles would allow the ability to select the best profile for the vehicle that has the highest user comfort.
Regarding claim 32, Aikin, as modified, does not teach wherein selecting the trajectory comprises comparing at least two of the at least two candidate trajectories generated by filtering the road-profile data.
Kobilarov teaches wherein selecting the trajectory comprises comparing at least two of the at least two candidate trajectories generated by filtering the road-profile data (Kobilarov: Col. 18, lines 9 – 27: “At operation 702, the process can include receiving a candidate trajectory. In some instances, the candidate trajectory received in the operation 702 can include an optimized trajectory that is to be implemented by components of an autonomous vehicle. For example, the candidate trajectory of the operation 702 may have been selected as an action to be performed and optimized to minimize one or more costs while respecting motion dynamics, safety, performance, mission requirements, and the like. In some instances, the candidate trajectory can be received by the decision planner component 512, the trajectory tracker component 514, and/or the execution component 516. In some instances, the operation 702 can include simulating the vehicle dynamics with respect to the candidate trajectory and/or simulating various fallback or stopping operations with respect to the candidate trajectory or obstacles that may be present in an environment with respect to the candidate trajectory.”; Col. 17, lines 57 – 67 :“At operation 610, the process can include outputting the candidate trajectory. In some instances, the candidate trajectory can be output to another selection step whereby a candidate trajectory can be selected from a plurality of optimized candidate trajectories corresponding to various actions (e.g., optimal trajectories for merging left, merging right, stopping, continuing straight, etc.). In some instances, the candidate trajectory can be output to the trajectory tracker component 514 and/or the execution component 516 to control an autonomous vehicle to follow the candidate trajectory.”).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention disclosed by Aikin with the teachings of Kobilarov with a reasonable expectation of success. Please refer to claim 1 as both state the same function and therefore rejected under the same pretenses. Aikin in view of Kobilarov however still do not teach filtering with filters having distinct filter-frequency parameters.
Nauderer teaches with filters having distinct filter-frequency parameters (Nauderer: Paragraph 0002: “The elevation profile data can e.g. For example, the course of the road ahead in the vertical direction at a given point in time can be described as a sequence of points in the longitudinal and vertical directions. The height profile data from each bump sensor can be overlaid to determine a road profile relative to a contact point of the vehicle's tires.”; Paragraph 0003: “The obtained road profile is typically filtered with a bandpass filter to isolate unevenness in the road surface that stimulates the body of the vehicle. Such irregularities lie in the frequency range from 0.5 Hz to approx. 2 Hz For low-pass filtering of the road profile, for example, For example, a “moving average” method can be used, which leads to a smoothing of the road profile. In the “moving average” method, average values are calculated over a section of the road profile. The window used is moved overlapping over the course of the road profile.”; Paragraph 0064: “Furthermore, the described procedure does not consider a low-pass filtered road profile, which e.g. B. is limited to a frequency range of less than 5 Hz. Through such low-pass filtering, individual events/unevenness of the road surface 120 are detected with a higher frequency (e.g. B. up to 15 Hz) is lost, so that the chassis of the vehicle 100 cannot react to such individual events/bumps. The filter described in this document makes it possible to react individually to higher frequencies when the threshold values 311, 312, 321, 322 are exceeded. In other words, the described procedure enables a chassis to react even to significant high frequency individual events/bumps. In addition, by increasing the number of threshold values 311, 312, 321, 322, continuous control according to an increased number of different profile classes 341, 342, 343 can be implemented.”,
Supplemental Note: One filter is used for frequencies from 5 Hz to 15 Hz. Higher frequencies are also filtered above these values as shown in Figure B).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention disclosed by Aikin with the teachings of Nauderer with a reasonable expectation of success. As discussed in claim 1, Aikin and Nauderer both teach a vehicle system able to acquire roadway surface data to be used to adjust the suspension of a vehicle for a smooth ride. One of ordinary skill in the art would find it obvious to try to implement the filter frequencies of the road profile with a bandpass filter as taught by Nauderer with the vehicle of Aikin as applying a bandpass filter aids in isolating the unevenness of the roadway applied to the body of the vehicle. This information can be applied to calculate how much suspension force, an opposite force to apply to cancel an uneven road surface (i.e. potholes, rutting, etc.), when an a roadway surface is isolated per the filter.
Regarding claim 33, Aikin, as modified, does not teach wherein, for the selected trajectory, the distinct filter-frequency parameter is a cutoff frequency or a band-pass range chosen to avoid violating one or more constraints.
Nauderer teaches wherein, for the selected trajectory, the distinct filter-frequency parameter is a cutoff frequency or a band-pass range chosen to avoid violating one or more constraints (Nauderer: Paragraph 0003: “The obtained road profile is typically filtered with a bandpass filter to isolate unevenness in the road surface that stimulates the body of the vehicle. Such irregularities lie in the frequency range from 0.5 Hz to approx. 2 Hz For low-pass filtering of the road profile, for example, For example, a “moving average” method can be used, which leads to a smoothing of the road profile. In the “moving average” method, average values are calculated over a section of the road profile. The window used is moved overlapping over the course of the road profile.”; Paragraph 0004: “By low-pass filtering the road profile, high-frequency components of the road profile are eliminated. In particular, high-frequency components in a frequency range of approx. 4 Hz to approx. 15 Hz largely eliminated from the road profile. Irregularities in this frequency range typically cause wheel vibrations. The high-frequency components of the road profile can cause a damper in the chassis to tremble or vibrate, particularly in active chassis. This can be e.g. This can be caused, for example, by noise and inaccuracies in the elevation profile data provided by the cameras or by jumps in the composition of the road profile.”,
Supplemental Note: a frequency from 0.5 Hz to 2 Hz is filtered out as not violating any constraints as it does not impact stimulations onto the body of the vehicle. The low-pass filter is an example of a cutoff frequency ).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention disclosed by Aikin with the teachings of Nauderer with a reasonable expectation of success. As discussed in claim 1, Aikin and Nauderer both teach a vehicle system able to acquire roadway surface data to be used to adjust the suspension of the vehicle for a smooth ride. One of ordinary skill in the art would find it obvious to try to implement the filter frequencies of the road profile with a bandpass filter as taught by Nauderer with the vehicle of Aikin as applying a bandpass filter aids in isolating the unevenness of the roadway applied to the body of the vehicle. This information can be applied to calculate how much suspension force, an opposite force to apply to cancel an uneven road surface (i.e. potholes, rutting, etc.), when an a roadway surface is isolated per the filter.
Regarding claim 34, Aikin, as modified, teaches wherein the one or more constraints comprise a suspension-travel constraint (Aikin: Paragraph 0003: “Comfort of a passenger in a vehicle is generally managed with passive hardware elements, such as seats, dampers, bushing, springs, jounce bumpers, etc. The passive hardware elements are configured to attenuate lateral, longitudinal or vertical accelerations resulting from the vehicle driving over a road.”; Paragraph 0025: “The control system 112 may be communicatively coupled to the internal sensors 116 and the external sensors 114 via communication links 111. In some embodiments, the control elements may include suspension actuators 130A-B of an active suspension system that is configured to reduce movement of the sprung mass 110 (e.g., a body of the vehicle or a vehicle interior) during operation of the vehicle 100. Accordingly, the control system 112 may control the suspension actuators 130A-B based at least in part on the data received from the external sensors 114, the internal sensors 116, or both.”,
Supplemental Note: the suspension of a vehicle provides comfort to the passengers. The prior art teaches the adjustments of the suspension to increase the comfort of the passengers in the vehicle).
Regarding claim 35, Aikin, as modified, teaches wherein the suspension-travel constraint is based on a difference between a road-profile height along the path of travel and a height of the selected trajectory (Aikin: Paragraph 0041: “the control system 312 may anticipate the road hazard 342 prior to the road hazard 342 entering the field of view 320 of the one or more sensors 316. In another example, the road profile 314 may indicate that the road hazard 342 is limited to a particular portion of the road 340. The control system 312 may be configured to adjust only portions of the active suspension system based on the particular portion of the road 340 relative to the vehicle 310. For example, the road hazard 342 may be a small pothole on a passenger side of the vehicle 310. Based on the road profile 314 indicating the size and location of the road hazard 342, the control system 312 may adjust only portions of the active suspension system corresponding to the passenger side of the vehicle 310.”,
Supplemental Note: the road profile states data of a pothole, which a vehicle with this suspension system as it anticipates the pothole and only adjusts the active suspension for that particular portion. The road profile is adjusted based on the depth (interpreted as height) of the pothole).
Regarding claim 36, Aikin teaches, as modified, wherein the selected trajectory causes the suspension system to start moving a vehicle body of the vehicle before traversing an upcoming upward or downward deviation in the path of travel (Aikin: Paragraph 0006: “a method to minimize motion of a vehicle is disclosed. The method includes receiving, at a control system of a vehicle, a road profile for a road at a particular location, the road profile indicating a road condition of the road at the particular location. The method also includes determining that the vehicle is approaching the road at the particular location. The method further includes adjusting an active suspension system of the vehicle in response to a determination that the vehicle is approaching the road at the particular location.”; Paragraph 0041: “the control system 312 may anticipate the road hazard 342 prior to the road hazard 342 entering the field of view 320 of the one or more sensors 316. In another example, the road profile 314 may indicate that the road hazard 342 is limited to a particular portion of the road 340. The control system 312 may be configured to adjust only portions of the active suspension system based on the particular portion of the road 340 relative to the vehicle 310. For example, the road hazard 342 may be a small pothole on a passenger side of the vehicle 310. Based on the road profile 314 indicating the size and location of the road hazard 342, the control system 312 may adjust only portions of the active suspension system corresponding to the passenger side of the vehicle 310.”,
Supplemental Note: the road profile states data of a pothole, which a vehicle with this suspension system as it anticipates the pothole and only adjusts the active suspension for that particular portion. A road profile can be received by the control system of the vehicle, therefore interpreted as gathering the profile before traversing the roadway).
Regarding claim 37, Aikin, as modified, teaches wherein implementing the selected trajectory increases comfort of a vehicle occupant (Aikin: Paragraph 0003: “Comfort of a passenger in a vehicle is generally managed with passive hardware elements, such as seats, dampers, bushing, springs, jounce bumpers, etc. The passive hardware elements are configured to attenuate lateral, longitudinal or vertical accelerations resulting from the vehicle driving over a road.”; Paragraph 0025: “The control system 112 may be communicatively coupled to the internal sensors 116 and the external sensors 114 via communication links 111. In some embodiments, the control elements may include suspension actuators 130A-B of an active suspension system that is configured to reduce movement of the sprung mass 110 (e.g., a body of the vehicle or a vehicle interior) during operation of the vehicle 100. Accordingly, the control system 112 may control the suspension actuators 130A-B based at least in part on the data received from the external sensors 114, the internal sensors 116, or both.”,
Supplemental Note: the suspension of a vehicle provides comfort to the passengers. The prior art teaches the adjustments of the suspension to increase the comfort of the passengers in the vehicle).
Regarding claim 38, Aikin, as modified, teaches wherein the road-profile data for the path of travel is obtained from one or more remate databases (Aikin: Paragraph 0057: “The profile library 450 may aggregate multiple road profiles received from multiple vehicles and store the multiple road profiles in a profile database 454. The profile library 450 may include hardware components such as system memory, general purpose processors and various interfaces to provide the profile database 454.”: Paragraphs 0051 – 0052: “The profile library 450 may be configured to receive and refine suspension adjustment profiles or force profiles in addition to or instead of the road profile. The vehicle 402 may be configured to send a suspension adjustment profile to the profile library 450 via the network 440 using the one or more communication interfaces 406. The suspension adjustment profile may include information identifying a type of vehicle, a particular location and one or more particular adjustments, as described herein. The profile library 450 may store the suspension adjustment profile to the profile database 454. The profile library 450 may aggregate multiple suspension adjustment profiles from multiple vehicles, including the vehicle 402, in the profile database 454. The vehicle 402 may request a suspension adjustment profile corresponding to a particular road segment from the profile library 450, such as when the vehicle 402 has not traveled over the particular road segment. The profile library 450 may send the suspension adjustment profile from the profile database 454 to the vehicle 402 via the network 440 using the one or more communication interfaces 452. In some embodiments, the profile library 450 may restrict the vehicle 402 from receiving the suspension adjustment profile from a particular vehicle make or model when the vehicle 402 has a different vehicle make or model. In other embodiments, the profile library 450 may send the suspension adjustment profile, and the vehicle 402 may be configured to modify the suspension adjustment profile based on known differences between the make or model of the vehicle 402 and a different make or model associated with the received suspension adjustment profile.”,
Supplemental Note: the profile library is a database which can be used by the vehicles).
Regarding claim 39, Aikin, as modified, does not teach wherein the filter having a distinct filter-frequency parameter is a zero-phase filter.
Nauderer teaches wherein the filter having a distinct filter-frequency parameter is a zero-phase filter (Nauderer: Paragraph 0032: “Fig. 1a shows an exemplary vertical dynamics model of a vehicle 100. The vehicle travels in a horizontal direction 111 (i.e. along an x-axis 151) over the roadway 120. The road surface 120 has unevennesses 121, which cause movements of the vehicle 100 in the vertical direction 112 (i.e. perpendicular to the road surface 120 or along a z-axis 152). The vehicle 100 typically includes devices 102, 104 (e.g. suspension/damping units) to cushion and/or dampen the impulses in the vertical direction 112 caused by the bumps 121.”; Paragraph 0047: “The road profile 301 has different amplitudes of vertical deflections on the z-axis 152 at different locations on the x-axis 151. The amplitudes of the vertical deflections of the road profile 301 can be evaluated via threshold values S1 311 and S2 312 (in positive direction) and S3 321 and S4 322 (in negative direction). The threshold values 311, 312, 321, 322 can be parameterized. In particular, the amplitudes of the vertical deflections can be divided into ranges, e.g. B. in the following areas: • Range I: S3 < amplitude < S1; • Range II: S1 < amplitude < S2 or S4 < amplitude < S3; • Range III: Amplitude > S2 or amplitude < S4.”,
Supplemental Note: based on the deflections of the roadway as captured on the roadway profile, the suspension system analyzes the correct force to alleviate the bumps. This is interpreted as zero-phase filtering as the suspension systems are acting as an opposite force to the acquired roadway profile. Please see Figures A and B)
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention disclosed by Aikin with the teachings of Nauderer with a reasonable expectation of success. Please refer to claim 28 as both state the same function and therefore rejected under the same pretenses.
Regarding claim 41, Aikin, as modified, teaches wherein the negative effect is a decrease in vehicle-occupant comfort (Aikin: Paragraph 0003: “Comfort of a passenger in a vehicle is generally managed with passive hardware elements, such as seats, dampers, bushing, springs, jounce bumpers, etc. The passive hardware elements are configured to attenuate lateral, longitudinal or vertical accelerations resulting from the vehicle driving over a road. The passive hardware elements act as a filter of the accelerations to minimize cabin movement and, accordingly, passenger movement. Passive management of the accelerations, such as air suspension, generally results in no attenuation of acceleration at lower frequencies (e.g., lower than a primary ride frequency) or limited attenuation at higher frequencies (e.g., above the primary ride frequency). Air suspension systems are also slow to react to rapid changes in road conditions.”).
Regarding claim 42, Aikin, as modified, teaches wherein the decrease in vehicle-occupant comfort is due to road-induced jerk (Aikin: Paragraph 0003: “Comfort of a passenger in a vehicle is generally managed with passive hardware elements, such as seats, dampers, bushing, springs, jounce bumpers, etc. The passive hardware elements are configured to attenuate lateral, longitudinal or vertical accelerations resulting from the vehicle driving over a road. The passive hardware elements act as a filter of the accelerations to minimize cabin movement and, accordingly, passenger movement. Passive management of the accelerations, such as air suspension, generally results in no attenuation of acceleration at lower frequencies (e.g., lower than a primary ride frequency) or limited attenuation at higher frequencies (e.g., above the primary ride frequency). Air suspension systems are also slow to react to rapid changes in road conditions.”; Paragraph 0033: “For example, each traversal over the surface 140 may improve a root-mean-square (RMS) acceleration of a particular wheel assembly, peak acceleration of a particular wheel assembly, RMS jerk of a particular wheel assembly, or any combination thereof. As such, the road profile is progressively improved each time the vehicle 100 traverses over the surface 140. In situations where optimization of the road profile may be too computationally intensive to be performed in real-time or near real-time during travel, computation of optimization may be deferred to a later time, such as later in the day or overnight.”,
Supplemental Note: to increase comfort of the passenger from vibrations and movements of the vehicle, the road profiles are updated to reduce jerk).
Claim 40 is rejected under 35 U.S.C. 103 as being unpatentable over Aikin et al. (US 20180079272 A1) in view of Nauderer et al. (DE102015202405A1) and Kobilarov et al. (US 10671075 B1) as applied to claim 31 above, and further in view of Bradlow et al. (US 20200124430 A1).
Regarding claim 40, Aikin, as modified, does not teach wherein the upcoming upward or downward deviation is selected from the group consisting of a pothole, a bump, a crack, a manhole cover, and an abrupt change in a vertical direction.
Bradlow teaches wherein the upcoming upward or downward deviation is selected from the group consisting of a pothole, a bump, a crack, a manhole cover, and an abrupt change in a vertical direction (Bradlow: Abstract: “The disclosed embodiments relate to detecting sidewalk riding by a personal mobility vehicle (e.g., an electric scooter). For example, a method includes collecting sensor data (e.g., vibration data of an accelerometer) generated by the scooter while traveling on a surface of a travel pathway.”; Paragraph 0063: “In other instances, intelligent sensing systems are used to increase the safety of PMVs by warning users of restricted usage in areas of known hazards, such as in construction zones or nearby potholes.”; Paragraph 0087: “Particular surface materials may have a distinctive surface roughness. A surface roughness may be characterized as the average deviation between an actual surface and a perfectly smooth ideal surface. Surface roughness may be characterized across length scales from small scales (e.g., the roughness of individual aggregate grains on a concrete surface) to larger scales (e.g., the deflection caused by a speed bump). In some instances, surface roughness may be characterized using a roughness index, such as the International Roughness Index (IRI). The IRI may be measured to be the total amount of vertical deflection in a vehicle traveling over a flat surface.”; Paragraph 0138: “Such visual cues may include parked vehicles, traveling vehicles, pedestrians, streetlight poles, road signs, traffic lights, fire hydrants, utility boxes, power poles, manholes, buildings, fencing, grass, trees, landscaping, walls, traffic cones, impediments, ramps, curbs, joints, bridges, overpasses, underpasses, tunnels, drainage channels, drainage gratings, manholes, refuse containers, bicycle racks, reflectors, and lane dividers.”: Paragraph 0142: “The bike lane 702 has a substantially smooth asphalt surface with some defects (e.g., cracks) that can transverse or substantially aligned with an axis z-z in the direction in which the PMV travels.”).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention disclosed by Aikin with the teachings of Bradlow with a reasonable expectation of success. Both Aikin and Bradlow teach vehicle which are able to acquire data about their environment for traversal improvements. Aikin utilizes gathering profiles for different roadways which reduce the vibrations in the vehicle and increase comfort the passengers. The profiles relate to deviations in height of the roadway and adjusting components, such as the suspension, to adjust prior to traversing that roadway. One with knowledge in the art would find this profiles being able to gather deviations in height of the roadway to be a simple substitution in identifying the many roadway variables as taught by Bradlow. For example, the roadway profile of Aikin will be able to detect any deviations in height caused by a bump, manhole cover, crack, etc. of the roadway which is able to be acquired by a vehicle traveling along that section. The profile already includes any deviations previous vehicles have traveled over and has them stored.
Claims 43 – 45 are rejected under 35 U.S.C. 103 as being unpatentable over Aikin et al. (US 20180079272 A1), further in view of Anderson et al. (US 20150224845 A1).
Regarding claim 43, Aikin teaches a method of minimizing a negative effect of vehicle travel along a particular path on a road surface ahead of a vehicle, the method comprising: (Aikin: Paragraph 0006: “In one embodiment, a method to minimize motion of a vehicle is disclosed. The method includes receiving, at a control system of a vehicle, a road profile for a road at a particular location, the road profile indicating a road condition of the road at the particular location.”)
obtaining road-profile data for the particular path; (Aikin: Abstract: “A method includes receiving, at a control system of a vehicle, a road profile for a road at a particular location, the road profile indicating a road condition of the road at the particular location. The method also includes determining that the vehicle is approaching the road at the particular location.”)
before traveling along the particular path, (Aikin: Paragraph 0006: “a method to minimize motion of a vehicle is disclosed. The method includes receiving, at a control system of a vehicle, a road profile for a road at a particular location, the road profile indicating a road condition of the road at the particular location. The method also includes determining that the vehicle is approaching the road at the particular location. The method further includes adjusting an active suspension system of the vehicle in response to a determination that the vehicle is approaching the road at the particular location.”; Paragraph 0041: “ In some embodiments, the control system 312 may prepare for the road hazard 342 by reading data from the road profile 314 that may indicate previous adjustments to the active suspension system of the vehicle 310. For example, the road profile 314 may indicate that in a previous drive over the road hazard 342 that the vehicle 310 was raised a particular height to minimize vertical motion of the vehicle 310. The road profile 314 may indicate a particular location corresponding to the road hazard 342 such that the control system 312 may anticipate the road hazard 342 prior to the road hazard 342 entering the field of view 320 of the one or more sensors 316.”; Paragraphs 0051 – 0052: “The profile library 450 may be configured to receive and refine suspension adjustment profiles or force profiles in addition to or instead of the road profile. The vehicle 402 may be configured to send a suspension adjustment profile to the profile library 450 via the network 440 using the one or more communication interfaces 406. The suspension adjustment profile may include information identifying a type of vehicle, a particular location and one or more particular adjustments, as described herein. The profile library 450 may store the suspension adjustment profile to the profile database 454. The profile library 450 may aggregate multiple suspension adjustment profiles from multiple vehicles, including the vehicle 402, in the profile database 454. The vehicle 402 may request a suspension adjustment profile corresponding to a particular road segment from the profile library 450, such as when the vehicle 402 has not traveled over the particular road segment. The profile library 450 may send the suspension adjustment profile from the profile database 454 to the vehicle 402 via the network 440 using the one or more communication interfaces 452. In some embodiments, the profile library 450 may restrict the vehicle 402 from receiving the suspension adjustment profile from a particular vehicle make or model when the vehicle 402 has a different vehicle make or model. In other embodiments, the profile library 450 may send the suspension adjustment profile, and the vehicle 402 may be configured to modify the suspension adjustment profile based on known differences between the make or model of the vehicle 402 and a different make or model associated with the received suspension adjustment profile.”,
Supplemental Note: a road profile is saved in a profile library and can be received by the control system of the vehicle, therefore interpreted as gathering the profile before traversing the roadway).
In sum, Aikin teaches a method of minimizing a negative effect of vehicle travel along a particular path on a road surface ahead of a vehicle, the method comprising: obtaining road-profile data for the particular path; before traveling along the particular path. Aikin however does not teach associating a cost function with each of a multiplicity of projected vehicle-body motion trajectories of the vehicle along the particular path; selecting a trajectory based on the cost functions of the multiplicity of projected vehicle- body motion trajectories; and while traveling along the particular path, operating a suspension system of the vehicle to implement the selected projected vehicle-body motion trajectory along the particular path.
Anderson teaches associating a cost function with each of a multiplicity of projected vehicle-body motion trajectories of the vehicle along the particular path;
selecting a trajectory based on the cost functions of the multiplicity of projected vehicle- body motion trajectories; and
while traveling along the particular path, operating a suspension system of the vehicle to implement the selected projected vehicle-body motion trajectory along the particular path (Anderson: Paragraph 0464: “Events are detected and classified as early as possible, using advanced information, statistical information, or sensor information, and then the expected benefit to the occupants in terms of any of a number of known analysis methodologies that may be further described. The expected cost of the intervention is calculated in terms of its power consumption, or in terms of its energy consumption if the event has a finite duration. This cost function may comprise of other parameters such as gain factors, force commands, averages of these parameters, or any other control parameter that may have an energy implication on the system.”; Paragraph 0468: “Methods and systems disclosed herein generally relate to changing active suspension control algorithms in relation to a cost function that has at least one parameter related to energy consumption (average power, instantaneous power, control function gains, force output, etc.).”; Paragraph 0481: “The algorithm may look for time periods in the past history of the motion of the vehicle where the occupant comfort levels are poor, and find characteristics in the input profile leading up to these time periods that are repeatable. As an example, an analysis of wheel motion as measured by accelerometers on the wheel may detect elevated levels of peak wheel acceleration on roads with cracked or damaged road surface. These roads are likely to excite the vehicle body even if they have not already done so, and an analysis of past history of driving may lead to defining a continuous or discrete scale relating road roughness to the likelihood of poor occupant comfort, taking into account the past actions of the active suspension system during these times. This continuous or discrete scale may then be used, possibly in conjunction with other sensors, to recognize this event.”; Paragraph 0492 – Paragraph 0493: “The expected benefit for the occupant is calculated ahead of time, and for a multitude of interventions from the active suspension system. In order to do this, we may use information from the available sensors on the vehicle and ahead of the vehicle, as described previously, to predict the upcoming inputs. This information is then fed into a model of the vehicle and suspension. In a simple embodiment, this model may represent a quarter car model with a sprung and unsprung mass, the suspension and tire springs, dampers, and actuators as needed… The model may also, in other embodiments, be continuously adapted and improved based on measured outputs, in a predictor-corrector type scheme, like for example a Kalman filter.”; Paragraphs 0495 – 0496: “The cost for the purposes of this calculation may be defined as the amount of power consumed by the active suspension system. Depending on the type of input event, the cost may mean one of a multitude of things. For events that are characterized by short or in general finite duration, or may be predicted in their entirety, it makes more sense to calculate the total amount of energy for the event, while for events that are indeterminate in duration it makes more sense to talk about the average or instantaneous power. The goal is for the system to reduce overall energy consumption. Once a classified event is recognized, and a calculation of the expected benefit and cost is made, then a scheme may be applied to determine the course of action to take in the active suspension system”; Paragraph 0499: “The algorithm in one embodiment continuously adjusts its expected benefit/cost ratio for the present or upcoming road events, and sets the performance parameter accordingly. For events or interventions where a high benefit/cost ratio is expected, the performance parameter is set high and the active suspension algorithm creates high performance along with typically higher power outputs. For events where the benefit/cost ratio is expected to be low, the performance parameter may be low and the active suspension algorithm may maintain a low-energy, low performance status, thus saving overall average energy. For events where the benefit/cost ratio is between high and low, the performance factor may also be lower than the maximum but higher than the lowest value, and the active suspension system may go into an intermediate mode where comfort is prioritized, but not as much as in high performance mode.”).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have been modified the invention disclosed by Aikin with the teachings of Anderson with a reasonable expectation of success. One of ordinary skill in the art would find it obvious to try to implement the method of Anderson to determine the amount of active intervention required for each event as obvious to try with the vehicle system of Aikin. Anderson teaches the ability of evaluating roadway events by the use of an algorithm utilizing a cost function, a determination can be made of how to adjust the active suspension system in modes of either high passenger comfort, high performance, or both. Events are classified as, for example, areas of the roadway where there are cracks which lead to higher vehicle wheel vibrations and lower passenger comfort. The algorithm works in conjunction with the model representing the vehicle to determine the expected benefits to the occupant by the suspension behavior in which information is gathered that maximizes suspension behavior while minimizing the power consumption. Aikin would find applying this method as obvious to try with its system as Aikin also reaches gathering roadway information (such as any event information taught by Anderson) in which a force profile is generated to adjust the suspension of the vehicle as it travels along that section. The combination with Anderson allows for the vehicle system of Aikin to utilize the algorithm in aiding to better determine an active suspension procedure which maximizes the suspension behavior (such as passenger comfort) and minimizes the power consumption. Minimizing power consumption is known to one of ordinary skill in the art to reduce the load on the power source of the vehicle, therefore increasing the life of the vehicle and making the vehicle system of Aikin more efficient.
Regarding claim 44, Aikin, as modified, does not teach wherein the cost function penalizes violation of one or more constraints of the suspension system of the vehicle.
Anderson teaches wherein the cost function penalizes violation of one or more constraints of the suspension system of the vehicle (Anderson: Paragraph 0464: “The expected cost of the intervention is calculated in terms of its power consumption, or in terms of its energy consumption if the event has a finite duration. This cost function may comprise of other parameters such as gain factors, force commands, averages of these parameters, or any other control parameter that may have an energy implication on the system.”; Paragraph 0465: “in response to the event detector, the algorithm adjusts the actions of the active suspension in a way such that the energy or power consumed over the upcoming detected event is kept as low as possible while the performance meets the desired levels… For example, in the latter case a smooth road may be detected, and the system may reduce active control output (gain factors, thresholds, etc.) when there is a high cost (in terms of energy, etc.) compared to a small benefit it is creating (vertical acceleration mitigation, other ride metric, etc.), in response to the smooth road.”; Paragraph 0468: “Methods and systems disclosed herein generally relate to changing active suspension control algorithms in relation to a cost function that has at least one parameter related to energy consumption (average power, instantaneous power, control function gains, force output, etc.).”,
Supplemental Note: based on the energy consumption needed by the suspension system, there is a high cost for using more energy for controlling the suspension system. This is equivalent to a penalization as the whole point of the system is to adjust the suspension to use as little energy as possible).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have been modified the invention disclosed by Aikin with the teachings of Anderson with a reasonable expectation of success. As stated for claim 43, One of ordinary skill in the art would find it obvious to try to implement the method of Anderson to determine the amount of active intervention required for each event as obvious to try with the vehicle system of Aikin. Anderson teaches the ability of evaluating roadway events by the use of an algorithm utilizing a cost function, a determination can be made of how to adjust the active suspension system in terms of power consumption. The algorithm works in conjunction with the model representing the vehicle to determine the expected benefits to the occupant by the suspension behavior in which information is gathered that maximizes suspension behavior while minimizing the power consumption. Aikin would find applying this method as obvious to try with its system as Aikin also reaches gathering roadway information (such as any event information taught by Anderson) in which a force profile is generated to adjust the suspension of the vehicle as it travels along that section. The combination with Anderson allows for the vehicle system of Aikin to utilize the algorithm in aiding to better determine an active suspension procedure which maximizes the suspension behavior (such as passenger comfort) and minimizes the power consumption. Minimizing power consumption is known to one of ordinary skill in the art to reduce the load on the power source of the vehicle, therefore increasing the life of the vehicle and making the vehicle system of Aikin more efficient.
Regarding claim 45, Aikin does not teach wherein the one or more constraints of the suspension system comprise a suspension-travel constraint.
Anderson teaches wherein the one or more constraints of the suspension system comprise a suspension-travel constraint (Anderson: Paragraph 0142: “The difference between the measured power and average power neutrality constraint is used by the plurality of active vehicle suspension actuator controllers to throttle the actuator commands in such a way that the total power consumed by each of the plurality of active vehicle suspension actuators stays below the at least one average power neutrality constraint. The average power neutrality constraint may be a power consumption constraint, a power generation constraint, or both.”; Paragraph 0148: “a least a portion of the plurality of active vehicle suspension actuators are controlled to ensure that the average power neutrality for the portion of the plurality of active vehicle suspension actuators stays below the at least one average power neutrality constraint.”,
Supplemental Note: the constraints are based on the power generation constraints that dictate how much energy is to be supplied to the suspension system).
As stated for claim 43, One of ordinary skill in the art would find it obvious to try to implement the method of Anderson to determine the amount of active intervention required for each event as obvious to try with the vehicle system of Aikin. Anderson teaches the ability of evaluating roadway events by the use of an algorithm utilizing a cost function, a determination can be made of how to adjust the active suspension system in terms of power consumption. The algorithm works in conjunction with the model representing the vehicle to determine the expected benefits to the occupant by the suspension behavior in which information is gathered that maximizes suspension behavior while minimizing the power consumption. The power consumption constraints are set as such that at least a portion of the vehicle suspension actuators stay below an average power neutrality constraint. Aikin would find applying this method as obvious to try with its system as Aikin also reaches gathering roadway information (such as any event information taught by Anderson) in which a force profile is generated to adjust the suspension of the vehicle as it travels along that section. The combination with Anderson allows for the vehicle system of Aikin to utilize the algorithm in aiding to better determine an active suspension procedure which maximizes the suspension behavior (such as passenger comfort) and minimizes the power consumption. Minimizing power consumption is known to one of ordinary skill in the art to reduce the load on the power source of the vehicle, therefore increasing the life of the vehicle and making the vehicle system of Aikin more efficient.
Claims 46 and 49 are rejected under 35 U.S.C. 103 as being unpatentable over Aikin et al. (US 20180079272 A1) in view of Anderson et al. (US 20150224845 A1) as applied to claim 43 above, and further in view of Nauderer et al. (DE102015202405A1).
Regarding claim 46, Aikin does not teach wherein at least one of the multiplicity of projected vehicle- body motion trajectories is generated.
Anderson teaches wherein at least one of the multiplicity of projected vehicle- body motion trajectories is generated (Anderson: Paragraph 0493: “In a simple embodiment, this model may represent a quarter car model with a sprung and unsprung mass, the suspension and tire springs, dampers, and actuators as needed. In more complicated embodiments, this model may represent a full vehicle, which may include only rigid body degrees of freedom or also include flexibility of the vehicle body, and may include suspension dynamics and kinematics as required to achieve the desired model accuracy. The model may also, in other embodiments, be continuously adapted and improved based on measured outputs, in a predictor-corrector type scheme, like for example a Kalman filter.”).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have been modified the invention disclosed by Aikin with the teachings of Anderson with a reasonable expectation of success. Please refer to the rejection of claim 43 as both claim the same function and therefore rejected under the same pretenses. Aikin in view of Anderson however still do not teach by filtering the road-profile data with a filter having a filter- frequency parameter.
Nauderer teaches by filtering the road-profile data with a filter having a filter- frequency parameter (Nauderer: Paragraph 0003: “The obtained road profile is typically filtered with a bandpass filter to isolate unevenness in the road surface that stimulates the body of the vehicle. Such irregularities lie in the frequency range from 0.5 Hz to approx. 2 Hz.”; Paragraph 0004: “In particular, high-frequency components in a frequency range of approx. 5 Hz to approx. 15 Hz largely eliminated from the road profile. Irregularities in this frequency range typically cause wheel vibrations. The high-frequency components of the road profile can cause a damper in the chassis to tremble or vibrate, particularly in active chassis”; Paragraph 0018: “The plurality of locations of the driving profile then corresponds, depending on the driving speed, to a plurality of points in time at which the vehicle reaches the corresponding plurality of locations.”; Paragraph 0033: “The suspension and/or damping of the wheel block 103 relative to the vehicle block 101 by the suspension and/or by the shock absorber is represented in Fig. 1a by the chassis unit 102. The chassis unit 102 includes suspension and/or damping properties that can be changed by selecting different driving modes (comfort mode, sport mode). A setting of the chassis unit 102 can be changed according to the method described in this document and adapted in a predictive manner to a profile of the roadway 120”).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have been modified the invention disclosed by Aikin with the teachings of Nauderer with a reasonable expectation of success. Please refer to the rejection of claim 1 as both claim the same function and therefore rejected under the same pretenses.
Regarding claim 49, Aikin, as modified, does not teach wherein each of the multiplicity of projected vehicle-body motion trajectories is generated.
Anderson teaches wherein each of the multiplicity of projected vehicle-body motion trajectories is generated (Anderson: Paragraph 0406: “A computer-based model or algorithm may predict or calculate energy usage by at least a portion of the plurality of loads at a variety of points along the route. According to one aspect, energy usage may be positive or negative (consumption or regeneration). While driving, the algorithm or model may then dynamically and predictively set a state of charge of the energy storage apparatus as a function of calculated energy usage for points along the route.”; Paragraph 0493: “In a simple embodiment, this model may represent a quarter car model with a sprung and unsprung mass, the suspension and tire springs, dampers, and actuators as needed. In more complicated embodiments, this model may represent a full vehicle, which may include only rigid body degrees of freedom or also include flexibility of the vehicle body, and may include suspension dynamics and kinematics as required to achieve the desired model accuracy. The model may also, in other embodiments, be continuously adapted and improved based on measured outputs, in a predictor-corrector type scheme, like for example a Kalman filter.”; Paragraph 0494: “The output of this model may then be used to determine the expected benefit to the occupants. In a simple embodiment, the output may be calculated for the vehicle in each of a multitude of control modes, and the expected benefit and cost may be calculated for each, based on the model. This may provide sufficient information to preemptively modify suspension behavior to maximize performance and minimize power consumption.”).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have been modified the invention disclosed by Aikin with the teachings of Anderson with a reasonable expectation of success. Please refer to the rejection of claim 49 as both claim the same function and therefore rejected under the same pretenses. Aikin in view of Anderson however still do not teach by filtering the road-profile data with a filter having a filter- frequency parameter.
Nauderer teaches by filtering the road-profile data with a filter having a distinct filter- frequency parameter (Nauderer: Paragraph 0003: “The obtained road profile is typically filtered with a bandpass filter to isolate unevenness in the road surface that stimulates the body of the vehicle. Such irregularities lie in the frequency range from 0.5 Hz to approx. 2 Hz.”; Paragraph 0004: “In particular, high-frequency components in a frequency range of approx. 5 Hz to approx. 15 Hz largely eliminated from the road profile. Irregularities in this frequency range typically cause wheel vibrations. The high-frequency components of the road profile can cause a damper in the chassis to tremble or vibrate, particularly in active chassis”; Paragraph 0018: “The plurality of locations of the driving profile then corresponds, depending on the driving speed, to a plurality of points in time at which the vehicle reaches the corresponding plurality of locations.”; Paragraph 0033: “The suspension and/or damping of the wheel block 103 relative to the vehicle block 101 by the suspension and/or by the shock absorber is represented in Fig. 1a by the chassis unit 102. The chassis unit 102 includes suspension and/or damping properties that can be changed by selecting different driving modes (comfort mode, sport mode). A setting of the chassis unit 102 can be changed according to the method described in this document and adapted in a predictive manner to a profile of the roadway 120”).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have been modified the invention disclosed by Aikin with the teachings of Nauderer with a reasonable expectation of success. Please refer to the rejection of claim 1 as both claim the same function and therefore rejected under the same pretenses.
Claims 47 is rejected under 35 U.S.C. 103 as being unpatentable over Aikin et al. (US 20180079272 A1) in view of Anderson et al. (US 20150224845 A1) as applied to claim 43 above, and further in view of Kobilarov et al. (US 10671075 B1).
Regarding claim 47, Aikin, as modified, does not teach wherein the cost function values low jerk levels of vehicle- body motion.
Kobilarov teaches wherein the cost function values low jerk levels of vehicle- body motion (Kobilarov: Col. 18, lines 9 – 27: “At operation 702, the process can include receiving a candidate trajectory. In some instances, the candidate trajectory received in the operation 702 can include an optimized trajectory that is to be implemented by components of an autonomous vehicle. For example, the candidate trajectory of the operation 702 may have been selected as an action to be performed and optimized to minimize one or more costs while respecting motion dynamics, safety, performance, mission requirements, and the like. In some instances, the candidate trajectory can be received by the decision planner component 512, the trajectory tracker component 514, and/or the execution component 516. In some instances, the operation 702 can include simulating the vehicle dynamics with respect to the candidate trajectory and/or simulating various fallback or stopping operations with respect to the candidate trajectory or obstacles that may be present in an environment with respect to the candidate trajectory.”; Col. 11, lines 15 – 22: “If multiple trajectories are determined not to violate the TL formula, a trajectory with a lowest cost (or a highest performance, comfort, etc.) can be selected. For example, for various operations of the autonomous vehicle, or for various possible trajectories, a cost function can penalize acceleration, jerk, lateral acceleration, yaw, steering angle, steering angle rate, etc.”).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention disclosed by Aikin with the teachings of Kobilarov with a reasonable expectation of success. As stated for claim 1, Aikin and Kobilarov both teach gathering roadway information and adjusting its vehicle components to increase the comfort of the user while traversing that section. Kobilarov further teaches the ability to select an candidate trajectory with the lowest cost from multiple optimized trajectories by the use of a cost function which penalizes jerk. One with knowledge in the art would find this obvious to try to implement this function with the vehicle of Aikin to increase the comfort for the passenger. Aikin teaches storing roadway profiles in an online database which can be acquired by any vehicle also planning to traverse that section (Aikin: Paragraphs 0051 – 0052). The profiles however may not fully match the vehicle therefore the selected profile may not be the most effective. The ability to compare the different profiles would allow the ability to select the best profile for the vehicle that has the highest user comfort.
Claims 48 is rejected under 35 U.S.C. 103 as being unpatentable over Aikin et al. (US 20180079272 A1) in view of Anderson et al. (US 20150224845 A1) and Nauderer et al. (DE102015202405A1) as applied to claim 46 above, and further in view of Kobilarov et al. (US 10671075 B1).
Regarding claim 48, Aikin, as modified, does not teach wherein the cost function values low jerk levels of vehicle- body motion.
Kobilarov teaches wherein the cost function values low jerk levels of vehicle- body motion (Kobilarov: Col. 18, lines 9 – 27: “At operation 702, the process can include receiving a candidate trajectory. In some instances, the candidate trajectory received in the operation 702 can include an optimized trajectory that is to be implemented by components of an autonomous vehicle. For example, the candidate trajectory of the operation 702 may have been selected as an action to be performed and optimized to minimize one or more costs while respecting motion dynamics, safety, performance, mission requirements, and the like. In some instances, the candidate trajectory can be received by the decision planner component 512, the trajectory tracker component 514, and/or the execution component 516. In some instances, the operation 702 can include simulating the vehicle dynamics with respect to the candidate trajectory and/or simulating various fallback or stopping operations with respect to the candidate trajectory or obstacles that may be present in an environment with respect to the candidate trajectory.”; Col. 11, lines 15 – 22: “If multiple trajectories are determined not to violate the TL formula, a trajectory with a lowest cost (or a highest performance, comfort, etc.) can be selected. For example, for various operations of the autonomous vehicle, or for various possible trajectories, a cost function can penalize acceleration, jerk, lateral acceleration, yaw, steering angle, steering angle rate, etc.”).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention disclosed by Aikin with the teachings of Kobilarov with a reasonable expectation of success. Please refer to the rejection of claim 47 as both claim the same function and therefore rejected under the same pretenses.
Response to Arguments
Applicant’s arguments of Rejections under 35 U.S.C. 112 section in the REMARKS, filed 05/29/2026 with respect to the 35 U.S.C. 112(a) written description and enablement of claims 31 – 42 have been fully considered and are persuasive. The 35 U.S.C. 112(a) written description and enablement of claims 31 – 42 has been withdrawn.
Applicant’s arguments of Unrebutted Arguments from the Prior Remarks section in the REMARKS, filed 05/29/2026 with respect to the Response to Arguments of the Non-Final office action mailed 12/01/2025 have been fully considered but are not persuasive.
Applicant states:
Several arguments from the 08/11/2025 Remarks were not substantively engaged in the Office Action's Response to Arguments (Office Action pp. 34-36) and remain unrebutted.
(i) Applicant argued that the Office Action "conflates signal conditioning with physical isolation" (Remarks 08/11/2025, p. 8). The Office Action did not address this; the same "isolating the unevenness" motivation language was simply repeated (e.g., See Office Action p. 14).
(ii) Applicant argued that Nauderer's bandpass is "predetermined" and "not identified per event... by a controller during trajectory selection" (Remarks 08/11/2025, p. 8). The Office Action responded only by referencing Nauderer's two frequency ranges, without engaging on the predetermined-versus-runtime-identification distinction.
Examiner respectfully disagrees. Regarding the first argument (i), Aikin teaches the ability of a road profile to be used to determine a suspension adjustment profile (force profile). This force profile (also known as suspension adjustment profile) is used to minimize the frequency response from the surface (Aikin: Paragraph 0032). Nauderer teaches the ability of the road profile able to be analyzed where, for example, the high frequencies can be identified (Nauderer: Paragraph 0018). Furthermore, the system isolates this frequency range from the roadway profile to detect unevenness of the road surface (Nauderer: Paragraph 0045). The areas which are isolated are within this frequency range, thus there is no conflating signal conditioning with physical isolation. Furthermore, isolating the unevenness is equivalent to Nauderer’s system being able to isolate area of the road profile that is within this high frequency range. Regarding the second argument (ii), as stated above, Nauderer already states the frequencies ranges it needs to isolate form the road profile to detect unevenness of the road. How is this different from what the claimed system does? The specification states the controller filters disturbances by determining if the frequencies of an upcoming road segment are within certain frequency thresholds. This way allows the controller to create sections of the profile to be filtered out by different frequencies (Specification: Page 20, lines 6 – 16). The claim limitation being “wherein the selecting comprises identifying a filter-frequency parameter of a filter”, thus Nauderer’s method of only isolating the high-frequencies from the road profile is equivalent to this limitation.
Applicant further states:
(iii) The Office Action ignores a fundamental difference between Aikin's approach and the claimed approach.
Aikin associates specific force profiles with specific road segments - force profiles collected by various vehicles during their previous drives over those segments (Aikin 1[0048], [0051]-[0052]). When a host vehicle approaches a road segment, Aikin's profile library either restricts the host vehicle to receiving only profiles collected by a vehicle matching the host vehicle's make and model, or sends a profile and configures the host vehicle to modify it based on known make/model differences (Aikin 1[0052]). Aikin's "selection" is therefore performed at the input layer - selecting (or modifying) a stored force profile to fit the host vehicle. Aikin expressly contemplates that its library may operate without road profile data at all: "[t]he profile library 450 may be configured to receive and refine suspension adjustment profiles or force profiles in addition to or instead of the road profile" (Aikin [0051], emphasis added). Aikin's selection mechanism therefore does not require processing road profile data - it operates by matching stored force profiles to host vehicles regardless of whether road profile data is in the library. Aikin does not disclose processing the road profile data - by filtering or otherwise - to generate multiple candidate trajectories.
The claimed system operates differently. The system receives road profile preview data for an upcoming travel surface, applies filters with distinct filter-frequency parameters to that data, generates multiple candidate trajectories of vehicle-body motion from the filtered outputs, and selects from among those candidate trajectories the one that minimizes a negative effect. The claimed method does not select from force profiles. It selects from candidate body-motion trajectories generated by filtering road-profile data. The selection - i.e., the identification of the filter-frequency parameter - may further account for the current state of the vehicle (e.g., speed),since vehicle dynamics affect the constraints the trajectory must satisfy (Spec [[0105]). As Applicant noted previously, "generating a force profile is not the same as selecting a force profile from multiple alternative force profiles" (Remarks 08/11/2025, p. 8) - and more fundamentally, the claim selects on the output side (a resulting body-motion trajectory) rather than the input side (force profiles to be commanded).
By treating Aikin's library-side selection of input force profiles as equivalent to the claim's selection of possible target output trajectories, the Office Action conflates two different operations that would occur at different stages of a control loop.
Examiner respectfully disagrees. Aikin teaches the ability of the road profile of a roadway to be received by the control system. This road profile is based in part of the data received from the vehicle sensors and can also be created in real-time. The control system then takes this data and generates a force profile which is used to minimize frequency responses from the surface of the roadway (Aikin: Paragraph 0031 - 0032). Aikin teaches the claimed system as it is still receiving a road profile (equivalent to the claimed road profile preview data) and creates a force profile which teaches adjusting the suspension of the vehicle (equivalent to the improved trajectory). The system may receive the force profile in addition to or instead of the road profile, however the terms of ‘may’ or ‘in addition to or instead of’ still allow for the other function of generating the force profile based at least in part of the road profile data. In some situations it may or may not do that.
Applicant further states:
(iv) Applicant distinguished Aikin's force profile (a control input) from a vehicle-body
trajectory (a state of the system) (Remarks 08/11/2025, pp. 7-8). The Office Action attempts to meet this argument with a citation to Applicant's specification at [[0101], followed by the conclusion that the specification "thus impl[ies] that the trajectory works with the vehicle suspensions applying various filters" (Office Action p. 35). The meaning of "trajectory works with" is unclear, and this response does not explain the basis for the suggestion that Aikin's force profile is the same as the claimed trajectory. The cited specification passage describes the trajectory as the output of applying a filter to the disturbance input - an operation Aikin does not perform - and so the citation does not bridge the input-versus-state distinction. The Office Action does not articulate the logical step from "the specification describes trajectories produced by filtering" to "Aikin's force profile, which Aikin does not produce by filtering, is a trajectory." See MPEP § 2143 (an obviousness rejection must be supported by articulated reasoning with a rational underpinning).
MPEP § 707.07(f) (Answering Arguments of Applicant) provides that "Where the applicant traverses any rejection, the examiner should, if they repeat the rejection, take note of the applicant's argument and answer the substance of it." MPEP § 2145 (Consideration of Applicant's Rebuttal Arguments and Evidence) further provides that consideration of rebuttal arguments "requires Office personnel to weigh the proffered evidence and arguments" and to "explain their conclusions." A form-paragraph conclusory statement that the arguments "have been fully considered but they are not persuasive" does not, by itself, discharge those duties where the substance of an argument is not weighed, answered, or explained on the merits. Each of the four arguments above is independently sufficient to undermine the prima facie case, and each remains unrebutted on the present record.
Examiner respectfully disagrees. The previous response and specification citation was used to highlight that the improved trajectory is calculated by applying the various filters designed to set a certain desired trajectory. Aikin teaches the force profile to be adjusted to minimize the frequency response from the surface (Aikin: Paragraph 0032). The suspension position for the actuators are taught to be adjusted for low and high frequencies (Aikin: Paragraph 0028), therefore the force profile is able to be adjusted to minimize these frequencies. The specification states the proactive suspension controller is able apply an improved trajectory that reduces the jerk which negatively affect the comfort of vehicle occupants (Specification: lines 21 – 24). Therefore, Aikin is teaching this exact limitation by having a force profile which minimizes the frequencies gathered from the surface of the roadway by adjusting the suspension of the vehicle.
Applicant’s arguments of Rejections under 35 U.S.C. 103 section in the REMARKS, filed 05/29/2026 with respect to the 35 U.S.C. 103 prior art rejection of claims 1, 9, 10 and 24 – 30 have been fully considered but are not persuasive.
Applicant states:
In the Office Action, independent claim 1 and dependent claims 9, 10 and 24-30 are rejected under 35 U.S.C. § 103 as being unpatentable over U.S. Publication No. 2018/0079272 (Aikin) in view of DE 10 2015 202405A1 (Nauderer).
I. Independent Claim 1:
Claim 1 recites a three-step integrated process:
obtaining information associated with a road-profile of an upcoming travel surface ahead of a vehicle; and
based on the information, before traversing the upcoming travel surface, selecting a trajectory to minimize a negative effect of the road- profile on the vehicle, wherein the selecting comprises identifying a filter-frequency parameter of a filter to be applied during a traversal of the upcoming travel surface by a proactive controller to the information; and
implementing the selected trajectory when the vehicle traverses the upcoming travel surface
The combination of Aikin and Nauderer does not disclose this integrated process.
One of ordinary skill in the art would recognize that "selection" presupposes a set of
alternatives - a controller cannot "select" among a single possibility. The claim therefore requires that multiple candidate trajectories be determined before the selecting step occurs. The Office Action identifies no disclosure of any step that produces multiple candidate trajectories from road- profile preview information.
What Aikin discloses is generating or retrieving a single "force profile" - "particular force adjustments to the suspension actuators 130A-B required for a smooth ride over a particular road segment" (Aikin 1[0032]; see also 1[0034]). That disclosure fails to disclose the selecting step for two independent reasons. First, generation and retrieval are not selection. Aikin's force-profile module either generates a single force profile through an undisclosed algorithm or retrieves a single stored profile from the library. Neither operation produces alternative trajectory candidates from road-profile preview information. Second, Aikin's output is a force profile, not a trajectory. On the other hand, the claimed process selects "a trajectory" - a planned motion of the vehicle body - to be implemented by the suspension during traversal. As discussed above, Aikin's force profile is a control input (commanded actuator forces) applied to the suspension; the body's resulting motion in Aikin is an emergent consequence, not a selected target the vehicle body is driven to follow. Because Aikin discloses no trajectory to be followed, Aikin discloses neither the selecting step nor the implementing step the claim recites.
Nauderer does not cure the deficiency in Aikin. Nauderer discloses a sliding-window
amplitude-threshold classifier that assigns sections of a road profile to amplitude-based "profile classes" (I, II, III) based on maximum vertical deflection against thresholds (S 1-54). Nauderer does not disclose determining any trajectory, much less producing multiple candidate trajectories from road-profile preview information. The cited Nauderer 1[0003] is a background description of prior- art bandpass filtering - a signal-processing operation producing filtered data, not trajectory candidates and not a trajectory the suspension is driven to follow. Nauderer cannot supply what Aikin lacks.
The combination of Aikin and Nauderer does not disclose producing multiple candidate body-motion trajectories from road-profile preview information, selecting one of those candidates before the vehicle traverses the travel surface, or implementing the selected trajectory during traversal.
Therefore, for at least the above reasons, Aikin and Nauderer, individually or in
combination, do not inherently or expressly disclose or render obvious the above cited limitations of claim 1.
Examiner respectfully disagrees. The claim limitation states “based on the information, before traversing the upcoming travel surface, selecting a trajectory to minimize a negative effect of the road- profile on the vehicle, wherein the selecting comprises identifying a filter-frequency parameter of a filter to be applied during a traversal of the upcoming travel surface by a proactive controller to the information”. Breaking down the broadest reasonable interpretation of the claim is teaching to select a trajectory which represents the desired motion of the vehicle (Specification: Page 18, lines 28 – 29). Aikin teaches the ability of the force profile to adjust the suspension of the vehicle, therefore the claimed trajectory is equivalent to the this generated force profile. The force profile is also used to reduce the negative effects of bumps and other road hazards (Aikin: Paragraph 0032), thus teaching the claim limitation of also minimizing a negative effect of the road-profile on the vehicle. The claimed selecting process is taught in view of Naurderer. Naurderer teaches the ability of filtering the road profile with a bandpass filter to isolate unevenness in the road surface (Naurderer: Paragraph 0003). Therefore the claimed filter-frequency parameter of a filter to be applied is the bandpass filter, Naurderer teaches these frequencies are in the range of 5 – 15 Hz (Nauderer: Paragraph 0003 – 0004; Paragraph 0033). The selecting process is only claimed to identify a filter-frequency parameter, thus it cannot be interpreted that multiple trajectories are produced as argued above.
Applicant further states:
In the Office Action, independent claim 31 and dependent claims 32-39, 41 and 42 are rejected under 35 U.S.C. § 103 as being unpatentable over Aikin in view of Nauderer and further in view of U.S. Patent No. 10671075 (Kobilarov).
II. Independent Claim 31:
Claim 31 includes four integrated steps:
obtaining road-profile data for the path of travel;
before traveling along the path, planning at least two candidate trajectories of vehicle-body motion along the path, wherein, for each of the at least two candidate trajectories, the planning comprises generating that trajectory by filtering the road-profile data with a filter having a distinct filter-frequency parameter;
from among the at least two candidate trajectories, selecting a trajectory that minimizes the negative effect of traveling along the path;
and
while traveling along the path, operating a suspension system of the vehicle to implement the selected trajectory of vehicle-body motion.
As discussed above regarding claim 1 - Aikin's force profile is a control input rather than a trajectory of vehicle-body motion; Aikin's library-side selection of input profiles is not the same as host-vehicle generation of candidate trajectories; Aikin does not process road-profile data by filtering or otherwise; Nauderer's amplitude-threshold classifier is not a filter-frequency selection mechanism - Aikin and Nauderer do not disclose claim 31's planning step. The Office Action itself acknowledges this gap as to comparison/selection (Office Action p. 36).
Kobilarov is, by its title, a "Trajectory Generation Using Curvature Segments" reference (Kobilarov, title). Kobilarov teaches an autonomous-vehicle path planner that operates in the two- dimensional ground plane. Specifically:
Kobilarov's candidate trajectories are clothoid curve segments connecting reference lines along a centerline, generated by perturbing curvature values of segments (Kobilarov Col. 9; FIGS. 1-2).
Kobilarov's vehicle model is the "bicycle" model - "a vehicle with four wheels is simplified as a motorcycle or bicycle" (Kobilarov Col. 10) - with state variables limited to longitudinal position, lateral position, heading, velocity, and steering angle.
Kobilarov's cost function penalizes "deceleration, jerk, lateral acceleration, yaw, steering angle, steering angle rate" (Kobilarov Col. 12) - all in-plane quantities, none of which is vertical or pitch or roll motion of a vehicle body.
Kobilarov's example actions are "merge left, continue straight, merge right" (Kobilarov Col. 11) - ground-plane path-planning decisions.
Kobilarov's candidate trajectories are therefore in-plane path geometry for an autonomous- vehicle behavioral planner. They have no vertical-motion component, no sprung-mass dynamics, no suspension, and no road-profile filtering. The vehicle model has no vertical dimension. The reference contains no mention of 'filter, " 'frequency, " "road profile, " or "suspension. " Kobilarov is a path/navigation-layer reference; claim 31 is a suspension/vertical-dynamics-layer claim. "Vehicle-body motion" in a suspension-control claim has a specific physical meaning - vertical, pitch, and roll motion of the sprung mass - and Kobilarov's lateral path geometry is not "vehicle- body motion" in that sense.
Moreover, Kobilarov does not generate its candidate trajectories by filtering road-profile data with distinct filter-frequency parameters. Kobilarov's candidates are generated by perturbing curvature values - a geometric operation that has no relationship to filtering or to filter-frequency parameters. Even if a person of ordinary skill in the art were to combine Aikin's force-profile library with Kobilarov's curvature-perturbation candidate generation, the resulting system would not produce the "candidate trajectories of vehicle-body motion" that claim 31 requires, generated "by filtering the road-profile data with a filter having a distinct filter-frequency parameter."14726112
Aikin operates at the actuator-force-command layer; Nauderer operates at the road- classification (amplitude-threshold) layer; Kobilarov operates at the lateral-path-planning layer. The claimed invention operates at the body-motion-trajectory-planning layer through filter-frequency- driven candidate generation, which none of the references discloses. The Office Action's combination assembles pieces from three different layers of the vehicle control stack, but the assembly does not produce the claimed limitation. No combination of these references discloses "planning at least two candidate trajectories of vehicle-body motion ... by filtering the road-profile data with a filter having a distinct filter-frequency parameter," nor "selecting a trajectory that minimizes the negative effect," nor "operating a suspension system of the vehicle to implement the selected trajectory of vehicle-body motion."
Therefore, for at least the above reasons, Aikin, Nauderer, and Kobilarov, individually or in combination, do not inherently or expressly disclose or render obvious the limitations of claim 31.
Examiner respectfully disagrees. Kobilarov teaches the ability of evaluating the various possible trajectories by a cost function that is able to penalize jerk and lateral acceleration (Kobilarov: Col. 11, lines 6 – 22). Furthermore, the Kabilarov is merely teaching the claim limitation stating: “from among the at least two candidate trajectories, selecting a trajectory that minimizes the negative effect of traveling along the path”. Aikin, as substantially argued above, teaches the ability of the road profile of a roadway to be received by the control system. This road profile is based in part of the data received from the vehicle sensors and can also be created in real-time. The control system then takes this data and generates a force profile which is used to minimize frequency responses from the surface of the roadway (Aikin: Paragraph 0031 - 0032). Aikin further teaches the force profile to be adjusted to minimize the frequency response from the surface (Aikin: Paragraph 0032). The suspension position for the actuators are taught to be adjusted for low and high frequencies (Aikin: Paragraph 0028), therefore the force profile is able to be adjusted to minimize these frequencies. Kobilarov is brought in to teach the ability of the evaluating multiple possible trajectories to select the trajectory with the lowest cost. This ability of Kobilarov when combined with Aikin would be obvious to try it allows Aikin to further create multiple force profiles to be evaluated. This increases the amount of minimization of a frequency response from a surface of a roadway as the cost function can negatively penalize, for example, any jerk movement. This improves the current system of Aikin as it is able to select multiple force profile evaluated through a cost function, as taught by Kobilarov, and then select the best one to use which minimizes the jerk from the roadway surface.
Conclusion
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 SHIVAM SHARMA whose telephone number is (703)756-1726. The examiner can normally be reached Monday-Friday 8:00-5:00.
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, Erin Bishop can be reached at 571-270-3713. 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.
/SHIVAM SHARMA/ Examiner, Art Unit 3665
/Erin D Bishop/ Supervisory Patent Examiner, Art Unit 3665
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