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 .
This is a final office action on the merits. Claims 1-21 are currently pending and are addressed below.
The examiner notes that the fundamentals of the rejection are based on the broadest reasonable interpretation of the claim language. Applicant is kindly invited to consider the reference as a whole. References are to be interpreted as by one of ordinary skill in the art rather than as by a novice. See MPEP 2141. Therefore, the relevant inquiry when interpreting a reference is not what the reference expressly discloses on its face but what the reference would teach or suggest to one of ordinary skill in the art.
Response to Arguments
Applicant’s arguments with respect to the rejection of claims 1-21 under 35 U.S.C 103 have been considered but are not persuasive. According to applicant’s remarks, the cited sections of Sol related to an acoustic sensor configured to detect acoustic signals associated with tire noise mentions the detection of such, and that the brief mention of acoustic-related sensors would not be considered by one of ordinary skill in the art, to constitute description of the recited features related to an acoustic sensor configured to detect acoustic signals associated with tire noise. The examiner believes this reads too narrowly as Sol discloses an autonomous vehicle having a controller coupled to a plurality of sensors, including LIDAR devices, cameras, radars, GPS sensors, IMUs, odometry sensors such as wheel encoders, and “any other suitable sensors,” including any other acoustic sensors (see at least Sol, ¶¶ [0065]).
The reference further teaches that sensor data is provided to autonomous vehicle control components, including the planner, motion controller, localizer, perception engine, and local map generator. Calibration, or estimation may include parameters such as surface road friction. Surface road friction in a wheeled vehicle occurs at the tire to road interface. Accordingly, a person of ordinary skill in the art would have understood that sensor data associated with tire-road interaction is one predictable type of information generated at the interface. As such, when Sol’s disclosure of acoustic-energy based sensors read in the context of its autonomous road vehicle and surface road friction estimation teachings, suggests using acoustic sensor data with tire-road interaction in connection with determining surface road friction. Moreover, the combination of Levinson and Qingrong would have rendered the claimed acoustic/friction features obvious. Levinson teaches that acoustic sensors are suitable in an autonomous road vehicle system and that surface road friction may be estimated. In turn, Qingrong teaches determining road friction values from sensor signals indicative of road surface conditions and controlling vehicle operation based on those friction values. It would have been obvious to a person of ordinary skill in the art to use the acoustic sensor taught by Levinson as one of the components for obtaining road surface condition information in the automated driving system of Qingrong’s disclosure since tire-road acoustic signals are generated by the same interaction of the vehicle’s tires on the road surface from which surface friction can occur.
Additionally, the argument that Zheng’s focus on UAV flight operations cannot be combined with Sol is not persuasive. Zheng is not relied upon as teaching tire noise, roadway surface friction, or acoustic signals generated by the tires. Rather, the examiner believes the disclosure is tied to teaching vehicle control and motion planning based on distance data and object/obstacle planning in a direction of travel and vehicle kinematic constraints. Applicant’s argument that Zheng recites a UAV does not negate the motivation to combine as the rejection does not require incorporating Zheng’s UAV into Sol’s road vehicle. Instead, Zheng is the general vehicle control concept of using object information in the direction of travel and kinematic constraints to determine a safe motion profile and control a vehicle operation. The examiner believes the concept is reasonable applicable to Sol’s automated driving system because vehicles likewise must account for objects in the direction of travel, available deceleration, maximum speed, and safe motion planning when generating control instructions. A person of ordinary skill in the art would have reason to combine Zheng’s motion planning teachings with Sol and Qingrong because the references concern automated or remotely controlled vehicle operation used sensed information to improve safe navigation and motion planning control. As such, the examiner respectfully disagrees and the rejection is maintained.
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 1-21 are rejected under 35 U.S.C. 103 as being unpatentable over Yang Zheng et al. (CN114527783A), hereinafter referred to as Zheng, in view of Zhao Qingrong et al. (US2020257292A1), hereinafter referred to as Qingrong. in further view of Levinson Jesse Sol et al. (US20190361432A1) hereinafter referred to as Sol.
Regarding claim 1, Zheng discloses: a method to dynamically control a vehicle via a remote driving system (see at least Zheng pg.31, par.5 which details of a method to control a UAV, which is defined as an unmanned aircraft and controlled by radio remote control equipment), comprising:
receiving, by the processor from a time-of-flight sensor onboard the vehicle, distance data to an object in the longitudinal movement direction of the vehicle (see at least pg.34, par.2-3 which discloses the process of motion planning involving information of each obstacle (an object) in the flight direction (longitudinal) of the UAV)
determining, by the processor, a maximum speed in the longitudinal movement direction based on the maximum deceleration and the distance data (see at least Zheng, pg.35, par.7-11 which discloses the determination of kinematic factors within a UAV motion profile such as speed, acceleration (in this instance it can be negative, zero, or positive), and jerk, a factor which is measured as a rate of change for acceleration)
instructing, by the processor, operation of the vehicle based at least in part on the maximum speed (see at least Zheng, pg.35, par.12 which discloses how these kinematic features can influence a set flight path, pg.39, par.10)
Zheng is silent on, however, in the same field of endeavor, Qinrong teaches: determining, by the processor, a maximum deceleration in a longitudinal movement direction of the vehicle based on the surface friction conditions (see at least Qingrong, ¶¶ [0012]-[0013] which disclose that friction values are used to determine a maximum deceleration)
It would have been obvious to a person of ordinary skill in the art to modify Zheng to include determining, by the processor, a maximum deceleration in a longitudinal movement direction of the vehicle based on the surface friction conditions as taught by Qingrong. Doing so would allow for an improvement to the base device of Zheng to include adaptive measures that prospectively acclimate vehicle operations to certain friction road conditions.
Modified Zhang is silent on, however, in the same field of endeavor, Sol teaches: receiving, by a processor at a teleoperator station via a communication network, environment data from an environment sensor onboard the vehicle, the vehicle being operated on a surface of a roadway, within an environment remote from the teleoperator station (see at least Sol Fig.10; Fig.36 which discloses receiving environment data from an environment sensor onboard a vehicle at a remote teleoperator station; ¶¶ [0056], [0068]-[0070] which discloses , the vehicle being operated on a surface of a roadway, within an environment remote from the teleoperator station communicating environment data obtained from sensors onboard)
the environment sensor comprising at least one of a laser sensor or an acoustic sensor configured to detect acoustic signals associated with tire noise generated by tires of the vehicle (see at least Sol, Fig.3, “Item 341” ¶¶ [0057], [0065] which discloses the environment sensor comprising at least one of a laser sensor or an acoustic sensor configured to detect acoustic signals)
determining, by the processor, surface friction conditions of the surface in the environment proximate the vehicle based on the environment data (see at least Sol, Fig.2 ¶¶ [0055], [0070], which discloses the determination of surface friction conditions of the surface in the environment proximate the vehicle based on the environment data)
It would have been obvious to a person of ordinary skill in the art to change modified Zhang to include: receiving, by a processor at a teleoperator station via a communication network, environment data from an environment sensor onboard the vehicle, the vehicle being operated on a surface of a roadway, within an environment remote from the teleoperator station as taught by Sol. The examiner would like to note that the disclosure of modified Zhang explicitly discloses determining surface friction conditions off the surface in the environment, proximate to the vehicle based on the environment data, however, specific environment sensors associated with acoustic signals required by the claim language is inherent and not directly stated, as such, Sol is provided. It is entirely possible to incorporate the teachings of Sol into the disclosure of modified Zhang using its components to achieve the same end result. The addition of Sol’s teachings would also provide further improvement of accuracy towards the end result of modified Zhang’s disclosure.
Regarding claim 2, Zheng is silent on, however in the same field of endeavor, Qingrong teaches: the method of claim 1, wherein the environment data comprises at least one of weather conditions or driving surface conditions in the environment proximate the vehicle (see at least Qingrong, ¶¶ [0032] which discloses sensors indicative of road surface conditions)
It would have been obvious to a person of ordinary skill in the art to modify Zheng to include the method of claim 1, wherein the environment data comprises at least one of weather conditions or driving surface conditions in the environment proximate the vehicle as taught by Qingrong. Doing so would allow for adaptive measures to prospectively acclimate vehicle operations to certain friction road conditions.
Regarding claim 3, Zheng discloses: the method of claim 1, further comprising:
receiving, by the processor from a vehicle dynamics sensor, a current speed in the longitudinal movement direction of the vehicle (see at least Zheng, pg. 32, par.4 which discloses the obstacle avoidance perception model and its ability to obtain position, speed, acceleration…data to characterize the current motions of a UAV)
wherein instructing operation of the vehicle based at least in part on the maximum speed comprises maintaining the current speed at or below the maximum speed (see at least Zheng, pg.35, par.7-11 which discloses the motion planning preparation data used to instruct a UAV flight path, where a speed constraint is set according, but not limited to a maximum speed value, pg.36, par.3 discloses an example of a speed constraint where the speed is kept within the bounds of a minimum and maximum value depending on the parameter)
Regarding claim 4, modified Zheng discloses: the method of claim 1, further comprising:
receiving, by the processor, video data from an imaging device onboard the vehicle (see at least Qingrong, ¶¶ [0026] which discloses image data indicating a field-of-view of the vehicle)
Modified Zheng is silent on, however in the same field of endeavor, Sol teaches: causing, by the processor via a presentation device at the teleoperator station, presentation of a notification based on the maximum speed (see at least Sol, ¶¶ [0061] which discloses the tracking data consisting of maximum speed, ¶¶ [0078], which discloses an example of data exchange generated by a planner which notifies a teleoperator about a subset of data, including but not limited to the tracking data)
It would have been obvious to a person of ordinary skill in the art to further change modified Zheng to include causing, by the processor via a presentation device at the teleoperator station, presentation of a notification based on the maximum speed as taught by Sol. Doing so would allow for an exchange of data for facilitating teleoperations between a unmanned vehicle and a teleoperator in a remote location.
Regarding claim 5, modified Zheng is silent on, however in the same field of endeavor, Sol teaches: the method of claim 4, wherein the notification comprises at least one of a visual notification, an audio notification, or a haptic notification (see at least Sol, ¶¶ [0061], [0078], [0086] which discloses the notifying of a teleoperator of subsequent data generated)
It would have been obvious to a person of ordinary skill in the art to further change modified Zheng to include the method of claim 4, wherein the notification comprises at least one of a visual notification, an audio notification, or a haptic notification as taught by Sol. Doing so would allow for an exchange of data for facilitating teleoperations between a unmanned vehicle and a teleoperator in a remote location.
Regarding claim 6, Zheng discloses: a method (see at least Zheng pg.31, par.5 which details of a method to control a UAV, which is defined as an unmanned aircraft and controlled by radio remote control equipment), comprising:
receiving, by the processor from at least one sensor associated with the vehicle, data related to at least one of a current speed of the vehicle, a distance to an object in a movement direction of the vehicle, or a current steering angle of the vehicle (see at least Zheng pg.34, par.2-3 which discloses the process of motion planning involving information of each obstacle (an object) in the flight direction (longitudinal) of the UAV)
determining, by the processor, at least one dynamic control limit based on the maximum acceleration and at least one of the current speed, the distance to the object, or the current steering angle (see at least Zheng pg.35, par.7-11 which discloses the determination of kinematic factors within a UAV motion profile such as speed, acceleration (in this instance it can be negative, zero, or positive), and jerk, a factor which is measured as a rate of change for acceleration)
wherein the at least one dynamic control limit comprises a maximum steering angle (see at least Zheng pg.35, par.7-11 which discloses the determination of kinematic factors within a UAV motion profile such as speed, acceleration (in this instance it can be negative, zero, or positive), and jerk, a factor which is measured as a rate of change for acceleration)
instructing, by the processor, operation of the vehicle based on the at least one dynamic control limit (see at least Zheng, pg.35, par.12 which discloses how these kinematic features can influence a set flight path, pg.39, par.10)
Zheng is silent on, however, in the same field of endeavor, Qingrong teaches: determining, by the processor, a maximum acceleration of the vehicle based at least in part on the surface friction conditions (see at least Qingrong, ¶¶ [0012]-[0013] which disclose that friction values are used to determine a maximum acceleration)
It would have been obvious to a person of ordinary skill in the art to modify Zheng to include the environment sensor comprising at least one of a laser sensor or an acoustic sensor configured to detect characteristics of at least one of tires of the vehicle or the surface of the roadway within the environment, determining, by the processor, surface friction conditions in the environment proximate the vehicle based on the environment data and determining, by the processor, a maximum acceleration of the vehicle based at least in part on the surface friction conditions as taught by Qingrong. Doing so would allow for an improvement to the base device of Zheng to include adaptive measures that prospectively acclimate vehicle operations to certain friction road conditions.
Modified Zhang is silent on, however, in the same field of endeavor, Sol teaches: receiving, by a processor associated with a teleoperator station via a network, environment data from an environment sensor associated with the vehicle, the vehicle being operated on a surface of a roadway within an environment remote from the teleoperator station (see at least Sol Fig.10; Fig.36 which discloses receiving environment data from an environment sensor onboard a vehicle at a remote teleoperator station; ¶¶ [0056], [0069]-[0070] which discloses, the vehicle being operated on a surface of a roadway, within an environment remote from the teleoperator station communicating environment data obtained from sensors onboard)
determining, by the processor, surface friction conditions in the environment proximate the vehicle based on the environment data (see at least Sol, Fig.2 ¶¶ [0059], [0074], [0145], which discloses the determination of surface friction conditions of the surface in the environment proximate the vehicle based on the environment data)
It would have been obvious to a person of ordinary skill in the art to change modified Zhang to include: receiving, by a processor at a teleoperator station via a communication network, environment data from an environment sensor onboard the vehicle, the vehicle being operated on a surface of a roadway, within an environment remote from the teleoperator station as taught by Sol. The examiner would like to note that the disclosure of modified Zhang explicitly discloses determining surface friction conditions off the surface in the environment, proximate to the vehicle based on the environment data, however, specific environment sensors associated with acoustic signals required by the claim language is inherent and not directly stated, as such, Sol is provided. It is entirely possible to incorporate the teachings of Sol into the disclosure of modified Zhang using its components to achieve the same end result. The addition of Sol’s teachings would also provide further improvement of accuracy towards the end result of modified Zhang’s disclosure.
Regarding claim 7, Zheng is silent on, however, in the same field of endeavor, Qingrong teaches: the method of claim 6, further comprising:
receiving, by the processor, additional environment data from additional environment sensors associated with additional vehicles within the environment (see at least Qingrong, ¶¶ [0028-[0030] discloses an example of a surrounding vehicle environment where a “target” vehicle is detected, there are other subject vehicles disclosed, as well as their distances)
wherein the surface friction conditions in the environment proximate the vehicle are further determined based on the additional environment data (see at least Qingrong, ¶¶ [0026],. [0028]-[0032])
It would have been obvious to a person of ordinary skill in the art to modify Zheng to include receiving, by the processor, additional environment data from additional environment sensors associated with additional vehicles within the environment and wherein the friction conditions in the environment proximate the vehicle are further determined based on the additional environment data as taught by Qingrong. Doing so would allow for adaptivity to various road conditions as well as an awareness of surrounding vehicles.
Regarding claim 8, Zheng discloses: the method of claim 6, further comprising:
receiving, by the processor, vehicle dynamics data from the at least one sensor associated with the vehicle (see at least Zheng, pg.35, par.5-11 which discloses the motion planning step which takes into account vehicle dynamics obtained from sensors such as current motion state, constraint conditions, and flight position)
Zheng is silent on, however, in the same field of endeavor, Qingrong teaches: wherein the surface friction conditions in the environment proximate the vehicle are further determined based on the vehicle dynamics data (see at least Qingrong, ¶¶ [0028]-[0032])
Regarding claim 9, Zheng is silent on, however, in the same field of endeavor, Qingrong teaches: the method of claim 6, wherein the environment sensor further comprises at least one of an optical sensor, an acoustic sensor, or laser sensor configured to detect characteristics of at least one of the tires of the vehicle or the surface of the roadway within the environment (see at least Qingrong, ¶¶ [0009] which discloses the various sensors that may be used to determine road segment conditions/friction values, [0026] discloses an optical sensor)
It would have been obvious to a person of ordinary skill in the art to modify Zheng to include the method of claim 6, wherein the environment sensor comprises at least one of an optical sensor, a laser sensor, or an acoustic sensor configured to detect characteristics of at least one of tires of the vehicle or a surface of a roadway within the environment as taught by Qingrong. Doing so would allow for sensor signals from one or more sensing devices indicative of road surface conditions of adjoining road segments being driven across.
Regarding claim 10, Zheng discloses: the method of claim 6, wherein the at least one sensor associated with the vehicle comprises at least one of a vehicle dynamics sensor, a radar sensor, a light detection and ranging (LIDAR) sensor, or an imaging sensor (see at least Zheng, pg.42, par.6 which discloses a radar sensor)
Regarding claim 11, Zheng discloses: the method of claim 6, wherein the maximum acceleration comprises:
at least one of a maximum longitudinal deceleration or a maximum lateral acceleration (see at least Zheng, pg.35, par.7-11)
Zheng is silent on, however, in the same field of endeavor Qingrong teaches: wherein the maximum longitudinal deceleration is determined based at least in part on a longitudinal coefficient of friction between tires of the vehicle and the surface of the roadway within the environment (see at least Qingrong, ¶¶ [0026], [0032]-[0033])
an acceleration due to gravity; or the maximum lateral acceleration is determined based at least in part on a lateral coefficient of friction between the tires of the vehicle and the surface of the roadway within the environment, and the acceleration due to gravity (see at least Qingrong, ¶¶ [0026], [0032]-[0033])
It would have been obvious to a person of ordinary skill in the art to modify Zheng to include wherein the maximum longitudinal deceleration is determined based at least in part on a longitudinal coefficient of friction between tires of the vehicle and a surface of a roadway within the environment and an acceleration due to gravity; or the maximum lateral acceleration is determined based at least in part on a lateral coefficient of friction between the tires of the vehicle and the surface of the roadway within the environment, and the acceleration due to gravity as taught by Qingrong. Doing so would allow for a road friction scenario estimate which will allow a vehicle to acclimate to various road conditions.
Regarding claim 12, Zheng discloses: the method of claim 11, wherein the at least one dynamic control limit comprises at least one of the maximum longitudinal deceleration, a maximum speed, or a minimum stopping distance (see at least pg.35, par.7-11 which discloses the determination of kinematic factors within a UAV motion profile such as speed, acceleration (in this instance it can be negative, zero, or positive), and jerk, a factor which is measured as a rate of change for acceleration)
Regarding claim 13, Zheng discloses: the method of claim 12, wherein the maximum speed is determined based on:
at least in part on the maximum longitudinal deceleration and the distance to the object (see at least pg.35, par.7-11 which discloses the determination of kinematic factors within a UAV motion profile such as speed, acceleration (in this instance it can be negative, zero, or positive), and jerk, a factor which is measured as a rate of change for acceleration)
Zheng is silent on, however, in the same field of endeavor, Qingrong teaches: wherein the minimum stopping distance is determined based at least in part on the maximum longitudinal deceleration and the current speed (see at least Qingrong, ¶¶ [0011]-[0012], [0038]-[0039], [0044] which disclose braking distance)
wherein the maximum steering angle is determined based at least in part on the maximum lateral acceleration and the current speed; or wherein the maximum speed is determined based at least in part on the maximum lateral acceleration and the current steering angle (see at least Qingrong, ¶¶ [0014], [0042]-[0043])
It would have been obvious to a person of ordinary skill in the art to modify Zheng to include wherein the minimum stopping distance is determined based at least in part on the maximum longitudinal deceleration and the current speed and wherein the maximum steering angle is determined based at least in part on the maximum lateral acceleration and the current speed; or wherein the maximum speed is determined based at least in part on the maximum lateral acceleration and the current steering angle as taught by Qingrong. Doing so would allow for a road friction scenario estimate which will allow a vehicle to acclimate to various road conditions.
Regarding claim 14, modified Zheng discloses: the method of claim 6, further comprising:
receiving, by the processor from an imaging device associated with the vehicle, video data of the environment proximate the vehicle (see at least Qingrong, ¶¶ [0026] which discloses image data indicating a field-of-view of the vehicle)
Modified Zheng is silent on, however in the same field of endeavor, Sol teaches: wherein instructing operation of the vehicle comprises causing, by the processor via a presentation device at the teleoperator station, presentation of a notification based on the at least one dynamic control limit with presentation of the video data (see at least Sol, ¶¶ [0061], [0078], [0086] which discloses the notifying of a teleoperator of subsequent data generated)
wherein the notification comprises at least one of a visual notification, an audio notification, or a haptic notification (see at least Sol, ¶¶ [0061], [0078], [0086] which discloses the notifying of a teleoperator of subsequent data generated)
It would have been obvious to a person of ordinary skill in the art to further change modified Zheng to include wherein instructing operation of the vehicle comprises causing, by the processor via a presentation device at the teleoperator station, presentation of a notification based on the at least one dynamic control limit with presentation of the video data and wherein the notification comprises at least one of a visual notification, an audio notification, or a haptic notification as taught by Sol. Doing so would allow for the reception of telemetry data through data exchange in facilitating teleoperations.
Regarding claim 15, modified Zheng is silent on, however in the same field of endeavor, Sol teaches: the method of claim 6, further comprising:
providing, via an output device at the teleoperator station, feedback to a teleoperator based on the environment data of the environment proximate the vehicle (see at least Sol, ¶¶ [0077]-[0079], [0106] which discloses feedback data)
wherein the feedback comprises at least one of visual feedback, audio feedback, or haptic feedback (see at least Sol, ¶¶ [0061], [0078], [0086] which discloses the notifying of a teleoperator of subsequent data generated, [0106])
It would have been obvious to a person of ordinary skill in the art to further change modified Zheng to include providing, via an output device at the teleoperator station, feedback to a teleoperator based on the environment data of the environment proximate the vehicle and wherein the feedback comprises at least one of visual feedback, audio feedback, or haptic feedback as taught by Sol. Doing so would allow for the reception of feedback data through data exchange in facilitating teleoperations.
Regarding claim 16, modified Zheng is silent on, however in the same field of endeavor, Sol teaches: the method of claim 15, wherein the visual feedback comprises simulated operation of at least one of windshield wipers, defroster, or defogger based on the environment data (see at least Sol, ¶¶ [0074], [0089], [0110])
wherein the audio feedback comprises simulated sound based on the environment data; or wherein the haptic feedback comprises simulated environment characteristics at the teleoperator station based on the environment data (see at least Sol, ¶¶ [0074], [0089], [0110])
It would have been obvious to a person of ordinary skill in the art to further change modified Zheng to include the method of claim 15, wherein the visual feedback comprises simulated operation of at least one of windshield wipers, defroster, or defogger based on the environment data and wherein the audio feedback comprises simulated sound based on the environment data; or wherein the haptic feedback comprises simulated environment characteristics at the teleoperator station based on the environment data as taught by Sol. Doing so would allow for the simulation of various conditions a vehicle experiences in an environment.
Regarding claim 17, Zheng discloses: a remote driving system comprising: (see at least Zheng pg.31, par.5 which details of a method to control a UAV, which is defined as an unmanned aircraft and controlled by radio remote control equipment), comprising:
a vehicle configured to operate on a surface of a roadway within an environment (see at least Zheng pg.30, par.5), the vehicle comprising:
an environment sensor and at least on additional sensor (see at least Zheng, pg.30, par.5, pg.31, par 10)
receive environment data from the environment sensor associated with the vehicle (see at least Zheng, pg.30, par.5, pg.31, par 10 discloses receiving environment data from the environment sensor associated with the vehicle)
determine a maximum acceleration of the vehicle based at least in part on the surface friction conditions (see at least Zheng, pg.35, par.7-11 which discloses the determination of kinematic factors within a UAV motion profile such as speed, acceleration (in this instance it can be negative, zero, or positive), and jerk, a factor which is measured as a rate of change for acceleration)
receive, from the at least one additional sensor, data related to at least one of a current speed of the vehicle, a distance to an object in a movement direction of the vehicle, or a current steering angle of the vehicle (see at least Zheng, pg. 32, par.4 which discloses the obstacle avoidance perception model and its ability to obtain position, speed, acceleration…data to characterize the current motions of a UAV)
determine at least one dynamic control limit based on the maximum acceleration and at least one of the current speed, the distance to the object, or the current steering angle (see at least Zheng pg.35, par.7-11 which discloses the determination of kinematic factors within a UAV motion profile such as speed, acceleration (in this instance it can be negative, zero, or positive), and jerk, a factor which is measured as a rate of change for acceleration)
wherein the at least one dynamic control limit comprises a maximum steering angle (see at least Zheng pg.35, par.7-11 which discloses the determination of kinematic factors within a UAV motion profile such as speed, acceleration (in this instance it can be negative, zero, or positive), and jerk, a factor which is measured as a rate of change for acceleration)
instruct operation of the vehicle based on the at least one dynamic control limit (see at least Zheng, pg.35, par.12 which discloses how these kinematic features can influence a set flight path, pg.39, par.10)
Modified Zheng is silent on, however, in the same field of endeavor, Sol teaches:
a teleoperator station that is remote from the vehicle, the teleoperator station in communication with the vehicle via a communication network, the teleoperator station comprising a control interface, a presentation device, and a processor (see at least Sol Fig.10; Fig.36 which discloses receiving environment data from an environment sensor onboard a vehicle at a remote teleoperator station; ¶¶ [0056], [0068]-[0070] which discloses , the vehicle being operated on a surface of a roadway, within an environment remote from the teleoperator station communicating environment data obtained from sensors onboard)
wherein the processor is configured to at least:
determine surface friction conditions of the surface in the environment proximate the vehicle based on the environment data (see at least Sol, Fig.2 ¶¶ [0055], [0070], which discloses the determination of surface friction conditions of the surface in the environment proximate the vehicle based on the environment data)
It would have been obvious to a person of ordinary skill in the art to change modified Zhang to include: wherein the environmental sensor comprises an acoustic sensor configured to detect acoustic signals associated with tire noise generated by tires of the vehicle, a teleoperator station that is remote from the vehicle, the teleoperator station in communication with the vehicle via a communication network, the teleoperator station comprising a control interface, a presentation device, and a processor, and receive environment data from the environment sensor associated with the vehicle determine surface friction conditions of the surface in the environment proximate the vehicle based on the environment data as taught by Sol. The examiner would like to note that the disclosure of modified Zhang explicitly discloses determining surface friction conditions off the surface in the environment, proximate to the vehicle based on the environment data, however, specific environment sensors associated with acoustic signals required by the claim language is inherent and not directly stated, as such, Sol is provided. It is entirely possible to incorporate the teachings of Sol into the disclosure of modified Zhang using its components to achieve the same end result. The addition of Sol’s teachings would also provide further improvement of accuracy towards the end result of modified Zhang’s disclosure.
Regarding claim 18, Zheng is silent on, however, in the same field of endeavor, Qinrong discloses: the remote driving system of claim 17, wherein the environment sensor comprises at least one of an optical sensor, an acoustic sensor, or a laser sensor, and wherein the at least one additional sensor comprises at least one of a vehicle dynamics sensor, a radar sensor, a light detection and ranging (LIDAR) sensor, or an imaging sensor (see at least Qingrong, ¶¶ [0009] which discloses the various sensors that may be used to determine road segment conditions/friction values)
It would have been obvious to a person of ordinary skill in the art to modify Zheng to include the remote driving system of claim 17, wherein the environment sensor comprises at least one of an optical sensor, a laser sensor, or an acoustic sensor; and wherein the at least one additional sensor comprises at least one of a vehicle dynamics sensor, a radar sensor, a light detection and ranging (LIDAR) sensor, or an imaging sensor as taught by Qingrong. Doing so would allow for sensor signals from one or more sensing devices indicative of road surface conditions of adjoining road segments being driven across.
Regarding claim 19, modified Zheng discloses: the remote driving system of claim 17, wherein the vehicle further comprises:
an imaging device (see at least Qingrong, ¶¶ [0026] which discloses image data indicating a field-of-view of the vehicle)
wherein the processor is further configured to:
receive, from the imaging device, video data of the environment proximate the vehicle (see at least Qingrong, ¶¶ [0026] which discloses image data indicating a field-of-view of the vehicle)
Modified Zheng is silent on, however in the same field of endeavor, Sol teaches: cause via the presentation device, presentation of a notification based on the at least one dynamic control limit with presentation of the video data (see at least Sol, ¶¶ [0061], [0078], [0086] which discloses the notifying of a teleoperator of subsequent data generated)
It would have been obvious to a person of ordinary skill in the art to further change modified Zheng to include cause via the presentation device, presentation of a notification based on the at least one dynamic control limit with presentation of the video data as taught by Sol. Doing so would allow for the reception of telemetry data through data exchange in facilitating teleoperations.
Regarding claim 20, modified Zheng is silent on, however in the same field of endeavor, Sol teaches: the remote driving system of claim 17, wherein the teleoperator station further comprises:
an output device (see at least Sol, ¶¶ [0077]-[0079], [0106] which discloses feedback data)
wherein the processor is further configured to:
provide, via the output device, feedback to a teleoperator based on the environment data of the environment proximate the vehicle (see at least Sol, ¶¶ [0077]-[0079], [0106] which discloses feedback data to a teleoperator based on the environment data of the environment proximate the vehicle)
wherein the feedback comprises at least one of visual feedback, audio feedback, or haptic feedback (see at least Sol, ¶¶ [0061], [0078], [0086] which discloses the notifying of a teleoperator of subsequent data generated, [0106])
It would have been obvious to a person of ordinary skill in the art to further change modified Zheng to include providing, via an output device at the teleoperator station, feedback to a teleoperator based on the environment data of the environment proximate the vehicle and wherein the feedback comprises at least one of visual feedback, audio feedback, or haptic feedback as taught by Sol. Doing so would allow for the reception of feedback data through data exchange in facilitating teleoperations.
Regarding claim 21, modified Zheng is silent on, however in the same field of endeavor, Sol teaches: the method of claim 9, wherein the acoustic sensor is configured to detect acoustic signals associated with tire noise generated by the tires of the vehicle and wherein the acoustic signals associated with the tire noise generated by the tires of the vehicle further comprise tire noise associated with at least one of smooth surfaces, loose terrain, dry surfaces, wet surfaces, snowy surfaces, or icy surfaces (see at least Sol, Fig.3, “Item 341” ¶¶ [0057], [0065] which discloses the environment sensor comprising at least one of a laser sensor or an acoustic sensor configured to detect acoustic signals; Fig.2 ¶¶ [0055], [0070], which discloses the determination of surface friction conditions of the surface in the environment proximate the vehicle based on the environment data, this means wherein the acoustic signals associated with the tire noise generated by the tires of the vehicle further comprise tire noise associated with at least one of smooth surfaces, loose terrain, dry surfaces, wet surfaces, snowy surfaces, or icy surfaces)
It would have been obvious to a person of ordinary skill in the art to further change modified Zheng to include the method of claim 6, wherein the acoustic signals associated with the tire noise generated by the tires of the vehicle further comprise tire noise associated with at least one of smooth surfaces, loose terrain, dry surfaces, wet surfaces, snowy surfaces, or icy surfaces as taught by Sol. The examiner would like to note that the disclosure of modified Zhang explicitly discloses determining surface friction conditions off the surface in the environment, proximate to the vehicle based on the environment data, however, specific environment sensors associated with acoustic signals required by the claim language is inherent and not directly stated, as such, Sol is provided. It is entirely possible to incorporate the teachings of Sol into the disclosure of modified Zhang using its components to achieve the same end result. The addition of Sol’s teachings would also provide further improvement of accuracy towards the end result of modified Zhang’s disclosure.
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.
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/KIRSTEN JADE M SANTOS/Examiner, Art Unit 3664
/RACHID BENDIDI/Supervisory Patent Examiner, Art Unit 3664
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